{ "count" : 82961, "data" : [ { "id" : "6a2ca5bd74d8ee00a09b7ee8", "title" : "Principal Data Scientist", "company" : "Intellishore", "industry" : "Consulting", "salary" : { "min" : 950000.0, "max" : 1450000.0, "currency" : "DKK", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Denmark, adjusted for executive seniority, biotech industry, and Copenhagen city tier." }, "location" : "Copenhagen", "locations" : [ "Copenhagen" ], "timestamp" : "2026-06-16T00:46:31.765", "fingerprint" : "9488786ac1ba448028ae7190dbf3c956e5ec1dfccd326cf39dd5db85c2c2d3e4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/intellishoredk/jobs/7724568003", "externalId" : "7724568003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Copenhagen", "country" : "Denmark", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "55.6867243,12.5700724" } ], "locationText" : "Copenhagen, Denmark", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Machine learning, Forecasting", "professionalSkills" : [ "Client engagements", "Business critical programs", "Commercial measurement", "Data science workstream", "Methodology development", "Offering development" ], "hardSkillsList" : [ "Machine learning", "Forecasting", "Causal inference", "Measurement" ], "hardSkills" : [ { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Forecasting", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" }, { "name" : "Measurement", "level" : "intermediate" } ], "majorSkills" : "Machine learning, Forecasting, Causal inference", "majorSkillsList" : [ "Machine learning", "Forecasting", "Causal inference" ], "coreResponsibilities" : "Lead data science workstream on client engagements, Set technical bar on machine learning, Set technical bar on forecasting, Build methods and templates, Mentor and grow data scientists, Mentor and grow data engineers, Shape new offerings, Represent Intellishore externally", "teamCollaboration" : "Client executives; Brand leadership; Leadership team", "domainKnowledge" : "Commercial pharma; Regulated industry; Healthcare; Pharma", "domainList" : [ "commercial-pharma", "regulated-industry", "healthcare", "pharma" ], "domainSpecificKnowledge" : [ "Commercial pharma", "Regulated industry", "Healthcare", "Pharma" ], "communicationSkills" : "Thought leadership; Client conversations", "specialRequirements" : "Right to work in Denmark", "qualificationsBasic" : "8+ years in data science, Machine learning experience, Forecasting experience, Commercial context experience, Marketing context experience, Pricing context experience, Lead senior client-facing engagements, Lead business-critical internal programs, Domain grounding in pharma, Domain grounding in healthcare, Domain grounding in regulated industry", "qualificationsPreferred" : "Understanding MLOps, Experience shaping data offerings, Experience shaping AI offerings, Experience launching data offerings, Experience launching AI offerings, Experience shaping data products, Experience shaping AI products, Experience launching data products, Experience launching AI products, Danish language", "remoteFriendly" : false, "workSiteFlexibility" : "Hybrid", "rawDescription" : "The problem we're hiring you to solve Commercial pharma is sitting on a measurement problem. Launch decisions, field force deployment, HCP engagement, pricing - most of the value moves before anyone knows what worked, and the standard playbooks weren't built for fragmented channels, privacy constraints, or the causal questions that actually matter to commercial leaders. And the ground keeps moving - AI is rewriting what \"analytics\" even means to a commercial org, and the regulatory and tech stack underneath it all is shifting faster than most teams can absorb. Intellishore works at the sharp end of this. Our commercial pharma practice partners with global top-20 pharma pioneers on data and AI decisions that shape launches, portfolios, and commercial performance. We're hiring a Principal Data Scientist to lead the technical depth of this work — shaping methodology, owning delivery on our most demanding engagements, and building out how we deliver measurements, causal inference, and machine learning in the next generation of our offerings. What you'll actually do Lead the data science workstream on senior client engagements - typically 1-2 concurrent projects, working directly with client executives and brand leadership. Set the technical bar on machine learning and forecasting across our commercial pharma portfolio and build the methods and templates that scale across the practice and into new segments. Mentor and grow a small team of data scientists and engineers. Team size: 10 today, growing to 30. Shape new offerings alongside our leadership - from scoping to pricing to the IP that underpins them. Represent Intellishore externally: Thought leadership, conferences, and senior client conversations where credibility matters. Who you are Must-haves: 8+ years in data science, with meaningful time spent on machine learning and forecasting in commercial, marketing, or pricing contexts. Track record of leading senior client-facing engagements or business-critical internal programs - consulting, in-house commercial analytics, or both. Strong domain grounding in pharma, healthcare, or another regulated industry where commercial measurement is hard. Nice to have: Understanding MLOps at a level where you know what good looks like and can still get your hands dirty when it matters. Experience shaping or launching data/AI offerings, practices, or products. Danish is a plus, not a requirement. Our working language is English. Why Intellishore? We're a boutique of ~100 people across Copenhagen and Zürich, and our commercial pharma stronghold is genuine - not a side bet. That means three things that matter at your level: Real mandate. You'll own the technical direction of a practice, not a single workstream within a larger machine. If you've wanted to shape how a firm approaches machine learning in healthcare, this is the seat. Concrete path. Practice Lead for ML in Commercial Pharma within 1–2 years; Director track over 2–4 years from hire. We'll map it to your ambitions in the first conversation. Compensation. We'll be direct about level, bonus structure, and the full package early in the process. Practicalities Based in Copenhagen. Expect 3-5 days in the office or at the client site. Travel roughly 5% of weeks, primarily within Europe. You must have the right to work in Denmark at the time of application. Apply We read every application. If most of this resonates, but you don't tick every box, apply anyway — we'd rather have the conversation. Reach out to Sofie Freund with questions: sofie.freund@intellishore.dk · +45 93 98 17 27. We interview on a rolling basis.", "summaryDescription" : "Principal Data Scientist at Intellishore. Skills: Machine learning, Forecasting, Causal inference. Lead data science workstream on client engagements. Set technical bar on machine learning", "postedDate" : "2026-06-14T20:09:49.596", "createdAt" : "2026-06-14T20:09:49.596", "lastUpdated" : "2026-06-16T00:46:31.765", "ingestTimestamp" : "2026-06-14T20:09:49.596", "mongoId" : "6a2ca5bd74d8ee00a09b7ee8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Machine learning", "Forecasting", "Causal inference", "Measurement", "Client engagements", "Business critical programs", "Commercial measurement", "Data science workstream", "Methodology development", "Offering development", "Commercial pharma", "Regulated industry", "Healthcare", "Pharma" ], "skillCount" : 14, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Executive", "dataQualityScore" : 1.0, "_score" : 990.384, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.95 }, { "id" : "68b706987fc9a711f0f6fd2e", "title" : "Principal Applied Scientist", "company" : "Amazon Development Center U.S., Inc.", "industry" : "Data Science, Applied Science, Cloud Computing", "salary" : { "min" : 179000.0, "max" : 309400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T02:15:48.309", "fingerprint" : "ee5be20183b9084bfd8649f55be2c1035dfda061915f2779e3ca2b22f40ec819", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3052445/apply", "externalId" : "837843be-4907-4b0f-b91e-9e829b40bcd8", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI, ML, NLP, Computer vision, Deep learning, AWS, Amazon Lex, Amazon Polly, AWS Lambda, Amazon S3, Amazon Kinesis", "professionalSkills" : [ "Scientific vision", "Business applications", "Turnkey solutions", "Customer impact", "Responsible AI" ], "hardSkillsList" : [ "Machine learning", "AI systems", "Scientific research", "Data science" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "AI systems", "level" : "intermediate" }, { "name" : "Scientific research", "level" : "intermediate" }, { "name" : "Data science", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "AI, Machine Learning, Scientific vision", "majorSkillsList" : [ "AI", "Machine Learning", "Scientific vision" ], "coreResponsibilities" : "Drive scientific vision, Advise technical leadership, Initiate design of science solutions, Lead design of science solutions, Deliver science solutions, Propose innovative solutions, Influence organization adoption, Mentor scientists, Develop scientists", "teamCollaboration" : "Senior technical leaders; Across AWS; Product teams; Engineering teams", "domainKnowledge" : "Contact center; Cloud-based contact center; Artificial Intelligence; AWS services", "domainList" : [ "contact-center", "cloud-based-contact-center", "artificial-intelligence", "aws-services" ], "domainSpecificKnowledge" : [ "Contact center", "Cloud-based contact center", "Artificial Intelligence", "AWS services" ], "communicationSkills" : "Influence across organizations", "innovationCreativity" : "Rapid innovation; Innovative solutions", "problemSolvingSkills" : "Exceptional problem-solving; Analytical skills; Decision making; Ambiguous problem spaces", "outcomesObjectives" : "Deliver measurable customer impact", "qualificationsBasic" : "PhD in Computer Science, 10+ years research experience, Production AI/ML systems delivery, Deep expertise in AI/ML, Publication record, Experience leading teams, Exceptional problem-solving skills, Exceptional analytical skills", "qualificationsPreferred" : "Experience with large-scale ML systems, Experience with cloud computing, Track record of driving scientific innovation, Experience partnering with product teams, Experience partnering with engineering teams, Translate complex scientific concepts", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Principal Applied Scientist will drive the scientific vision for AI systems. The role requires tackling intrinsically hard, previously unsolved problems while balancing rapid innovation with reliability and compliance. You should be comfortable making decisions with incomplete information and driving solutions in ambiguous problem spaces. You'll work closely with senior technical leaders within the team and across AWS. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Drive the scientific vision of teams in the organization and advise technical leadership on scientific challenges * Initiate and lead the design and delivery of science solutions that address significantly large or endemic customer and business problems * Propose innovative solutions to intrinsically hard, previously unsolved problems * Influence the organization towards adopting new approaches, concepts, and paradigms * Mentor and develop other scientists, fostering a culture of scientific excellence About the team Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. Amazon Connect is the result of the ten years of development that went into building the tools Amazon uses to provide its award winning customer service at massive scale and launching it as a publicly available AWS service. With Amazon Connect, you can create your own cloud-based contact center and be taking calls in minutes. Amazon Connect leverages the power of Artificial Intelligence and the large ecosystem of AWS services such as Amazon Lex, Amazon Polly, AWS Lambda, Amazon S3 and Amazon Kinesis to provide a truly frustration free, easy-to-use, extensible, and natural customer experience. With this technology, we are transforming an industry and the way customers interact with businesses and how agents service them. Basic Qualifications: * PhD in Computer Science, Machine Learning, or related field * 10+ years of relevant, broad research experience after PhD * Track record of delivering production AI/ML systems with significant customer impact * Deep expertise in one or more areas of AI/ML (e.g., NLP, computer vision, deep learning) * Strong publication record in top-tier conferences or journals * Experience leading and mentoring teams of scientists and engineers * Exceptional problem-solving and analytical skills * Strong communication skills and ability to influence across organizations Preferred Qualifications: * Experience with large-scale machine learning systems and cloud computing * Track record of driving scientific innovation in industry settings * Experience partnering with product and engineering teams to deliver AI solutions * Demonstrated ability to translate complex scientific concepts to non-technical stakeholders Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Principal Applied Scientist at Amazon Development Center U.S., Inc.. Skills: AI, Machine Learning, Scientific vision. Drive scientific vision. 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"6a2c8d5d74d8ee00a0978bc6", "title" : "Lead / Principal Data Scientist", "company" : "UptimeAI", "industry" : "Engineering", "salary" : { "min" : 3500000.0, "max" : 5500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for Lead Data Scientist in Bangalore, India, adjusted for the manufacturing industry and company size." }, "location" : "Bangalore (India)", "locations" : [ "Bangalore (India)" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T03:31:32.901", "fingerprint" : "148b77fc252f79245fd3d809f8a7f1e56cc137a3949e91529d33273144ee9809", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/uptimeai/c8738ec7-92a0-44bf-8fc3-9e83cc7e2f99/application", "externalId" : "c8738ec7-92a0-44bf-8fc3-9e83cc7e2f99", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bangalore", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "hybrid", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bangalore, Karnataka, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "Python, TensorFlow, PyTorch, Scikit-learn, SQL, AWS, Azure, GCP, AI, ML, Deep Learning, SCADA, DCS, IoT", "professionalSkills" : [ "Computational modeling", "First-principles modeling", "Signal processing", "Feature engineering", "Model interpretability", "Model scalability", "Model accuracy", "Problem-solving", "Decision-making" ], "hardSkillsList" : [ "Predictive maintenance", "Process optimization", "Industrial performance intelligence", "Time-series analysis", "Sensor data analysis", "Telemetry data analysis", "Transient state detection", "Steady-state identification", "Inference pipelines", "Hybrid modeling", "Mass balances", "Energy balances", "Kinetics" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Predictive maintenance", "level" : "intermediate" }, { "name" : "Process optimization", "level" : "intermediate" }, { "name" : "Industrial performance intelligence", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "Sensor data analysis", "level" : "intermediate" }, { "name" : "Telemetry data analysis", "level" : "intermediate" }, { "name" : "Transient state detection", "level" : "intermediate" }, { "name" : "Steady-state identification", "level" : "intermediate" }, { "name" : "Inference pipelines", "level" : "intermediate" }, { "name" : "Hybrid modeling", "level" : "intermediate" }, { "name" : "Mass balances", "level" : "intermediate" }, { "name" : "Energy balances", "level" : "intermediate" }, { "name" : "Kinetics", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "AI, ML, Data Science, Industrial AI", "majorSkillsList" : [ "AI", "ML", "Data Science", "Industrial AI" ], "coreResponsibilities" : "Build production-grade AI systems, Deploy production-grade AI systems, Design agentic workflows, Reason in dynamic environments, Adapt in dynamic environments, Take actions in dynamic environments, Derive meaningful insights from industrial data, Collaborate with domain experts, Create context-aware AI solutions, Solve ambiguous problems, Develop advanced AI/ML models, Deploy advanced AI/ML models, Handle complex sensor data, Handle high-dimensional data, Handle time-series sensor data, Drive model interpretability, Drive model scalability, Drive model accuracy, Ensure robust performance, Integrate First-Principles Models with ML, Ensure physical consistency, Engineer features on telemetry data, Detect transient states, Identify steady states, Deploy inference pipelines, Respect edge-computing constraints, Validate models with industry experts, Derive insights with customers, Deliver measurable business outcomes, Incorporate innovative techniques, Contribute to thought leadership, Publish whitepapers, Obtain patents, Present at industry conferences, Mentor data scientists, Provide technical leadership", "teamCollaboration" : "Product teams; Engineering teams; Customer Success teams; Domain experts; Industry experts; Customers", "domainKnowledge" : "Industrial data; Thermodynamics; Fluid dynamics; Mechanical stress; Manufacturing; Energy sector; Oil & Gas; Power sectors; Industrial systems; IoT systems; SCADA systems; DCS systems; Industrial AI", "domainList" : [ "industrial-data", "thermodynamics", "fluid-dynamics", "mechanical-stress", "manufacturing", "energy-sector", "oil-gas", "power-sectors", "industrial-systems", "iot-systems", "scada-systems", "dcs-systems", "industrial-ai" ], "domainSpecificKnowledge" : [ "Industrial data", "Thermodynamics", "Fluid dynamics", "Mechanical stress", "Manufacturing", "Energy sector", "Oil & Gas", "Power sectors", "Industrial systems", "IoT systems", "SCADA systems", "DCS systems", "Industrial AI" ], "toolProficiency" : [ "TensorFlow", "PyTorch", "Scikit-learn", "AWS", "Azure", "GCP" ], "communicationSkills" : "Influence senior stakeholders", "continuousLearning" : "Continuous learning; Professional growth", "innovationCreativity" : "Innovative thinking; Creative thinking", "problemSolvingSkills" : "First-principles problem solving; Problem-solving; Decision-making", "outcomesObjectives" : "Improve operational efficiency; Improve reliability; Deliver actionable insights; Ensure maximum efficiency; Ensure reliability", "qualificationsBasic" : "5+ years of hands-on experience developing and deploying ML models, Hands-on experience with Python, Hands-on experience with TensorFlow/PyTorch, Hands-on experience with Scikit-learn, Hands-on experience with SQL, Hands-on experience with cloud ML platforms, Bachelor’s or higher in Chemical Engineering, Mechanical Engineering, Aerospace, or Applied Physics, Significant experience in heavy industry (for CS degrees), Background in handling time-series and sensor data", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "About UptimeAI: UptimeAI is leading the way in predictive analytics and AI-driven solutions to optimize operational uptime and reduce downtime for industrial and enterprise clients. Our innovative platform harnesses cutting-edge data science to deliver actionable insights, ensuring maximum efficiency and reliability. UptimeAI uniquely combines Artificial Intelligence with Subject Matter Knowledge from 200+ years of cumulative experience to explain interrelations across upstream/downstream equipment, adapt to changes, identify problems, and give prescriptive diagnosis like a human expert would. Recently receiving a funding round led by WestBridge Capital, UptimeAI is prime for global expansion Role : Lead / Principal Data Scientist Location: Bangalore- Karnataka (Hybrid) Experience: 5+ years Department: Data Science ROLE OVERVIEW We are looking for individuals who sit at the intersection of Data Science and Physical Sciences. You understand that industrial data isn't just rows in a database—it represents thermodynamics, fluid dynamics, and mechanical stress. The candidate should be capable of translating business problems into scalable AI solutions, leveraging creative thinking and first-principles problem solving. This role requires someone who can: · Build and deploy production-grade AI systems, not just prototypes · Design agentic workflows that can reason, adapt, and take actions in dynamic environments · Work with noisy, incomplete, and real-time industrial data to derive meaningful insights · Collaborate closely with domain experts (e.g., operations, reliability, or plant engineers) to create context-aware AI solutions · Demonstrate innovative thinking in solving ambiguous problems where standard approaches may not apply KEY RESPONSIBILITIES · Be a part of the design, development, and deployment of advanced AI/ML models for predictive maintenance, process optimization, and industrial performance intelligence · Collaborate closely with Product, Engineering, and Customer Success teams to translate business problems from industrial domains into data science solutions. · Guide the team in handling complex, high-dimensional, and time-series sensor data from IoT, SCADA, and DCS systems. · Drive model interpretability, scalability, and accuracy, ensuring robust performance in real-world production environments. · Hybrid Modeling: Integrate First-Principles Models (mass/energy balances, kinetics) with data-driven ML to ensure physical consistency in model outputs. · Signal Processing: Lead the strategy for feature engineering on high-frequency telemetry data from SCADA/DCS, focusing on transient state detection and steady-state identification. · Operationalization: Move beyond \"notebook AI\" to deploy robust, low-latency inference pipelines that respect the edge-computing constraints of industrial environments. · Partner with industry experts and customers to validate models, derive insights, and deliver measurable business outcomes. · Stay ahead of emerging trends in AI/ML, deep learning, and industrial AI to incorporate innovative techniques into UptimeAi’s product roadmap. · Contribute to thought leadership by publishing whitepapers, patents, or presenting at industry conferences · Mentor and provide technical leadership to data scientists, ensuring continuous upskilling and adoption of best practices QUALIFICATIONS · Bachelor’s or higher in Chemical Engineering, Mechanical Engineering, Aerospace, or Applied Physics with a heavy emphasis on computational modeling. (Candidates with CS degrees are welcome if they have significant experience in heavy industry). · 5+ years of hands-on experience developing and deploying ML models specifically within Manufacturing, Energy, Oil & Gas, or Power sectors. · Strong background in handling time-series and sensor data from industrial or IoT systems. · Hands-on experience with Python, TensorFlow/PyTorch, Scikit-learn, SQL, and cloud ML platforms (AWS, Azure, GCP). · Excellent problem-solving and communication skills with the ability to influence senior stakeholders. · Demonstrated ability to lead and mentor teams while being a hands-on contributor · Ability to work independently, with strong problem-solving and decision-making abilities Why to join UptimeAI: · Impact Industry-Wide Change: Contribute to transformative solutions that significantly improve operational efficiency and reliability for global clients. · Collaborative and Growth-Oriented Environment: Join a talented, passionate team that values innovation, continuous learning, and professional growth. · Opportunities for Leadership and Innovation: Lead pioneering projects, influence product development, and shape the future of industrial AI solutions.", "summaryDescription" : "Lead / Principal Data Scientist at UptimeAI. Skills: AI, ML, Data Science, Industrial AI. Build production-grade AI systems. Deploy production-grade AI systems", "createdAt" : "2026-06-14T19:29:55.730", "lastUpdated" : "2026-06-16T03:31:32.901", "ingestTimestamp" : "2026-06-14T19:29:55.730", "mongoId" : "6a2c8d5d74d8ee00a0978bc6", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Predictive maintenance", "Process optimization", "Industrial performance intelligence", "Time-series analysis", "Sensor data analysis", "Telemetry data analysis", "Transient state detection", "Steady-state identification", "Inference pipelines", "Hybrid modeling", "Mass balances", "Energy balances", "Kinetics", "Leadership", "Mentoring", "AI", "ML", "Data Science", "Industrial AI", "Computational modeling", "First-principles modeling", "Signal processing", "Feature engineering", "Model interpretability", "Model scalability", "Model accuracy", "Problem-solving", "Decision-making", "Industrial data", "Thermodynamics", "Fluid dynamics", "Mechanical stress", "Manufacturing", "Energy sector", "Oil & Gas", "Power sectors", "Industrial systems", "IoT systems", "SCADA systems", "DCS systems", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "TensorFlow", "PyTorch", "Scikit-learn", "AWS", "Azure", "GCP" ], "skillCount" : 50, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "_score" : 890.6417, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Manufacturing", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2cb20e74d8ee00a09df743", "title" : "Principal Data Scientist", "industry" : "IT", "salary" : { "min" : 114400.0, "max" : 164400.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Canada", "locations" : [ "Canada" ], "timestamp" : "2026-06-15T23:59:49.999", "fingerprint" : "c1abb3bd5079505a712b6a8a9ba6ee79aadf1825b01d4e58f2b581b0b3e90bf3", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/9eb674a7-f4dd-40c7-9770-fbdc02ecaf60/apply", "externalId" : "9eb674a7-f4dd-40c7-9770-fbdc02ecaf60", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 10, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "Python, Spark, Hadoop, Large language models, Transformer architectures, Generative AI", "professionalSkills" : [ "Technical strategy", "Model development", "Production solutions", "Technical leadership", "Prompt engineering" ], "hardSkillsList" : [ "Machine learning techniques", "Deep learning", "Gradient boosting", "Ensemble methods", "LLM behavior", "Applied generative AI" ], "softSkillsList" : [ "Leadership", "Mentoring", "Problem-solving" ], "hardSkills" : [ { "name" : "Machine learning techniques", "level" : "intermediate" }, { "name" : "Deep learning", "level" : "intermediate" }, { "name" : "Gradient boosting", "level" : "intermediate" }, { "name" : "Ensemble methods", "level" : "intermediate" }, { "name" : "LLM behavior", "level" : "intermediate" }, { "name" : "Applied generative AI", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" }, { "name" : "Problem-solving" } ], "majorSkills" : "AI, Machine learning, Data science, Generative AI", "majorSkillsList" : [ "AI", "Machine learning", "Data science", "Generative AI" ], "coreResponsibilities" : "Lead development and deployment of AI/ML models, Define technical strategy, Define model development standards, Define best practices, Collaborate with engineering and product teams, Design scalable AI solutions, Build scalable AI solutions, Operationalize scalable AI solutions, Analyze large-scale datasets, Identify patterns, Identify trends, Identify opportunities for model improvement, Provide technical leadership, Provide mentorship to data scientists, Ensure high-quality outputs, Establish methodologies for AI/ML development, Establish frameworks for AI/ML development, Establish governance standards for AI/ML development, Partner with stakeholders, Align data science initiatives with business goals, Align data science initiatives with customer needs, Communicate insights, Communicate technical findings, Communicate recommendations, Lead small to mid-sized teams, Provide direction to teams, Provide structure to teams, Provide execution oversight across projects, Continuously evaluate AI technologies, Continuously evaluate ML technologies", "teamCollaboration" : "Collaborate with engineering teams; Collaborate with product teams; Partner with stakeholders; Cross-functional teams", "projectManagementSkills" : [ "Execution oversight" ], "domainKnowledge" : "Large language models; Transformer architectures; Generative AI techniques", "domainList" : [ "large-language-models", "transformer-architectures", "generative-ai-techniques" ], "domainSpecificKnowledge" : [ "Large language models", "Transformer architectures", "Generative AI techniques" ], "communicationSkills" : "Communicate insights; Communicate technical findings; Communicate recommendations", "continuousLearning" : "Evaluate emerging AI technologies; Evaluate emerging ML technologies", "innovationCreativity" : "Model improvement; Innovation", "problemSolvingSkills" : "Problem-solving mindset; Navigate ambiguity; Drive technical decisions", "qualificationsBasic" : "10+ years of experience in data science, AI, or machine learning, Proven experience leading complex AI/ML projects, Experience working with large-scale datasets, Programming skills in Python", "qualificationsPreferred" : "Advanced degree (Master’s or PhD) in Computer Science, Mathematics, Statistics, or a related field", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "## Accountabilities Lead the development and deployment of advanced AI and machine learning models to solve complex business and product challenges. Define technical strategy, model development standards, and best practices across data science teams. Collaborate with engineering and product teams to design, build, and operationalize scalable AI solutions. Analyze large-scale datasets to identify meaningful patterns, trends, and opportunities for model improvement. Provide technical leadership and mentorship to junior and mid-level data scientists, ensuring high-quality outputs. Establish methodologies, frameworks, and governance standards for AI/ML development and deployment. Partner with stakeholders to align data science initiatives with business goals and customer needs. Communicate insights, technical findings, and recommendations clearly to both technical and non-technical audiences. Lead small to mid-sized teams, providing direction, structure, and execution oversight across projects. Continuously evaluate emerging AI and ML technologies to improve model performance and innovation. Requirements: 10+ years of experience in data science, AI, or machine learning roles with significant senior-level responsibility. Proven experience leading complex AI/ML projects and delivering production-grade solutions. Strong background in mentoring, coaching, and guiding technical teams in a leadership capacity. Deep expertise in machine learning techniques such as deep learning, gradient boosting, and ensemble methods. Strong experience with large language models and transformer architectures (e.g., BERT, T5, GPT-based systems). Solid understanding of prompt engineering, LLM behavior, and applied generative AI techniques. Experience working with large-scale datasets and distributed computing frameworks (e.g., Spark, Hadoop). Strong programming skills in Python and familiarity with modern ML frameworks. Excellent communication skills with the ability to influence senior stakeholders and cross-functional teams. Strong problem-solving mindset with the ability to navigate ambiguity and drive technical decisions. Advanced degree (Master’s or PhD) in Computer Science, Mathematics, Statistics, or a related field is highly preferred. Benefits: Competitive base salary range of $114,400 – $164,400 CAD, plus eligibility for annual bonus incentives. Comprehensive health, dental, and vision coverage through a multi-carrier plan. Retirement savings plans, including employer contributions and stock purchase options. Disability, life, and accident insurance coverage. Flexible and remote work arrangements supporting work-life balance. Family-focused benefits, including adoption and surrogacy support. Dependent care and commuter spending accounts. Inclusive and diverse workplace culture with strong commitment to equity and accessibility. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "Principal Data Scientist. Skills: AI, Machine learning, Data science, Generative AI. Lead development and deployment of AI/ML models. Define technical strategy", "postedDate" : "2026-06-12T07:02:23.299", "createdAt" : "2026-06-12T07:02:23.299", "lastUpdated" : "2026-06-15T23:59:49.999", "ingestTimestamp" : "2026-06-14T22:14:25.653", "mongoId" : "6a2cb20e74d8ee00a09df743", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Machine learning techniques", "Deep learning", "Gradient boosting", "Ensemble methods", "LLM behavior", "Applied generative AI", "Leadership", "Mentoring", "Problem-solving", "AI", "Machine learning", "Data science", "Generative AI", "Technical strategy", "Model development", "Production solutions", "Technical leadership", "Prompt engineering", "Execution oversight", "Large language models", "Transformer architectures", "Generative AI techniques" ], "skillCount" : 22, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "_score" : 887.58215, "daysOld" : 3, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ca0ce74d8ee00a09a3594", "title" : "Staff / Principal Data Scientist", "company" : "Auror", "industry" : "Product", "salary" : { "min" : 157500.0, "max" : 225000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "Remote - United States", "locations" : [ "Remote - United States" ], "timestamp" : "2026-06-15T06:21:48.680", "fingerprint" : "a3f3537d052566d251b3b04110945d1b0aab290d9a84544eed0a6d64c19e6bf0", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/auror/0f19a00b-ff17-400f-9d1e-79132dbf164b/application", "externalId" : "0f19a00b-ff17-400f-9d1e-79132dbf164b", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, SQL", "professionalSkills" : [ "Statistical analysis", "Causal inference", "Experimental design", "Model calibration", "Measurement", "Risk classification", "Shrink prediction", "Loss Prevention", "Fraud detection", "Asset Protection", "POS Analytics", "ETL Pipeline Design", "Data Modeling", "Data Architecture", "Responsible AI", "Geospatial risk modeling", "Network analytics", "Graph analytics", "Exception Based Reporting" ], "hardSkillsList" : [ "Statistical modeling", "Time series analysis", "Model calibration", "Causal inference", "Experimental thinking", "Risk classification", "Shrink prediction", "ETL pipeline design", "Data modeling", "Data architecture" ], "hardSkills" : [ { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Time series analysis", "level" : "intermediate" }, { "name" : "Model calibration", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" }, { "name" : "Experimental thinking", "level" : "intermediate" }, { "name" : "Risk classification", "level" : "intermediate" }, { "name" : "Shrink prediction", "level" : "intermediate" }, { "name" : "ETL pipeline design", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Data architecture", "level" : "intermediate" } ], "majorSkills" : "Predictive modeling, Statistical modeling, Loss Prevention, Fraud detection", "majorSkillsList" : [ "Predictive modeling", "Statistical modeling", "Loss Prevention", "Fraud detection" ], "coreResponsibilities" : "Own predictive modeling end-to-end, Own advanced analytics end-to-end, Frame ambiguous problems, Deploy predictive models, Focus on LP applications, Focus on AP applications, Design ETL pipelines, Build ETL pipelines, Standardize ETL pipelines, Support scalable predictive modeling, Build defensible metrics, Link metrics to decision outcomes, Partner with ML engineers, Productionize feature definitions, Productionize scoring workflows, Productionize monitoring signals, Productionize retraining triggers, Communicate model uncertainty, Communicate model value, Communicate strategic application, Design randomized controlled trials, Design evaluation harnesses", "teamCollaboration" : "Partner with ML engineers; Communicate to diverse audiences; Communicate to internal Product/Engineering; Communicate to external customers; Communicate to executive teams", "domainKnowledge" : "Retail Loss Prevention; Fraud detection; Asset Protection; POS Analytics; Responsible AI", "domainList" : [ "retail-loss-prevention", "fraud-detection", "asset-protection", "pos-analytics", "responsible-ai" ], "domainSpecificKnowledge" : [ "Retail Loss Prevention", "Fraud detection", "Asset Protection", "POS Analytics", "Responsible AI" ], "communicationSkills" : "Communicate clearly; Communicate concisely", "continuousLearning" : "Personal growth support; Courses; Conferences; Events", "innovationCreativity" : "Embracing AI potential; Curious about AI", "problemSolvingSkills" : "Ambiguous problem framing; Statistical modeling; Advanced analytics", "qualificationsBasic" : "Expertise in statistical modeling, Experience taking models from problem to shipped decision support, Domain expertise in Retail Loss Prevention, SQL + Python experience, Experience in ETL Pipeline Design, Experience in Data Modeling & Architecture, Practical approach to responsible AI", "qualificationsPreferred" : "Experience with geospatial risk modeling, Experience with network/graph analytics, Experience with Exception Based Reporting tools, Experience building customer-facing proofs-of-concept, Translating complex analytics into product features", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "ABOUT AUROR At Auror, we’re empowering the retail industry to tackle theft and Organised Retail Crime, a $150 Billion problem globally. It’s high volume crime that’s increasingly organised in nature and is putting people, retailers, and communities at risk every day. Founded in New Zealand 12 years ago, we’re working with some of the best and largest retailers in the world across the US, Canada, Australia, New Zealand, and the UK. Auror is connecting people and intelligence to reduce crime. We’re using technology for good. Our mission is clear: reduce violent retail crime by 50% in 5 years. It's an ambitious goal - and one we believe is achievable. In partnership with our leading retail partners, we need people with the passion, determination, and innovation required to overcome one of the world's largest problems. If you’re looking to make a difference with and for the people dedicated to stopping crime, for good, then we want you on our team. We're also embracing the potential of AI to supercharge our impact - whether that's enhancing the way we detect trends, support our customers, or improve internal workflows. As a company, we're committed to responsibly incorporating AI into how we work and what we build, and we encourage all Aurors to be curious about how AI can elevate their work, regardless of role or function. THE ROLE Auror’s North American footprint is live and expanding. We need a highly practical and rigorous Data Scientist to build, productionize, and defend predictive models that customers can trust, especially for high-stakes operational decisions in Loss Prevention and Fraud detection (e.g., cashier risk scoring, deployment optimization, shrink prediction). This role fills a current need for deep statistical modeling expertise combined with real-world domain knowledge and the ability to ship robust analytics products. RESPONSIBILITIES - Own predictive modeling and advanced analytics end-to-end, from ambiguous problem framing to deployment, focusing on Loss Prevention (LP) and Asset Protection (AP) applications. - Design, build, and standardize ETL pipelines and data architecture necessary to support robust, scalable predictive modeling at scale. - Build defensible metrics (calibration, error tradeoffs, bias/disparity checks) and link them to measurable decision outcomes for C-suite and AP teams. - Partner with ML engineers to productionize: feature definitions, scoring workflows, monitoring signals, and retraining triggers. - Communicate clearly and concisely to diverse audiences (internal Product/Engineering, external customers, and executive teams) on model uncertainty, value, and strategic application. - Design randomized controlled trials and evaluation harnesses that make model quality legible to stakeholders and customers. REQUIREMENTS - Expertise in practical statistical modeling and analysis (inference, causal/experimental thinking, time series, model calibration, measurement) applied to real-world, messy data. - Demonstrated experience taking analyses/models from ambiguous problem → shipped decision support (e.g., shortage prediction, risk classification models). - Strong domain expertise in Retail Loss Prevention, Fraud detection, Asset Protection, or POS Analytics. - Strong SQL + Python, with demonstrated experience in ETL Pipeline Design and Data Modeling & Architecture. - Practical, high-integrity approach to responsible AI (limits, misuse risk, bias considerations, auditability). ⁠ NICE TO HAVES - Experience with geospatial risk modeling, network/graph analytics, or Exception Based Reporting (EBR) tools. - Experience building customer-facing proofs-of-concept and translating complex analytics into product features. - We are looking for people who demonstrate a strong alignment to our Guiding Principles (you can find these on our Careers page https://www.auror.co/company-careers). With diversity and inclusion at the forefront of Auror’s guiding principles, we promote a culture that celebrates diversity and inclusiveness at Auror, regardless of, but not limited to, race, gender, sexual orientation, family status, religion, ethnicity, national origin, physical disability, veteran status, or age. BENEFITS: - Competitive salary range: Depending on level of experience, between $[Salary band]. - Employee share scheme: You’ll own part of a company making a real difference! - Flexibility: We are hard-working and outcome focused, but recognise there is more to life than work. We promote a healthy work/life blend. - Shorter work weeks (at full pay): Everyone gets Friday afternoons off, so you can start your weekend early, and do more of whatever it is that makes you happy. - Focus on mental and physical health: We understand how vital our health is and have policies to support your wellness, including Wellness Days, and up to $500 for expert sessions every year. - Health care plan (Medical, Dental & Vision): Auror covers 100% of the cost of your individual health insurance plan with Anthem & Metlife. - Family-friendly: We offer comprehensive paid parental leave - 12 weeks for birth parents and 6 weeks for non-birth parents following birth, adoption, or surrogacy, available to all Aurors from day one. - Personal growth: We support our team to participate in courses, conferences, or events that will help them develop their skills. - Team love: We have regular team lunches and social events where most (if not all) activities are during work hours. What are the next steps? If you’re excited about our mission and you have the experience and a passion for this role, please hit “Apply”. If you’re not sure that you tick all the boxes but feel you’re close to what we’re looking for, please apply anyway! We’re proud that Auror is a place where everyone can learn and grow so we’d love to hear from you. You'll be asked to submit a cover letter as part of your application. While this is optional we do encourage it, as we find cover letters can tell a story that resumes alone often cannot. Our hiring team love to understand what attracted you to this role and why you are excited about the opportunity to join Auror. Once you apply, you’ll hear from us to acknowledge your application. If you have questions about any of the above, or if you have any accessibility requirements, we’ll be able to help you from there.", "summaryDescription" : "Staff / Principal Data Scientist at Auror. Skills: Predictive modeling, Statistical modeling, Loss Prevention, Fraud detection. Own predictive modeling end-to-end. Own advanced analytics end-to-end", "createdAt" : "2026-06-13T21:49:22.636", "lastUpdated" : "2026-06-15T06:21:48.680", "ingestTimestamp" : "2026-06-13T21:49:22.636", "mongoId" : "6a2ca0ce74d8ee00a09a3594", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 157500, "salaryAnnualMax" : 225000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistical modeling", "Time series analysis", "Model calibration", "Causal inference", "Experimental thinking", "Risk classification", "Shrink prediction", "ETL pipeline design", "Data modeling", "Data architecture", "Predictive modeling", "Loss Prevention", "Fraud detection", "Statistical analysis", "Experimental design", "Measurement", "Asset Protection", "POS Analytics", "ETL Pipeline Design", "Data Modeling", "Data Architecture", "Responsible AI", "Geospatial risk modeling", "Network analytics", "Graph analytics", "Exception Based Reporting", "Retail Loss Prevention" ], "skillCount" : 27, 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: "Thermal stability", "level" : "intermediate" }, { "name" : "Polyspecificity assays", "level" : "intermediate" }, { "name" : "Phage display", "level" : "intermediate" }, { "name" : "Yeast display", "level" : "intermediate" }, { "name" : "Directed evolution", "level" : "intermediate" }, { "name" : "Protein expression", "level" : "intermediate" }, { "name" : "Protein purification", "level" : "intermediate" }, { "name" : "Molecular biology techniques", "level" : "intermediate" }, { "name" : "ML model interpretation", "level" : "intermediate" }, { "name" : "Sequence design", "level" : "intermediate" }, { "name" : "Structure design", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Antibody Engineering, AI/ML Antibody Optimization, Protein Science, Developability Optimization", "majorSkillsList" : [ "Antibody Engineering", "AI/ML Antibody Optimization", "Protein Science", "Developability Optimization" ], "coreResponsibilities" : "Execute antibody optimization, Perform liability engineering, Identify deamidation hotspots, Identify oxidation hotspots, Identify isomerization hotspots, Identify aggregation hotspots, Lead affinity maturation campaigns, Execute antibody humanization strategies, Drive developability optimization, Address viscosity liabilities, Address solubility liabilities, Address thermal stability liabilities, Address polyspecificity liabilities, Serve as internal champion for AI-driven antibody optimization, Integrate computational design into engineering workflows, Coordinate with AI/ML CROs, Design computational optimization campaigns, Execute computational optimization campaigns, Define project scopes, Define deliverables, Define success criteria, Evaluate external AI/ML platforms, Select external AI/ML platforms, Translate computational sequence proposals, Design wet-lab validation experiments, Represent antibody engineering expertise, Provide scientific guidance, Shape program strategy, Accelerate candidate progression, Partner with discovery teams, Partner with structural biology teams, Partner with CMC teams, Partner with clinical teams, Align engineering strategies, Drive developability risk assessments, Contribute to IND-enabling activities, Champion new technologies, Foster scientific curiosity, Foster continuous improvement, Identify emerging technologies, Evaluate emerging technologies, Mentor junior scientists", "teamCollaboration" : "Multidisciplinary project teams; Cross-functional teams; External AI/ML CROs; Technology vendors; Discovery teams; Structural biology teams; CMC teams; Clinical teams", "domainKnowledge" : "Antibody Engineering; Protein Science; Biologics Research; Therapeutic Antibody Engineering; Computational Design; Structure-based Generative AI; Antibody Optimization Cycle; Protein Engineering; Immunology; Biophysics; Computational Biology; Deamidation; Oxidation; Isomerization; Aggregation; Affinity Maturation; Humanization; CDR Grafting; Framework Selection; Back-mutation Analysis; Developability Optimization; Viscosity; Solubility; Thermal Stability; Polyspecificity; Phage Display; Yeast Display; Directed Evolution; Biophysical Profiling; AI/ML CROs; IND-enabling activities", "domainList" : [ "antibody-engineering", "protein-science", "biologics-research", "therapeutic-antibody-engineering", "computational-design", "structure-based-generative-ai", "antibody-optimization-cycle", "protein-engineering", "immunology", "biophysics", "computational-biology", "deamidation", "oxidation", "isomerization", "aggregation", "affinity-maturation", "humanization", "cdr-grafting", "framework-selection", "back-mutation-analysis", "developability-optimization", "viscosity", "solubility", "thermal-stability", "polyspecificity", "phage-display", "yeast-display", "directed-evolution", "biophysical-profiling", "ai-ml-cros", "ind-enabling-activities" ], "domainSpecificKnowledge" : [ "Antibody Engineering", "Protein Science", "Biologics Research", "Therapeutic Antibody Engineering", "Computational Design", "Structure-based Generative AI", "Antibody Optimization Cycle", "Protein Engineering", "Immunology", "Biophysics", "Computational Biology", "Deamidation", "Oxidation", "Isomerization", "Aggregation", "Affinity Maturation", "Humanization", "CDR Grafting", "Framework Selection", "Back-mutation Analysis", "Developability Optimization", "Viscosity", "Solubility", "Thermal Stability", "Polyspecificity", "Phage Display", "Yeast Display", "Directed Evolution", "Biophysical Profiling", "AI/ML CROs", "IND-enabling activities" ], "toolProficiency" : [ "ProteinMPNN", "RFdiffusion", "ESMFold", "AlphaFold2/3", "Rosetta/PyRosetta", "AbMPNN" ], "communicationSkills" : "Translate scientific data; Clear insights; Actionable insights", "continuousLearning" : "Identify emerging technologies; Evaluate emerging technologies", "innovationCreativity" : "Platform innovation; Champion new technologies; Scientific curiosity; Continuous improvement; Emerging technologies", "problemSolvingSkills" : "Troubleshooting; Root cause analysis", "outcomesObjectives" : "Advance antibody engineering capabilities; Deliver next generation therapeutic molecules", "qualificationsBasic" : "5+ years antibody engineering experience, Ph.D. in Biochemistry, Protein Engineering, Immunology, Biophysics, Computational Biology, or related discipline, Hands-on experience in liability engineering, Demonstrated expertise in antibody humanization, Direct experience in biophysical characterization, Familiarity with antibody expression systems, Hands-on experience using ProteinMPNN, RFdiffusion, ESMFold, AlphaFold2/3, Rosetta/PyRosetta, AbMPNN, or similar, Practical experience applying ML models for antibody property prediction, Ability to independently run computational workflows, Working knowledge of Python or equivalent scripting", "qualificationsPreferred" : "Demonstrated track record of successfully advancing antibody candidates, Demonstrated expertise in antibody humanization experimental validation, Familiarity with generative AI approaches, Experience with fine-tuning or adapting pre-trained models, Mandarin proficiency is an advantage", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "**Job Title: Principal Scientist I, Antibody Engineering** Location: Suzhou, China **Position Summary** We are seeking an exceptional Principal Scientist, Antibody Engineering to join our Biologics Research team in Suzhou. This is a hands-on bench scientist role for a deep technical expert who thrives at the interface of classical antibody engineering and cutting-edge computational approaches. You will lead and execute the engineering of therapeutic antibody candidates — from liability removal and humanization through affinity maturation and developability optimization — while actively applying AI/ML-based tools to accelerate and enhance every stage of the antibody optimization cycle. This position is not primarily managerial. We are looking for a scientist who is equally comfortable overseeing protein science, interpreting developability findings, and deploying a structure-based generative AI model to design next-generation antibody variants. You will be a cornerstone of our antibody engineering capability, driving scientific excellence and platform innovation in a collaborative, fast-paced R&D environment. \\--- **Key Responsibilities** **1\\. Hands-On Antibody Engineering & Optimization** Execute the full spectrum of antibody optimization with direct bench involvement, from early liability identification through final candidate selection. Perform liability engineering to identify and resolve deamidation, oxidation, isomerization, and aggregation hotspots Lead affinity maturation campaigns using phage display, yeast display, or other directed evolution platforms Execute antibody humanization strategies including CDR grafting, framework selection, and back-mutation analysis Drive developability optimization through biophysical profiling — addressing viscosity, solubility, thermal stability, and polyspecificity liabilities **2\\. AI-Aided Protein Optimization & External Partner Collaboration** Serve as the internal champion for AI-driven antibody optimization, working closely with external AI/ML CROs and technology vendors to integrate computational design into engineering workflows. Coordinate with AI/ML CROs to design and execute computational optimization campaigns, defining project scopes, deliverables, and success criteria Evaluate and select appropriate external AI/ML platforms for specific engineering challenges Translate computational sequence proposals into structured wet-lab validation experiments, closing the loop between in silico design and in vitro outcomes **3\\. Cross-Functional Leadership & Program Delivery** Represent antibody engineering expertise within multidisciplinary project teams, providing scientific guidance that shapes program strategy and accelerates candidate progression. Partner with discovery, structural biology, CMC, and clinical teams to align engineering strategies with broader program objectives Drive developability risk assessments at key decision points and contribute to IND-enabling activities **4\\. Innovation & Mentorship** Champion new technologies and foster a culture of scientific curiosity and continuous improvement. Identify and evaluate emerging technologies in antibody engineering and computational design Mentor junior scientists through technical guidance, hands-on coaching, and career development support \\--- **Qualifications** **Educational Background & Experience** \\- Ph.D. in Biochemistry, Protein Engineering, Immunology, Biophysics, Computational Biology, or a closely related discipline is strongly preferred. \\- 5+ years of hands-on experience in antibody engineering within an industrial or advanced academic research setting. \\- Demonstrated track record of successfully advancing antibody candidates through engineering optimization cycles, with evidence of impact (publications, patents, program milestones). **Technical Expertise — Wet Lab (Hands-On)** \\- Proven hands-on experience in liability engineering: identification, prioritization, and experimental validation of deamidation, oxidation, aggregation, and isomerization hotspot removal. \\- Demonstrated expertise in antibody humanization: CDR grafting, framework selection, back-mutation analysis, and experimental validation of humanized variants is a plus. \\- Strong direct experience in biophysical characterization and developability profiling: DSF/nanoDSF, DLS, SEC, AC-SINS, HIC, viscosity measurement, and solubility/stability assays. \\- Familiarity with antibody expression systems (mammalian transient expression, yeast surface display), purification (Protein A/G, SEC), and standard molecular biology techniques. **AI/ML Competency — *Mandatory, Not Optional*** \\- Hands-on experience using one or more of the following (or equivalent tools): ProteinMPNN, RFdiffusion, ESMFold, AlphaFold2/3, Rosetta/PyRosetta, AbMPNN, or similar structure-based design platforms. \\- Practical experience applying ML models for antibody property prediction (e.g., aggregation, stability, affinity, immunogenicity scoring). \\- Ability to independently run computational workflows, interpret model outputs, and translate predictions into experimental hypotheses. \\- Familiarity with generative AI approaches for sequence and structure design; experience with fine-tuning or adapting pre-trained models on antibody-specific datasets is highly desirable. \\- Working knowledge of Python or equivalent scripting for data analysis and interfacing with computational tools is a strong advantage. **Collaboration & Communication Skills** \\- Strong ability to work effectively in cross-functional, matrixed environments. \\- Excellent written and verbal communication skills in English; Mandarin proficiency is an advantage in the Suzhou context. \\- Demonstrated ability to translate complex scientific data into clear, actionable insights for diverse audiences. \\--- We look forward to welcoming a Principal Scientist who will bring both deep bench expertise and computational boldness to advance our antibody engineering capabilities and deliver the next generation of therapeutic molecules for patients. # Pursue _progress_ , discover _extraordinary_ Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people. At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, ability or gender identity. Watch our [ALL IN video](https://www.youtube.com/watch?v=SkpDBZ-CJKw&t=67s) and check out our Diversity Equity and Inclusion actions at [sanofi.com](https://www.sanofi.com/en/our-responsibility/equality-and-inclusiveness)!", "summaryDescription" : "Principal Scientist I, Antibody Engineering at Sanofi. Skills: Antibody Engineering, AI/ML Antibody Optimization, Protein Science, Developability Optimization. Execute antibody optimization. Perform liability engineering", "postedDate" : "2026-06-10T14:26:01.590", "createdAt" : "2026-06-11T14:26:01.569", "lastUpdated" : "2026-06-12T19:01:15.306", "ingestTimestamp" : "2026-06-11T14:26:01.569", "mongoId" : "6a2a60b674d8ee00a062058d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://sanofi.wd3.myworkdayjobs.com/SanofiCareers/job/Suzhou-Jiangsu/R-D---Intrepide---Principal-Scientist-I--Antibody-Engineering---SZ_R2859778-1", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Liability identification", "Affinity maturation", "CDR grafting", "Framework selection", "Back-mutation analysis", "Biophysical profiling", "Viscosity measurement", "Solubility assays", "Thermal stability", "Polyspecificity assays", "Phage display", "Yeast display", "Directed evolution", "Protein expression", "Protein purification", "Molecular biology techniques", "ML model interpretation", "Sequence design", "Structure design", "Leadership", "Mentoring", 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} ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Engineering leadership, Business development, Project delivery", "majorSkillsList" : [ "Engineering leadership", "Business development", "Project delivery" ], "coreResponsibilities" : "Influence culture, morale, recruiting, Provide leadership, Identify opportunities, Take initiative, Establish relationships, Promote and represent BES, Develop scope, schedule, fee, Communicate pursuits, Address staffing needs, Address expertise requirements, Address business needs, Identify how to engage people, Align with strategic goals, Facilitate clear communication, Provide leadership for design team, Engage and challenge designers, Lead engineering teams, Deliver well-coordinated designs, Provide leadership for discipline, Act as leaders in practice, Maximize high performance design, Proactively look out for disciplines, Elevate design, Ensure scope, schedule, budget, Communicate concerns to management, Protect client relationships", "teamCollaboration" : "Cross discipline teams; Integrated practice; Design team; Project teams; Internal clients; External clients", "projectManagementSkills" : [ "Scope management", "Schedule management", "Budget management" ], "domainKnowledge" : "Building engineering; Data centers; Commercial environments; Built environment", "domainList" : [ "building-engineering", "data-centers", "commercial-environments", "built-environment" ], "domainSpecificKnowledge" : [ "Building engineering", "Data centers", "Commercial environments", "Built environment" ], "communicationSkills" : "Client communication; Internal communication; External communication", "continuousLearning" : "Tuition reimbursement", "innovationCreativity" : "Novel ideas; Innovation", "problemSolvingSkills" : "Complex design challenges", "outcomesObjectives" : "Win work for HDR; Help partner BGs win work; Capture building engineering scope; Deliver high-quality designs", "qualificationsBasic" : "Deep engineering expertise, Understand cross discipline teams, Business development skills, Develop scope, schedule, fee, Communicate pursuits with leadership, Understand building design process, Conceptual thinker, Engage and challenge designers, Lead engineering teams, Elevate design, Ensure scope, schedule, budget", "qualificationsPreferred" : "SME, Participate in strategy/visioning sessions", "remoteFriendly" : false, "rawDescription" : "At HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas to work every day. As we foster a culture of inclusion throughout our company and within our communities, we constantly ask ourselves: What is our impact on the world? Watch Our Story: ' https://www.hdrinc.com/our-story' Each and every role throughout our organization makes a difference in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world. We believe building engineering is more than systems and structures, it’s about powering progress and enabling innovation. As part of HDR’s Building Engineering Services Group, you’ll help design the critical infrastructure that supports the digital age and shapes the spaces where people work, connect, and thrive. From high-performance data centers driving the future of AI to dynamic commercial environments, your work will directly support technological advancement, sustainability, and human experience. We bring together mechanical, electrical, structural, and civil engineering experts to solve complex design challenges with precision, creativity, and collaboration. Whether you're optimizing energy efficiency, integrating resilient systems, or engineering the backbone of next-generation facilities, your contributions will help define the future of the built environment. This isn’t just a job, it’s a chance to lead innovation, engineer impact, and build a legacy of excellence. Engineering Principal Engineering Principals are leaders in the practice who influence culture, morale, and recruiting as well as provide leadership in the pursuit and delivery of work. An Engineering Principal not only has deep engineering expertise in their discipline, but they understand how cross discipline teams’ function. They couple that understanding with leadership and communication abilities to positively impact the success of the business. The behaviors represented by Engineering Principals are indicative to our staff, clients, and recruits of the behaviors and characteristics HDR rewards. Winning Work Engineering Principals have a significant impact on winning work for HDR – both for the Building Engineering Services (BES) Business Group (BG) and partner BGs. They have business development skills to identify opportunities and take the initiative to be responsive and establish relationships to win work. They promote and represent BES to our internal and external clients – they foster relationships that make people want to work with us. There are three ways in which BES wins work and Engineering Principals contribute to each: Book work in BES market sectors. Collaborate with partner business groups to help them win work in their market sectors by developing and leveraging our expertise, relationships, and reputation. Capture building engineering scope of work on HDR non-BES projects by selling our services internally. Engineering Principals are expected to help develop scope, schedule, and fee for projects. They must communicate regarding the pursuits they are leading with operational leadership to address staffing, expertise requirements, and business needs. Engineering Principals help us identify how to engage the right people in the right work in alignment with our strategic goals: “differentiating ourselves in our markets by amplifying our collective talent and knowledge”. Project Success Engineering Principals understand the building design process in the market sectors in which they practice. They facilitate clear communication and provide leadership for the entire design team. An Engineering Principal needs to be a conceptual thinker who can engage and challenge our architectural designers and engineering team during the early stages of projects to inform design. They should leverage our integrated practice to add value to our project delivery process and lead engineering teams to deliver well-coordinated, high-quality designs to our clients. Engineering Principals are expected to not only provide leadership for their discipline but act more broadly as leaders in our practice. The role requires a passion for maximizing high performance design within the project constraints. They are the team members who proactively look out for all BES disciplines on project teams to elevate design while ensuring that scope, schedule, and budget are understood and respected by the team and concerns are communicated to project management in a clear and timely manner. Engineering Principals are protecting HDR’s Client relationships (internal and external) and project successes. Their leadership has a direct impact on HDR’s financial plan. Culture, Morale & Recruiting Engineering Principals are leaders in the company that exemplify the company culture. They demonstrate expectations of how project teams' function and emphasize collaboration and design excellence. These individuals are responsible for mentoring and building the next generation of leadership at HDR by developing technical, client and business acumen in others. Principals recognize gaps in our expertise and project teams. They identify ways to fill those gaps by mentoring junior staff, identifying where we can shift or train staff, or identifying where we need to hire additional expertise. Principals network in the local community – leveraging their relationships to identify talent and recruit for HDR. Engineers in this role are contributing to BES’s strategy to develop expertise and strategy required to build a successful engineering practice. Engineer Principals represent HDR through their participation in the professional and local community. They are expected to represent HDR in the engineering community, participate in speaking engagements, author white papers and technical publications and participate on industry and community boards. Clarification from SME or Senior Engineer The role of Engineering Principal is a progression beyond Senior Engineer or Subject Matter Expert. But this is not a recognition that all Senior Engineers can expect to earn with time as the next step on the ladder. Competencies are not solely based upon technical skills. Subject Matter Expert/ Senior Engineer Exemplary technical performance and expertise. Hold the resume required to win work. In-depth market sector expertise. Interview performance to win work. Mentor to junior staff. Execute projects with little to no direction. Many Engineering Principals will also be SMEs. Framework Report or meet regularly with Area BG Management (Business Group Manager, Professional Services Leader, Project Delivery Leader, etc.) Participate in strategy/visioning sessions Values from HDR Strategic Plan: Engineering Principals are expected to guide teams to see the bigger picture beyond the immediate problem or project in front of them. Influence people to align with our company values: Live the network. We think global and act local, and as a result we learn from each other. We bring together the right people for each individual client and engagement, e nsuring the right skills, expertise, experience and the highest level of teamwork. Every time. Listen first. To find the best answer, we need to understand the root and complexity of the problem. We start by listening. Hold ourselves accountable. We are empowered to find the best solutions for our clients and for our own company. We do the right things for the right reasons. And we take personal responsibility to see things through. Push boundaries. We strive to do things better and stretch further. From our internal processes to the work we deliver, and from the projects we do, to the careers we enable. Design smart. We have the skills and ability to tailor our approach to each situation, whether it’s tried and tested, or something more cutting edge. We deliver our best work by designing smart. We provide a comprehensive benefits package that promotes employee ownership, employee health, performance, and success, which includes medical, dental, vision, short and long-term disability, life insurance, an employee assistance program, paid time away, parental leave, paid holidays, a retirement savings plan with employer match, employee referral bonus and tuition reimbursement. The expected compensation range for this position depends upon skills, experience, education and geographical location. (Stated benefits are for full-time regular positions. 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Example: Professional Engineer (PE or P.Eng) license. Extensive experience in project execution Proficient computer skills in Microsoft Office as well as standard design software. Must be comfortable being viewed as a technical expert in engineering analysis and design and have proven background of technical leadership on these types of projects An attitude and commitment to being an active participant of our employee-owned culture What We Believe HDR is our company. Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve. Our Commitment As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day. Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees. United States-Minnesota-Saint Louis Park", "summaryDescription" : "Engineering Principal. Perform engineering analysis. Perform engineering design", "createdAt" : "2026-06-14T04:57:07.760", "lastUpdated" : "2026-06-15T09:22:26.977", "ingestTimestamp" : "2026-06-14T04:57:07.760", "mongoId" : "6a16291b58b93c861e959dd5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 245000, "salaryAnnualMax" : 375000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Project execution", "Technical leadership", "Professional Engineer (PE or P. 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"Mentoring" ], "hardSkills" : [ { "name" : "Antibody design", "level" : "intermediate" }, { "name" : "Protein expression", "level" : "intermediate" }, { "name" : "Protein purification", "level" : "intermediate" }, { "name" : "Bispecific design", "level" : "intermediate" }, { "name" : "Protein engineering", "level" : "intermediate" }, { "name" : "Biophysical characterization", "level" : "intermediate" }, { "name" : "Protein-protein interactions", "level" : "intermediate" }, { "name" : "Analytical techniques", "level" : "intermediate" }, { "name" : "SPR", "level" : "intermediate" }, { "name" : "Mass spectrometry", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Bispecific Antibody Design, Protein Science, Molecular Engineering", "majorSkillsList" : [ "Bispecific Antibody Design", "Protein Science", "Molecular Engineering" ], "coreResponsibilities" : "Develop innovative strategies for design and engineering of, Implement innovative strategies for design and engineering of, Troubleshoot innovative strategies for design and engineering of, Design a portfolio of projects, Manage a portfolio of projects, Provide data-driven, structure-function insights, Improve expression, stability, and manufacturability, Oversee a team of research associates, Oversee a team of biotechnologists, Provide technical guidance to team, Foster a culture of excellence in protein science, Collaborate with cross-functional teams, Collaborate with cross-cultural teams, Support the development of biologics, Evaluate new technologies, Translate new technologies into production-ready solutions, Review advancements in antibody formats, Review advancements in engineering strategies, Review advancements in upstream and downstream integration impacts, Assess readiness of new technologies for tech transfer, Assess fit-for-purpose application across different molecule classes, Assess scalability and reproducibility, Assess impact on quality attributes, Act as a scientific bridge between R&D and, Ensure new platforms are scientifically sound, Ensure new platforms are translatable to production workflows, Ensure design decisions align with manufacturing realities, Partner with internal stakeholders, Develop design-for-manufacturability strategies, Develop internal guidelines for manufacturability, Develop AI-assisted design-for-manufacturability frameworks, Integrate AI-assisted design-for-manufacturability frameworks, Leverage internal datasets, Leverage external computational tools, Proactively identify risks, Proactively mitigate risks, Lead AI-enabled design initiatives, Support AI-enabled design initiatives, Translate computational design outputs into experimentally validated constructs, Ensure alignment between in silico design predictions and, Generate novel ideas, Contribute to intellectual property portfolio, Draft scientific papers, File patents, Report innovations in scientific forums, Contribute to development of scientific publications, Contribute to conference presentations, Contribute to webinars, Prepare technical reports, Review technical reports, Prepare technical documentation, Review technical documentation", "teamCollaboration" : "Cross-functional teams; Cross-cultural teams; Internal stakeholders; Quality Assurance; Process Development; Manufacturing", "projectManagementSkills" : [ "Project management" ], "domainKnowledge" : "Antibody formats; Protein science; Biologics production; Molecular engineering; Structure prediction; Developability scoring; Aggregation; Mispairing; Heterogeneity", "domainList" : [ "antibody-formats", "protein-science", "biologics-production", "molecular-engineering", "structure-prediction", "developability-scoring", "aggregation", "mispairing", "heterogeneity" ], "domainSpecificKnowledge" : [ "Antibody formats", "Protein science", "Biologics production", "Molecular engineering", "Structure prediction", "Developability scoring", "Aggregation", "Mispairing", "Heterogeneity" ], "toolProficiency" : [ "Computational tools" ], "communicationSkills" : "Scientific publications; Conference presentations; Webinars; Technical reports; Technical documentation", "documentationSkills" : "Technical documentation", "innovationCreativity" : "Innovation; Intellectual property; Novel ideas; R&D innovation", "problemSolvingSkills" : "Problem-solving skills; Troubleshooting", "qualificationsBasic" : "Ph.D. in Biochemistry, Molecular Biology, Cell Biology, Structural Biology, Bioengineering or related field, At least 5 years of experience in antibody design, protein expression, and purification, Expertise in bispecific design, Troubleshooting expression challenges, Demonstrated record of success with protein engineering for enhanced protein expression or properties, Experience with biophysical characterization of proteins, Experience with assessment of protein-protein interactions, Analytical and problem-solving skills, Wide ranging experience in analytical techniques, Excellent written and verbal English communication skills", "qualificationsPreferred" : "Experience in an industrial setting, Familiarity with automation and high-throughput techniques for protein expression and purification", "workSiteFlexibility" : "Onsite", "rawDescription" : "About GenScript GenScript Biotech Corporation (Stock Code: 1548.HK) is a global biotechnology group. Founded in 2002, GenScript has an established global presence across North America, Europe, the Greater China, and Asia Pacific. GenScript's businesses encompass four major categories based on its leading gene synthesis technology, including operation as a Life Science CRO, enzyme and synthetic biology products, biologics development and manufacturing, and cell therapy. GenScript is committed to striving towards its vision of being the most reliable biotech company in the world to make humans and nature healthier through biotechnology. Position Overview: We are seeking a highly motivated and experienced Principal Scientist in Bispecific Antibody Design & Engineering to establish and strengthen Singapore’s role as a center of excellence for complex antibody design and molecular engineering. In this role, you will serve as a functional leader in molecular design, format selection and recommendation, and engineering strategy while enabling improved expression, developability, and manufacturability. Additionally, you will play a key role in client-facing projects, ensuring seamless collaboration and delivery of high-quality biologics solutions. This position requires a blend of platform building, leadership skills, and the ability to build cross effectively. Key Responsibilities: Biologics Production Leadership: Develop, triage, implement, and troubleshoot innovative strategies for the design and engineering of complex antibody formats (bispecifics, multivalent, Fc-fusions, VHH). to achieve high yields, purity, and functionality. Design and manage a portfolio of projects to provide data-driven, structure-function insights to improve expression, stability, and manufacturability. Oversee a team of research associates and/or biotechnologists, providing technical guidance and fostering a culture of excellence in protein science methodologies. Cross-Functional Collaboration: Collaborate with cross-functional and cross-cultural teams to support the development of biologics, with a focus on evaluate and translate new technologies into production-ready solutions. Periodically review internal and external advancements in: Antibody formats and engineering strategies Upstream and downstream integration impacts driven by molecule design Assess readiness of new technologies for tech transfer, including: Fit-for-purpose application across different molecule classes Scalability and reproducibility Impact on quality attributes (aggregation, mispairing, heterogeneity) Act as a scientific bridge between R&D innovation and operational deployment, ensuring: New platforms are not only scientifically sound but also translatable to production workflows Design decisions are aligned with manufacturing realities Partner with internal stakeholders (e.g., Quality Assurance, Process Development, and Manufacturing) to ensure alignment and efficiency in biologics production workflows. Develop design-for-manufacturability strategies and internal guidelines: Develop and integrate AI-assisted design-for-manufacturability frameworks, leveraging internal datasets and external computational tools (e.g., structure prediction, developability scoring) to proactively identify and mitigate risks such as aggregation, mispairing, and low expression in complex antibody formats. Lead or support AI-enabled design and innovation initiatives (internal and external partnerships, including governmental or consortium projects) by translating computational design outputs into experimentally validated constructs, and ensuring alignment between in silico design predictions and real-world expression, quality, and manufacturability outcomes. Innovation & Intellectual Property: Generate novel ideas and contribute to the company’s intellectual property portfolio by drafting scientific papers, filing patents and reporting innovations in scientific forums. Contribute to the development of scientific publications, conference presentations, and webinars to showcase innovative findings and advancements. Prepare and review technical reports and documentation to internal and external stakeholders. Qualifications and Preferred Skills: Ph.D., in Biochemistry, Molecular Biology, Cell Biology, Structural Biology, Bioengineering or a related field. At least 5 years of experience in antibody design, protein expression, and purification, preferably in an industrial setting. Strong expertise in bispecific design and troubleshooting expression challenges. A demonstrated record of success with protein engineering for enhanced protein expression or properties. Experience with the biophysical characterization of proteins and the assessment of protein-protein interactions. Familiarity with automation and high-throughput techniques for protein expression and purification. Strong analytical and problem-solving skills, with a wide ranging experience in analytical techniques such as SPR, and mass spectrometry. Excellent written and verbal English communication skills, with a track record of scientific publications, presentations, and conferences. GenScript USA Inc/ProBio Inc. is a proud equal opportunity/affirmative action employer committed to attracting, retaining, and maximizing the performance of a diverse and inclusive workforce. It is the Company's policy to ensure equal employment opportunity without discrimination or harassment based on race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, national origin, marital or domestic/civil partnership status, genetic information, citizenship status, uniformed service member or veteran status, or any other characteristic protected by law. GenScript USA Inc./ProBio Inc. maintains a drug-free workplace. Please note: Genscript USA Inc./ProBio Inc. will only contact candidates through verified application sources. GenScript/Probio does not request personal information from candidates through individual email or any other platform.", "summaryDescription" : "Associate Principal / Principal Scientist (Protein Science) at GenScript/ProBio. Skills: Bispecific Antibody Design, Protein Science, Molecular Engineering. Develop innovative strategies for design and engineering of. Implement innovative strategies for design and engineering of", "postedDate" : "2026-06-11T22:09:12.938", "createdAt" : "2026-06-11T22:09:12.938", "lastUpdated" : "2026-06-14T21:07:17.797", "ingestTimestamp" : "2026-06-11T22:09:12.938", "mongoId" : "6a2a830a74d8ee00a06750e5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Antibody design", "Protein expression", "Protein purification", "Bispecific design", "Protein engineering", "Biophysical characterization", "Protein-protein interactions", "Analytical techniques", "SPR", "Mass spectrometry", "Leadership", "Mentoring", "Bispecific Antibody Design", "Protein Science", "Molecular Engineering", "Functional leadership", "Platform building", "Client-facing projects", "Tech transfer", "Operational deployment", "Intellectual property", "Project management", "Antibody formats", "Protein science", "Biologics production", "Molecular engineering", "Structure prediction", "Developability scoring", "Aggregation", "Mispairing", "Heterogeneity", "Computational tools" ], "skillCount" : 32, "jobCategory" : "other", "jobSubcategory" : "protein-&-antibody", "dataQualityScore" : 0.8888889, "_score" : 855.14386, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Biotechnology" }, { "id" : "6a2a7e5b74d8ee00a0668caa", "title" : "Principal Applied Scientist", "company" : "UiPath", "industry" : "Engineering", "salary" : { "min" : 200000.0, "max" : 250000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "Bellevue", "locations" : [ "Bellevue" ], "timestamp" : "2026-06-13T20:12:20.454", "fingerprint" : "8ead48167c8fe2d775c15404dcdc4333c40dc38f356d2f6493cf875e7fc551e8", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/uipath/e786c87c-054c-4ad7-a3c1-f8cf75f93c42/application", "externalId" : "e786c87c-054c-4ad7-a3c1-f8cf75f93c42", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bellevue", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6144219,-122.1923370" } ], "locationText" : "Bellevue, Washington, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 10, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, LLMs, Reinforcement learning, ML frameworks, AI systems, Multimodal pipelines, ML infrastructure, ML operations, Prompting, Retrieval-augmented generation, Chain-of-thought, Tool use, Long-term memory, Imitation learning", "professionalSkills" : [ "Technical strategy", "Productization", "System design", "ML infrastructure", "Model serving", "Continuous learning", "ML operations", "Agentic systems", "Research advances", "Automation workflows", "Agent behavior", "Cost analysis", "Latency analysis", "Quality analysis", "Technical leadership", "Experimentation", "Reproducibility", "Versioning", "Rigorous evaluation", "Ecosystem partners" ], "hardSkillsList" : [ "Agent-based automation", "Autonomous agents", "Multi-step reasoning", "LLM fine-tuning", "Computer-use modeling", "Agent orchestration", "Decision-making systems", "Model training", "Large-scale inference", "Model monitoring", "Drift detection", "Learning loops", "Offline evaluation", "Simulation environments", "Human-in-the-loop feedback", "A/B testing" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Agent-based automation", "level" : "intermediate" }, { "name" : "Autonomous agents", "level" : "intermediate" }, { "name" : "Multi-step reasoning", "level" : "intermediate" }, { "name" : "LLM fine-tuning", "level" : "intermediate" }, { "name" : "Computer-use modeling", "level" : "intermediate" }, { "name" : "Agent orchestration", "level" : "intermediate" }, { "name" : "Decision-making systems", "level" : "intermediate" }, { "name" : "Model training", "level" : "intermediate" }, { "name" : "Large-scale inference", "level" : "intermediate" }, { "name" : "Model monitoring", "level" : "intermediate" }, { "name" : "Drift detection", "level" : "intermediate" }, { "name" : "Learning loops", "level" : "intermediate" }, { "name" : "Offline evaluation", "level" : "intermediate" }, { "name" : "Simulation environments", "level" : "intermediate" }, { "name" : "Human-in-the-loop feedback", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Machine Learning, AI systems, Agent orchestration, LLM fine-tuning", "majorSkillsList" : [ "Machine Learning", "AI systems", "Agent orchestration", "LLM fine-tuning" ], "coreResponsibilities" : "Define and drive technical strategy for agent-based automation, Architect, prototype, and deploy advanced ML and AI, Lead the design and implementation of ML infrastructure, Partner closely with product, engineering, design, and go-to-market, Research state-of-the-art techniques, Apply techniques to automation workflows, Establish best practices, frameworks, and metrics for evaluating, Serve as a technical leader and mentor, Foster a culture of experimentation, reproducibility, versioning, and, Represent UiPath in the broader community", "teamCollaboration" : "Partner closely with product, engineering, design, and go-to-market teams; Collaboration with academia or ecosystem partners", "domainKnowledge" : "Agent-based automation; Autonomous agents; Enterprise automation; Foundation models; Agentic systems", "domainList" : [ "agent-based-automation", "autonomous-agents", "enterprise-automation", "foundation-models", "agentic-systems" ], "domainSpecificKnowledge" : [ "Agent-based automation", "Autonomous agents", "Enterprise automation", "Foundation models", "Agentic systems" ], "toolProficiency" : [ "ML frameworks", "ML libraries" ], "communicationSkills" : "Translate complex ML concepts", "innovationCreativity" : "Research advances; Experimentation", "problemSolvingSkills" : "Multi-step reasoning; Decision-making systems; Rigorous evaluation", "outcomesObjectives" : "Translate research advances into customer-facing capabilities; Drive high-impact outcomes", "qualificationsBasic" : "Advanced degree in Computer Science, Machine Learning, AI, or related field, or equivalent experience, 10+ years of industry experience in machine learning, Substantial experience building and operating ML systems in production, Deep expertise in modern ML frameworks and libraries, Proficiency in Python, Experience integrating ML models into large-scale software systems, Experience with large datasets, Experience with distributed training or inference, Experience with scalable architecture design, Experience with optimization for latency, throughput, and cost, Excellent communication skills", "qualificationsPreferred" : "MS or PhD preferred, Proven experience with large language models or foundation models, Fine-tuning, data preparation, inference optimization, or model evaluation experience", "workSiteFlexibility" : "Flexible", "rawDescription" : "LIFE AT UIPATH The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose. Could that be you? As a Principal Applied Scientist, you will lead the architecture, research, and productization of these next-generation ML systems, bridging deep research with deployment at scale and shaping the future of enterprise automation. What You Will Do • Define and drive technical strategy for agent-based automation, including how autonomous agents use LLMs, reinforcement learning, simulation environments, tool use, and multi-step reasoning to integrate with the UiPath platform. • Architect, prototype, and deploy advanced ML and AI systems, covering LLM fine-tuning, multimodal pipelines, computer-use modeling, agent orchestration frameworks, and decision-making systems. • Lead the design and implementation of ML infrastructure and services for model training, fine-tuning, large-scale inference, model serving, monitoring, drift detection, continuous learning loops, and ML operations for agentic systems. • Partner closely with product, engineering, design, and go-to-market teams to translate research advances into customer-facing capabilities. • Research state-of-the-art techniques in prompting, retrieval-augmented generation, chain-of-thought, tool use, long-term memory, and RL or imitation learning for agent behavior, and apply them to automation workflows. • Establish best practices, frameworks, and metrics for evaluating agentic systems, including offline evaluation, simulation environments, human-in-the-loop feedback, A/B testing, and cost, latency, and quality analysis. • Serve as a technical leader and mentor across ML engineering, data science, and software engineering, fostering a culture of experimentation, reproducibility, versioning, and rigorous evaluation. • Represent UiPath in the broader community through publications, open-source contributions, conference participation, and collaboration with academia or ecosystem partners. What We Are Looking For • Advanced degree (MS or PhD preferred) in Computer Science, Machine Learning, AI, or a related field, or equivalent experience. • 10+ years of industry experience in machine learning, including substantial experience building and operating ML systems in production. • Deep expertise in modern ML frameworks and libraries, strong proficiency in Python, and experience integrating ML models into large-scale software systems. • Proven experience with large language models or foundation models, including fine-tuning, data preparation, inference optimization, or model evaluation. • Experience with large datasets, distributed training or inference, scalable architecture design, and optimization for latency, throughput, and cost. • Excellent communication skills with the ability to translate complex ML concepts to product and business audiences. • Demonstrated technical leadership in mentoring, influencing strategy, balancing research with delivery, and driving high-impact outcomes. #LI-MH1 Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned. Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected. We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy https://www.uipath.com/legal/trust-and-security/privacy-policy.", "summaryDescription" : "Principal Applied Scientist at UiPath. Skills: Machine Learning, AI systems, Agent orchestration, LLM fine-tuning. Define and drive technical strategy for agent-based automation. Architect, prototype, and deploy advanced ML and AI", "postedDate" : "2026-06-11T16:30:27.984", "createdAt" : "2026-06-11T16:30:27.984", "lastUpdated" : "2026-06-13T20:12:20.454", "ingestTimestamp" : "2026-06-11T16:30:27.984", "mongoId" : "6a2a7e5b74d8ee00a0668caa", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 200000, "salaryAnnualMax" : 250000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Agent-based automation", "Autonomous agents", "Multi-step reasoning", "LLM fine-tuning", "Computer-use modeling", "Agent orchestration", "Decision-making systems", "Model training", "Large-scale inference", "Model monitoring", "Drift detection", "Learning loops", "Offline evaluation", "Simulation environments", "Human-in-the-loop feedback", "A/B testing", "Leadership", "Mentoring", "Machine Learning", "AI systems", "Technical strategy", "Productization", "System design", "ML infrastructure", "Model serving", "Continuous learning", "ML operations", "Agentic systems", "Research advances", "Automation workflows", "Agent behavior", "Cost analysis", "Latency analysis", "Quality analysis", "Technical leadership", "Experimentation", "Reproducibility", "Versioning", "Rigorous evaluation", "Ecosystem partners", "Enterprise automation", "Foundation models", "ML frameworks", "ML libraries" ], "skillCount" : 44, "jobCategory" : "engineering", "jobSubcategory" : "engineering", "dataQualityScore" : 1.0, "_score" : 851.7115, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2d58e574d8ee00a0b87933", "title" : "Scientist - Strain Engineering", "company" : "Cambrium", "industry" : "Biotech", "salary" : { "min" : 65000.0, "max" : 90000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Scientist - Strain Engineering in Berlin, Germany, adjusted for the Biotech industry and contract employment type." }, "location" : "Berlin, DE", "locations" : [ "Berlin", "DE" ], "timestamp" : "2026-06-15T09:58:39.946", "fingerprint" : "a0b6573ce767a053620a2c031b15a2afa8b3567d6f25cb9582e2996e0459def8", "source" : "personio", "language" : "en", "applyUrl" : "https://cambrium.jobs.personio.de/job/2653146", "externalId" : "2653146", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Berlin", "country" : "Germany", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "52.5173885,13.3951309" } ], "locationText" : "Berlin, Germany", "employmentType" : "CONTRACT", "minimumEducation" : "Master's", "technicalSkills" : "Molecular biology, Yeast biology, Pichia, High-throughput screening, Lab automation, LIMS, Fermentations, Bioreactors, Computational biology, Machine learning, HPLC, MS", "professionalSkills" : [ "Strain engineering", "Project management", "Data analysis", "Decision-making", "Resource allocation" ], "hardSkillsList" : [ "Strain engineering", "Molecular biology", "Yeast biology", "High-throughput screening", "Lab automation", "Fermentations", "Bioreactors", "Computational biology", "Machine learning", "HPLC", "MS" ], "softSkillsList" : [ "Support", "Guide" ], "hardSkills" : [ { "name" : "Strain engineering", "level" : "intermediate" }, { "name" : "Molecular biology", "level" : "intermediate" }, { "name" : "Yeast biology", "level" : "intermediate" }, { "name" : "High-throughput screening", "level" : "intermediate" }, { "name" : "Lab automation", "level" : "intermediate" }, { "name" : "Fermentations", "level" : "intermediate" }, { "name" : "Bioreactors", "level" : "intermediate" }, { "name" : "Computational biology", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "HPLC", "level" : "intermediate" }, { "name" : "MS", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Support" }, { "name" : "Guide" } ], "majorSkills" : "Strain Engineering, Microbial Production, High-throughput Screening", "majorSkillsList" : [ "Strain Engineering", "Microbial Production", "High-throughput Screening" ], "coreResponsibilities" : "Manage strain engineering projects, Experimental design, Wet-lab execution, In silico data analysis, Run high-throughput screenings, Improve strain performance, Support up-scaling, Support bioprocess team, Run controlled fermentations, Support junior team members, Guide junior team members, Collaborate with computational engineers, Enhance platform tools, Manage large datasets, Ensure data integrity, Conduct data analysis, Drive informed decision-making, Present work, Communicate work, Align business goals, Align timelines", "teamCollaboration" : "Junior team members; Computational engineers; Bioprocess team; Internal stakeholders; External stakeholders", "projectManagementSkills" : [ "Project management", "Experimental design", "Resource allocation" ], "domainKnowledge" : "Molecular intelligence; Living systems; Enzymes; Polymers; Peptides; Recombinant molecules; Structural proteins; Bioprocess; Yeast biology; Pichia; Computational biology; Machine learning", "domainList" : [ "molecular-intelligence", "living-systems", "enzymes", "polymers", "peptides", "recombinant-molecules", "structural-proteins", "bioprocess", "yeast-biology", "pichia", "computational-biology", "machine-learning" ], "domainSpecificKnowledge" : [ "Molecular intelligence", "Living systems", "Enzymes", "Polymers", "Peptides", "Recombinant molecules", "Structural proteins", "Bioprocess", "Yeast biology", "Pichia", "Computational biology", "Machine learning" ], "toolProficiency" : [ "LIMS" ], "communicationSkills" : "Present work; Communicate work", "documentationSkills" : "Data integrity; Data analysis", "continuousLearning" : "Learning & Development Programme", "problemSolvingSkills" : "Data analysis; Decision-making", "specialRequirements" : "7-months fixed-term contract", "outcomesObjectives" : "Improve strain performance; Support up-scaling; Drive informed decision-making", "qualificationsBasic" : "PhD or MSc with 3+ years industry experience, Developing microbes for recombinant production, Molecular biology techniques, Yeast biology, High-throughput techniques, Lab automation, Proficient in LIMS", "qualificationsPreferred" : "Experience with controlled fermentations, Bioreactors, Computational biology methodologies, Machine learning methodologies, Analytical methods such as HPLC, MS", "workSiteFlexibility" : "Flexible", "rawDescription" : "What we do Cambrium is a molecular intelligence company engineering advanced materials that outperform. From personal care to textiles, mobility to home care, we design and manufacture materials that deliver real results today and for generations to come. Our platform brings together molecular intelligence and living systems to design and produce enzymes, polymers, and peptides at scale, unlocking performance characteristics that traditional chemistry could never access - specifically within polymers. We are an equal-opportunity employer and value diversity. We consider all applications equally regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply, and we can help with immigration. Your role We are looking for a Scientist - Strain Engineering, who will be responsible for building and screening microbial production strains and preparing them to be scaled. This position is a parental leave cover with a 7-months fixed-term contract starting October 2026. Your responsibilities: Manage strain engineering projects from experimental design and wet-lab execution to in silico data analysis. Run high-throughput screenings of strain libraries for the production of recombinant molecules, such as peptides, enzymes and structural proteins. Improve strain performance and support the up-scaling of commercial production strains. Support the bioprocess team by running controlled fermentations at lab-scale. Support and guide junior team members. Collaborate with computational engineers to enhance platform tools and manage large datasets from high-throughput screenings. Ensure data integrity across screening campaigns and conduct data analysis to drive informed decision-making. Present and communicate your work on a regular basis to internal and external stakeholders. Align business goals and timelines with strain engineering resource allocation. Your profile Must haves PhD, or MSc with 3+ years of industry experience, focused on developing microbes for recombinant production of proteins and enzymes. Strong experience with molecular biology techniques. Strong experience with yeast biology (experience with Pichia is a plus). Experience with high-throughput techniques and lab automation. Proficient in the use of LIMS (Laboratory Information Management System). Nice to haves Experience with controlled fermentations in bioreactors. Understanding of both computational biology and machine learning methodologies. Experience with analytical methods such as HPLC or MS. What we offer In addition to a competitive salary, you can expect the following: Flexible working hours Learning & Development Programme for all our team members Urban Sports Club Membership Subsidized lunch and impassioned lunch discussions Regular team events The opportunity to be part of our journey to a future of advanced materials that outperform", "summaryDescription" : "Scientist - Strain Engineering at Cambrium. Skills: Strain Engineering, Microbial Production, High-throughput Screening. Manage strain engineering projects. Experimental design", "createdAt" : "2026-06-14T08:25:46.368", "lastUpdated" : "2026-06-15T09:58:39.946", "ingestTimestamp" : "2026-06-14T08:25:46.368", "mongoId" : "6a2d58e574d8ee00a0b87933", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ "Strain engineering", "Molecular biology", "Yeast biology", "High-throughput screening", "Lab automation", "Fermentations", "Bioreactors", "Computational biology", "Machine learning", "HPLC", "MS", "Support", "Guide", "Strain Engineering", "Microbial Production", "High-throughput Screening", "Project management", "Data analysis", "Decision-making", "Resource allocation", "Experimental design", "Molecular intelligence", "Living systems", "Enzymes", "Polymers", "Peptides", "Recombinant molecules", "Structural proteins", "Bioprocess", "Pichia", "LIMS" ], "skillCount" : 31, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 822.72424, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.95 }, { "id" : "68e6b1dc70f0b99d58d66e3a", "title" : "Principal Applied Scientist, AGI Foundations", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, Artificial Intelligence", "salary" : { "min" : 179000.0, "max" : 309400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, Massachusetts, USA", "locations" : [ "Boston, Massachusetts, USA" ], "timestamp" : "2026-06-15T09:19:51.035", "fingerprint" : "2b6cf8770992355deefd6060592c16532820a8715d4cb5d23b3970eb2b103232", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3102574/apply", "externalId" : "a33fb0c2-2341-4604-a786-849c6a5de168", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, Java, C++, Generative AI, Large language models, Multimodal models, Computer vision, Machine learning, PyTorch, TensorFlow, Scikit-learn, Hugging Face", "professionalSkills" : [ "Algorithm design", "Model structure", "Scientific reviews", "Experimental design", "Problem decomposition", "Strategy development" ], "hardSkillsList" : [ "Predictive modeling", "Data analysis", "Algorithm design", "Model structure", "Scientific reviews", "Experimental design", "Problem decomposition", "Strategy development" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Predictive modeling", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Algorithm design", "level" : "intermediate" }, { "name" : "Model structure", "level" : "intermediate" }, { "name" : "Scientific reviews", "level" : "intermediate" }, { "name" : "Experimental design", "level" : "intermediate" }, { "name" : "Problem decomposition", "level" : "intermediate" }, { "name" : "Strategy development", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Generative AI, Machine Learning, Large language models, Computer Vision", "majorSkillsList" : [ "Generative AI", "Machine Learning", "Large language models", "Computer Vision" ], "coreResponsibilities" : "Define research directions, Invent machine learning techniques, Conduct rigorous experiments, Publish research results, Translate research into practice, Develop long-term strategies, Persuade teams to adopt strategies, Propose goals, Deliver on goals, Participate in organizational planning, Participate in hiring, Participate in mentorship, Participate in leadership development, Build scalable science solutions, Build scalable engineering solutions, Serve as scientific resource, Lead scientific reviews, Review experimental design, Review modeling, Review verification, Review research procedures, Probe assumptions, Illuminate pitfalls, Foster shared understanding, Align teams toward strategies, Educate scientific community, Keep community updated, Guide career growth, Develop junior scientists, Develop junior leads, Drive development of GenAI, Handle Amazon-scale use cases, Impact customer experiences, Develop multimodal LLMs, Develop Gen AI, Provide customer experience", "teamCollaboration" : "Cross-organization views; Organizational planning; Leadership development", "domainKnowledge" : "Artificial General Intelligence; Generative AI; Large language models; Multimodal models; Computer vision; Amazon-scale use cases", "domainList" : [ "artificial-general-intelligence", "generative-ai", "large-language-models", "multimodal-models", "computer-vision", "amazon-scale-use-cases" ], "domainSpecificKnowledge" : [ "Artificial General Intelligence", "Generative AI", "Large language models", "Multimodal models", "Computer vision", "Amazon-scale use cases" ], "toolProficiency" : [ "PyTorch", "TensorFlow", "Scikit-learn", "Hugging Face" ], "innovationCreativity" : "Invent machine learning techniques; Develop long-term strategies", "problemSolvingSkills" : "Decompose complex problems; Tackle intrinsically hard problems", "outcomesObjectives" : "Impact customer experiences", "qualificationsBasic" : "5+ years predictive modeling, PhD in Electrical Engineering, PhD in Computer Science, PhD in Mathematics, Experience programming in Java, Experience programming in C++, Experience programming in Python, Leading experienced scientists, Developing junior members", "qualificationsPreferred" : "10+ years of experience, Experience with AWS, Experience with GCP, Experience with Azure, Experience with PyTorch, Experience with TensorFlow, Experience with scikit-learn, Experience with Hugging Face, Experience with large language models, Experience with multimodal models, Experience with computer vision, Experience with Generative AI, Experience with Amazon-scale use cases, Experience with scientific reviews, Experience with experimental design, Experience with modeling, Experience with verification, Experience with research procedures, Experience with mentoring, Experience with hiring, Experience with developing scientists, Experience with developing leads, Experience with organizational planning, Experience with leadership development, Experience with full-cycle development, Experience with conception, Experience with design, Experience with implementation, Experience with testing, Experience with documentation, Experience with delivery, Experience with maintenance, Experience with multimodal LLMs, Experience with Gen AI, Experience with Computer Vision", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "As a Principal Scientist within the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modeling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team The AGI team has a mission to push the envelope with multimodal LLMs and Gen AI in Computer Vision, in order to provide the best-possible experience for our customers. Basic Qualifications: - 5+ years of hands-on work in predictive modeling and analysis experience - PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field - Experience working in predictive modeling and analysis - Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives - Experience programming in Java, C++, Python or related language - Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment Preferred Qualifications: - 10+ years of relevant work in industry or academia experience - Knowledge of problem solving, algorithm design and complexity analysis - Experience creating novel algorithms and advancing the state of the art - Have peer-reviewed scientific contributions in premier journals and conferences Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Principal Applied Scientist, AGI Foundations at Amazon.com Services LLC. Skills: Generative AI, Machine Learning, Large language models, Computer Vision. Define research directions. Invent machine learning techniques", "postedDate" : "2026-06-14T03:15:36.099", "createdAt" : "2026-06-14T03:15:36.099", "lastUpdated" : "2026-06-15T09:19:51.035", "ingestTimestamp" : "2026-06-14T03:15:36.099", "mongoId" : "68e6b1dc70f0b99d58d66e3a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3102574/apply", "salaryAnnualMin" : 179000, "salaryAnnualMax" : 309400, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Predictive modeling", "Data analysis", "Algorithm design", "Model structure", "Scientific reviews", "Experimental design", "Problem decomposition", "Strategy development", "Leadership", "Mentoring", "Generative AI", "Machine Learning", "Large language models", "Computer Vision", "Artificial General Intelligence", "Multimodal models", "Computer vision", "Amazon-scale use cases", "PyTorch", "TensorFlow", "Scikit-learn", "Hugging Face" ], "skillCount" : 22, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Executive", "dataQualityScore" : 1.0, "_score" : 815.5003, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2cba5a74d8ee00a09f906e", "title" : "Senior or Principal Data Scientist/Machine Learning Scientist", "industry" : "Technology", "salary" : { "min" : 175000.0, "max" : 250000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Data Scientist/Machine Learning Scientist in Cambridge, United States, adjusted for seniority and industry." }, "location" : "Cambridge, MA", "locations" : [ "Cambridge, MA" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-15T05:15:21.554", "fingerprint" : "f157367f29879db9d85a91c4e1327e0df66eb8c53d3924a931697cb5c8582155", "source" : "jazzhr", "language" : "en", "externalId" : "tljr8NqfPM", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Cambridge", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3656347,-71.1040018" } ], "locationText" : "Cambridge, Massachusetts, United States", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, R, SQL, Spark, Snowflake, BigQuery, Redshift, Databricks, Dbt, Fivetran, Airflow, AWS, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow", "professionalSkills" : [ "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis" ], "hardSkillsList" : [ "Statistical methods", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" }, { "name" : "Regression", "level" : "intermediate" }, { "name" : "Classification", "level" : "intermediate" }, { "name" : "Clustering", "level" : "intermediate" }, { "name" : "Time-series analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Data science, Machine learning", "majorSkillsList" : [ "Data science", "Machine learning" ], "coreResponsibilities" : "Develop and deploy machine learning models, Design and implement data pipelines, Build and maintain BI dashboards, Perform statistical analysis, Conduct quantitative research, Collaborate with engineering teams, Communicate findings to stakeholders", "teamCollaboration" : "Cross-functional teams; Stakeholder communication", "domainKnowledge" : "Cloud data stacks", "domainList" : [ "cloud-data-stacks" ], "domainSpecificKnowledge" : [ "Cloud data stacks" ], "toolProficiency" : [ "Tableau", "Power BI", "Looker" ], "communicationSkills" : "Present findings", "qualificationsBasic" : "5+ years experience, Master's degree in Statistics, SQL proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification", "workSiteFlexibility" : "Onsite", "summaryDescription" : "Senior or Principal Data Scientist/Machine Learning Scientist. Skills: Data science, Machine learning. Develop and deploy machine learning models. Design and implement data pipelines", "createdAt" : "2026-06-14T01:14:00.336", "lastUpdated" : "2026-06-15T05:15:21.554", "ingestTimestamp" : "2026-06-14T01:14:00.336", "mongoId" : "6a2cba5a74d8ee00a09f906e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 175000, "salaryAnnualMax" : 250000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistical methods", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data science", "Machine learning", "Data engineering", "ML/AI", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Cloud data stacks", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker" ], "skillCount" : 23, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.5555556, "_score" : 802.59796, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "69fda4e24c40e2acd1b99666", "title" : "Principal Applied Scientist, Amazon Payments", "company" : "Amazon.com Services LLC", "industry" : "Data Science, Applied Science, international stores", "salary" : { "min" : 198900.0, "max" : 269000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T04:18:45.670", "fingerprint" : "5131b8cae2e9a9c3ace8d612ccb0cf86994677edfa21ffa7de8a86235c7ee611", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10414299/apply", "externalId" : "5d1a0b8b-e599-4da8-abf1-22fe1f357ede", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD or MSc", "experienceMinYears" : 10, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Machine Learning, GenAI, Natural Language Processing", "professionalSkills" : [ "Thought leadership", "Research direction", "Roadmap creation" ], "hardSkillsList" : [ "AI", "Machine Learning", "GenAI", "Natural Language Processing", "Recommendation systems", "Prediction modeling" ], "softSkillsList" : [ "Leadership", "Judgment", "Innovation", "Inspire passion" ], "hardSkills" : [ { "name" : "AI", "level" : "intermediate" }, { "name" : "Machine Learning", "level" : "intermediate" }, { "name" : "GenAI", "level" : "intermediate" }, { "name" : "Natural Language Processing", "level" : "intermediate" }, { "name" : "Recommendation systems", "level" : "intermediate" }, { "name" : "Prediction modeling", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Judgment" }, { "name" : "Innovation" }, { "name" : "Inspire passion" } ], "majorSkills" : "AI, Machine Learning, GenAI", "majorSkillsList" : [ "AI", "Machine Learning", "GenAI" ], "coreResponsibilities" : "Mentor a team of applied scientists, Create environment for applied scientists, Partner with engineering leaders, Deliver new Amazon Payments services, Leverage Machine Learning and GenAI, Identify research directions, Create roadmaps for research, Communicate roadmaps to senior leadership, Work closely with engineering teams, Bring research to production, Attract best scientists in machine learning, Leverage Amazon’s heterogeneous data sources, Leverage large-scale computing resources", "teamCollaboration" : "Work with peers; Partner with engineering leaders; Work with talented scientists; Work with talented peers", "projectManagementSkills" : [ "Roadmap creation" ], "domainKnowledge" : "Amazon Payments AI; Recommendation systems; Prediction systems; GEN AI platform; SOP automation", "domainList" : [ "amazon-payments-ai", "recommendation-systems", "prediction-systems", "gen-ai-platform", "sop-automation" ], "domainSpecificKnowledge" : [ "Amazon Payments AI", "Recommendation systems", "Prediction systems", "GEN AI platform", "SOP automation" ], "communicationSkills" : "Written communication; Verbal communication", "innovationCreativity" : "Expects and requires innovation", "problemSolvingSkills" : "Dive deep", "qualificationsBasic" : "PhD or MSc in computer science, 10+ years in AI and Machine Learning, Track record of thought leadership, skills in collaboration and teamwork, record of delivery in industry and academic contexts, Ability to handle multiple competing priorities, Excellent written and verbal communication skills", "qualificationsPreferred" : "12+ years in AI, Machine Learning, and Natural Language Processing, publication history in top publications", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are looking for a Principal Applied Scientist for Amazon Payments AI/ML Team, which contributes science and science-related engineering work for Amazon’s Payments Artificial Intelligence services (e.g. Amazon Payments Recommendation, Prediction, GEN AI platform to enable SOP automation and new projects already underway). In this role, you will work with your peers and senior management to set the direction for Amazon’s AI efforts. Our mission is to put the power of AI in the hands of every developer. You will be responsible for mentoring a team of applied scientists. You will be responsible for creating a strong environment for applied scientists, with a focus on recruiting, retaining and developing top talent. You will partner with engineering leaders to deliver remarkable new Amazon Payments services and features that leverage Machine Learning and GenAI. As a Principal Applied Scientist, you will identify research directions, create roadmaps for forward-looking research and communicate them to senior leadership, and work closely with engineering teams to bring research to production. You will work with teams of talented scientists, and fill the ranks by attracting the best scientists in machine learning, e.g. Amazon payments recommendation and natural language processing for SOP automation. You will work with talented peers and leverage Amazon’s heterogeneous data sources and large-scale computing resources. Basic Qualifications: - PhD or MSc in computer science or related fields - 10 + years in AI and Machine Learning in industry and/or academia - Track record of thought leadership and contributions that have advanced the field - Strong skills in collaboration and teamwork - Strong record of delivery in industry and academic contexts - Ability to handle multiple competing priorities in a fast-paced environment. - Excellent written and verbal communication skills Preferred Qualifications: - 12+ years in AI, Machine Learning, and Natural Language Processing in industry and/or academia. - Strong publication history in top publications. Professional traits that are not unique to this position, but necessary for Amazon leaders: - Exhibits excellent judgment - Hires and develops great people - Has relentlessly high standards (is never satisfied with the status quo) - Is able to dive deep and is never out of touch with the details of the business or the technology - Expects and requires innovation of her/his team - Has the innate ability to inspire passion in others - Strong results orientation - Thinks big Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually", "summaryDescription" : "Principal Applied Scientist, Amazon Payments at Amazon.com Services LLC. Skills: AI, Machine Learning, GenAI. Mentor a team of applied scientists. Create environment for applied scientists", "postedDate" : "2026-06-13T13:37:36.161", "createdAt" : "2026-06-13T13:37:36.161", "lastUpdated" : "2026-06-15T04:18:45.670", "ingestTimestamp" : "2026-06-13T13:37:36.161", "mongoId" : "69fda4e24c40e2acd1b99666", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10414299/apply", "salaryAnnualMin" : 198900, "salaryAnnualMax" : 269000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "AI", "Machine Learning", "GenAI", "Natural Language Processing", "Recommendation systems", "Prediction modeling", "Leadership", "Judgment", "Innovation", "Inspire passion", "Thought leadership", "Research direction", "Roadmap creation", "Amazon Payments AI", "Prediction systems", "GEN AI platform", "SOP automation" ], "skillCount" : 17, "jobCategory" : "data", "dataQualityScore" : 1.0, "_score" : 801.83124, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2a5dea74d8ee00a061ac00", "title" : "Principal Scientist, Process Chemistry", "company" : "Pfizer", "industry" : "Pharmaceutical", "salary" : { "min" : 106000.0, "max" : 106000.0, "currency" : "USD", "frequency" : "yearly" }, "location" : "United States of America", "locations" : [ "United States of America" ], "timestamp" : "2026-06-13T17:05:08.145", "fingerprint" : "8869fa16ba4051dccde7e9040344941f93ffd9513d0f94ec0b644fdff96f0ca1", "source" : "workday", "language" : "en", "applyUrl" : "https://pfizer.wd1.myworkdayjobs.com/PfizerCareers/job/United-States---Washington--Bothell/Principal-Scientist--Process-Chemistry_4958939-1", "externalId" : "4958939", "industryFunction" : { }, "locationPoint" : "51.43667,5.97917", "structuredLocations" : [ { "city" : "Bothell", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.7623204,-122.2054035" } ], "locationText" : "Bothell, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Organic chemistry, Process development, Analytical methods, Synthetic routes, High-throughput experimentation, Data-rich experimentation, Catalysis, Continuous processing, Predictive technologies, Computational tools, Predictive software", "professionalSkills" : [ "Route screening", "Process development", "Process characterization", "Scale-up", "GMP manufacturing", "Technology transfer", "Resource management" ], "hardSkillsList" : [ "Synthetic organic chemistry", "Process development", "Engineering", "Analytical technologies", "Purification technologies", "GMP deliveries", "Regulatory authoring" ], "softSkillsList" : [ "Technical leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Synthetic organic chemistry", "level" : "intermediate" }, { "name" : "Process development", "level" : "intermediate" }, { "name" : "Engineering", "level" : "intermediate" }, { "name" : "Analytical technologies", "level" : "intermediate" }, { "name" : "Purification technologies", "level" : "intermediate" }, { "name" : "GMP deliveries", "level" : "intermediate" }, { "name" : "Regulatory authoring", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Technical leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Process Chemistry, Drug-linker development, ADC therapeutics", "majorSkillsList" : [ "Process Chemistry", "Drug-linker development", "ADC therapeutics" ], "coreResponsibilities" : "Provide technical leadership, Drive development of safe chemistry, Leverage state-of-the-art technologies, Spearhead advancement of oncology portfolio, Oversee external resources, Manage technology transfer, Manage campaign execution, Serve as technical leader, Serve as strategic leader, Mentor junior staff, Propose technical solutions, Propose strategic solutions, Represent process chemistry, Design laboratory experiments, Execute laboratory experiments, Analyze complex data, Maintain laboratory records, Maintain reports, Maintain patents, Maintain regulatory documents, Maintain external communications, Employ state-of-the-art technologies, Be recognized as technical leader, Author publications, Present externally, Drive technical aspects, Lead technology transfer, Manage CRO/CMO resources, Communicate abstract concepts, Communicate ideas, Communicate solutions, Establish timelines, Deliver on timelines, Promote supportive environment, Promote inclusive environment, Maintain understanding of activities, Maintain understanding of research, Lead authoring for patents, Lead authoring for regulatory documents, Guide cross-functional team decisions, Build relationships with stakeholders, Advocate for department", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Antibody-drug conjugates; Drug-linkers; Targeted cancer therapy; Pharmaceutical development; Regulated pharmaceutical environment", "domainList" : [ "antibody-drug-conjugates", "drug-linkers", "targeted-cancer-therapy", "pharmaceutical-development", "regulated-pharmaceutical-environment" ], "domainSpecificKnowledge" : [ "Antibody-drug conjugates", "Drug-linkers", "Targeted cancer therapy", "Pharmaceutical development", "Regulated pharmaceutical environment" ], "communicationSkills" : "Oral communication; Written communication; Persuasive communication", "documentationSkills" : "Patent authoring; Regulatory document authoring", "continuousLearning" : "Presenting at scientific meetings", "innovationCreativity" : "Scientific innovation", "specialRequirements" : "Laboratory-based position, Use of PPE, Occasional travel, Permanent work authorization in the United States", "outcomesObjectives" : "Deliver breakthroughs; Accelerate delivery of medicines; Develop robust processes; Drive next generation therapy; Achieve portfolio goals", "qualificationsBasic" : "PhD in Organic Chemistry with 4+ years of experience in pharmaceutical process development, Master's degree with 9+ years of relevant experience, Bachelors degree and 12+ years of experience, Proven track record of scientific innovation, Sound understanding of modern synthetic organic chemistry principles, In-depth knowledge of pharmaceutical development, Experience in a regulated pharmaceutical environment, GMP deliveries and regulatory authoring experience", "qualificationsPreferred" : "Experience with drug-linkers for ADCs, Experience mentoring scientific staff, Experience with technology transfer activities, CRO/CDMO resource management experience", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "**OVERVIEW:** Pfizer’s purpose is to deliver breakthroughs that change patients’ lives. Process Research and Development is at the heart of fulfilling Pfizer’s purpose as we work to translate advanced science and technologies into the therapies that matter most. Whether you are in the discovery sciences, ensuring drug safety and efficacy or supporting clinical trials, you will apply cutting edge design and process development capabilities to accelerate and bring the best-in-class medicines to patients around the world. **ROLE SUMMARY:** The Chemical Process and Analytical Development (CPAD) group located in Bothell, WA is responsible for the development of chemical processes and analytical methods for novel drug-linkers (linker-payloads) used in antibody-drug conjugates (ADCs). Our process chemists, analytical chemists, and chemical engineers collaborate to discover phase-appropriate synthetic routes and chemical processes to accelerate the delivery of life saving medicines to patients, and to develop robust and innovative synthetic processes to novel commercial drug-linker candidates that drive the next generation of targeted cancer therapy. As a Principal Scientist in CPAD, you will provide technical leadership to a team of process chemists engaged in route screening/selection, process development, and process characterization for our growing drug-linker portfolio. You will drive the development of safe and scalable chemistry by leveraging state-of-the-art technologies such as high-throughput experimentation, data-rich experimentation, catalysis, continuous processing, and predictive technologies. You will spearhead the advancement of Pfizer’s oncology portfolio through personal laboratory effort as well as oversee external resources through technology transfer and campaign execution at CDMOs. You will serve as a technical and strategic leader for early _and_ late-phase programs while mentoring junior staff members in a supportive and inclusive work environment. You will propose technical and strategic solutions to management and represent process chemistry in cross-functional teams requiring excellent communication skills. Finally, you will be expected to establish an external presence as technical leader in the field by authoring journal articles and presenting at leading external scientific meetings. **ROLE RESPONSIBILITIES:** * Design and execute well-planned laboratory experiments that require complex data analysis. * Maintain high standards for all laboratory records, reports, patents, regulatory documents, and external communications. * Employ state-of-the art technologies including high-throughput experimentation, data-rich experimentation, computational tools, and predictive software to accelerate process development. * Be recognized as a technical leader internally and externally by authoring publications and presenting externally. * Drive technical aspects of early _and_ late phase pharmaceutical development. * Lead technology transfer to internal sites or external CDMOs for GMP manufacturing while managing CRO/CMO resources. * Persuasively communicate abstract concepts, ideas, and solutions to project teams, leadership, and cross-functional teams. * Establish and deliver on tight timelines aligned with our portfolio goals. * Promote a supportive and inclusive work environment and mentor junior staff. * Maintain an understanding of the activities and research carried out by the project team members. * Lead authoring for patents and regulatory documents. * Leverage knowledge and experience to guide cross-functional team decisions. * Build strong relationships with stakeholders to advocate for our department. **BASIC QUALIFICATIONS:** * PhD in Organic Chemistry with 4+ years of experience in pharmaceutical process development, including route design, scale-up, and GMP manufacturing; or a Master’s degree with 9+ years of relevant experience OR Bachelors degree and 12+ years of experience. * Proven track record of scientific innovation and impact, demonstrated through authorship of peer-reviewed publications, patents, or presentations at recognized scientific conferences. * A sound understanding of modern synthetic organic chemistry principles, process development, engineering, analytical and purification technologies. * Excellent written and oral communication skills, with a demonstrated ability to effectively collaborate with stakeholders. * In-depth knowledge of pharmaceutical development from pre-clinical to commercialization. * Experience in a regulated pharmaceutical environment including GMP deliveries and regulatory authoring. * This is an on-site designated role, and you will be expected to work five days per week on-site. **PREFERRED QUALIFICATIONS:** * Experience with drug-linkers for ADCs or other targeted mixed-modality therapeutics. * Experience in mentoring scientific staff, both directly and in a matrix environment. * Experience with technology transfer activities and CRO/CDMO resource management. **PHYSICAL/MENTAL REQUIREMENTS:** * Lifting, sitting, standing, walking, bending and ability to perform mathematical calculations. **NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS:** * This is a laboratory-based position. Adherence to safe work practices, including the use of personal protective equipment (PPE) such as safety glasses, lab coats, and gloves, is required. Occasional travel for business purposes, scientific conferences, or collaboration (typically <10%) is expected. **Additional Job Details:** * Work Location Assignment: **On Premise** * Last date to apply is June 23, 2026 The annual base salary for this position ranges from $106,000.00 to $176,600.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. Relocation assistance may be available based on business needs and/or eligibility. Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. **Sunshine Act** Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. **EEO & Employment Eligibility** Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States. Pfizer endeavors to make [www.pfizer.com/careers](http://www.pfizer.com/careers) accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email [disabilityrecruitment@pfizer.com](mailto:disabilityrecruitment@pfizer.com). This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned. To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on [ _Pfizer Careers_](https://www.pfizer.com/about/careers/ai-use-guidelines). Research and Development", "summaryDescription" : "Principal Scientist, Process Chemistry at Pfizer. Skills: Process Chemistry, Drug-linker development, ADC therapeutics. Provide technical leadership. Drive development of safe chemistry", "postedDate" : "2026-06-11T16:38:32.738", "createdAt" : "2026-06-11T16:38:32.584", "lastUpdated" : "2026-06-13T17:05:08.145", "ingestTimestamp" : "2026-06-11T16:38:32.584", "mongoId" : "6a2a5dea74d8ee00a061ac00", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://pfizer.wd1.myworkdayjobs.com/PfizerCareers/job/United-States---Washington--Bothell/Principal-Scientist--Process-Chemistry_4958939-1", "salaryAnnualMin" : 106000, "salaryAnnualMax" : 106000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Synthetic organic chemistry", "Process development", "Engineering", "Analytical technologies", "Purification technologies", "GMP deliveries", "Regulatory authoring", "Technical leadership", "Mentoring", "Process Chemistry", "Drug-linker development", "ADC therapeutics", "Route screening", "Process characterization", "Scale-up", "GMP manufacturing", "Technology transfer", "Resource management", "Antibody-drug conjugates", "Drug-linkers", "Targeted cancer therapy", "Pharmaceutical development", "Regulated pharmaceutical environment" ], "skillCount" : 23, "jobCategory" : "engineering", "seniorityLevel" : "senior", "dataQualityScore" : 1.0, "_score" : 788.6086, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Pharmaceutical" }, { "id" : "6a16291c58b93c861e95a2c8", "title" : "Healthcare Engineering Principal", "company" : "HDR", "industry" : "Healthcare", "salary" : { "min" : 235000.0, "max" : 350000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Executive Healthcare Engineering Principal in Dallas, adjusted for HDR's company size and the engineering industry." }, "location" : "United States-Texas-Dallas", "locations" : [ "United States-Texas-Dallas" ], "certifications" : [ "Professional Engineer (PE or P. 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Example: Professional Engineer (PE or P.Eng) license. Extensive experience in project execution Proficient computer skills in Microsoft Office as well as standard design software. Must be comfortable being viewed as a technical expert in engineering analysis and design and have proven background of technical leadership on these types of project An attitude and commitment to being an active participant of our employee-owned culture What We Believe HDR is our company. Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve. Our Commitment As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day. Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees. United States-Texas-Dallas", "summaryDescription" : "Healthcare Engineering Principal at HDR. Skills: Engineering analysis, Engineering design, Technical leadership. Execute projects. Provide technical leadership", "createdAt" : "2026-06-14T06:19:09.514", "lastUpdated" : "2026-06-15T13:54:53.139", "ingestTimestamp" : "2026-06-14T06:19:09.514", "mongoId" : "6a16291c58b93c861e95a2c8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 235000, "salaryAnnualMax" : 350000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Engineering analysis", "Engineering design", "Technical leadership", "Project execution", "Professional Engineer (PE or P. 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Cross-functional projects", "domainKnowledge" : "Ranking systems; Retrieval systems; Recommender systems; Advertising landscape; Generative AI technologies", "domainList" : [ "ranking-systems", "retrieval-systems", "recommender-systems", "advertising-landscape", "generative-ai-technologies" ], "domainSpecificKnowledge" : [ "Ranking systems", "Retrieval systems", "Recommender systems", "Advertising landscape", "Generative AI technologies" ], "communicationSkills" : "Verbal communication; Written communication", "innovationCreativity" : "Invent new product experiences; Innovates on behalf of customers; Invent new scientific techniques and paradigms", "problemSolvingSkills" : "Solve complex challenges", "qualificationsBasic" : "PhD or equivalent in Computer science/Math or related field, Experience in building complex, real-time systems using GenAI, Computer Science fundamentals in data structures, algorithm design and complexity analysis, Ability to develop machine learning platform strategy in recommender systems, Ability to develop a GenAI strategy for recommender systems", "qualificationsPreferred" : "10+ years of relevant, broad research experience after PhD degree, Deep expertise and knowledge of Generative AI methods, Proficiency in programming for algorithm and code reviews, Core competency in mathematics and statistics, Track record of successful projects in algorithm design and product development, Publications at top-tier peer-reviewed conferences or journals, Experience with mentorship and/or management of senior scientists and engineers, Effective verbal and written communication skills with non-technical and technical audiences, Experience working with real-world data sets and building scalable models from big data, Demonstrated track record of project delivery for large, cross-functional projects, Ability to take a project from requirements gathering and design to actual product launch", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Sponsored Products (SP) team is looking for a Principal Scientist to help our millions of shoppers intuitively navigate our vast inventory by harnessing the power of ML and GenAI models. Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, SP helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! As a Principal Scientist in Sponsored Products, you will have deep subject matter expertise in the area of ML and GenAI models for ranking and retrieval systems. You will work with multiple teams of scientists and engineers to translate business and functional requirements into concrete deliverables. You will invent new product experiences that enable our shoppers to easily navigate our vast inventory either via search queries, multi-turn conversations, or other modes of input. You will liaise with internal Amazon partners and work on bringing state-of-the-art models to production in the retrieval and relevance ranking models used in Sponsored Products. You will stay abreast of the latest developments in the space of AI/ML/GenAI modeling and identify opportunities to improve the efficiency and productivity of the team. You will define a long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of applied scientists, and engineers. Key job responsibilities - You define technical and scientific strategies to make progress on difficult scientific problems that are still unsolved at Amazon. - Your influence scientific and engineering methods across all of Sponsored Product and Sponsored Brand. - You invent new scientific techniques and paradigms to address our customers' needs and business problems. - You are a role model and help grow other scientists in the organization. - You have deep and broad expertise in Artificial Intelligence and GenAI. You draw from scientific and industrial maturity to make strategic judgement calls. - You have 10+ years of research experience after a PhD degree. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Within Sponsored Product and Brands, the Demand Utilization Venture team researches and deploys Generative AI and Reinforcement Learning solutions to improve our understanding of shoppers needs, our understanding of advertisers intent, and how we find the right sponsored products for the right shopper in the right search context. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond! Basic Qualifications: - PhD or equivalent in Computer science/Math or related field.  - Experience in building complex, real-time systems using GenAI, with successful delivery to customers. - Computer Science fundamentals in data structures, algorithm design and complexity analysis.  - Ability to develop machine learning platform strategy in the domain of recommender systems. - Ability to develop a GenAI strategy for recommender systems. Preferred Qualifications: 10+ years of relevant, broad research experience after PhD degree or equivalent.  Deep expertise and knowledge of Generative AI methods involved in pre/post training, LLM optimizations for performance and throughput. Proficiency in programming for algorithm and code reviews.  Strong core competency in mathematics and statistics.  Track record of successful projects in algorithm design and product development.  Publications at top-tier peer-reviewed conferences or journals.  Experience with mentorship and/or management of senior scientists and engineers.  Effective verbal and written communication skills with non-technical and technical audiences. Experience working with real-world data sets and building scalable models from big data. Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements. Ability to take a project from requirements gathering and design to actual product launch. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Principal Applied Scientist, Sponsored Products and Brands at Amazon.com Services LLC. Skills: ML, GenAI, Ranking systems, Retrieval systems. Define technical and scientific strategies. Influence scientific and engineering methods", "postedDate" : "2026-06-13T06:10:32.841", "createdAt" : "2026-06-13T06:10:32.841", "lastUpdated" : "2026-06-15T02:43:22.161", "ingestTimestamp" : "2026-06-13T06:10:32.841", "mongoId" : "68e6b1d870f0b99d58d66a7d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3103340/apply", "salaryAnnualMin" : 179000, "salaryAnnualMax" : 309400, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Algorithm design", "Complexity analysis", "Mathematics", "Statistics", "Leadership", "Mentoring", "ML", "GenAI", "Ranking systems", "Retrieval systems", "ML strategy", "GenAI strategy", "Recommender systems", "Advertising landscape", "Generative AI technologies" ], "skillCount" : 15, "jobCategory" : "data", "dataQualityScore" : 1.0, "_score" : 751.22394, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2af78374d8ee00a073d64d", "title" : "(Associate) Principal Bioanalysis Scientist", "company" : "AstraZeneca", "industry" : "Biotechnology", "salary" : { "min" : 650000.0, "max" : 1100000.0, "currency" : "CNY", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Lead Principal Bioanalysis Scientist in the Biotech industry in China, adjusted for seniority and company size." }, "location" : "China", "locations" : [ "China" ], "timestamp" : "2026-06-14T22:39:17.938", "fingerprint" : "73adc78593bd327430f14655fc74a026788fe151a9e9658f37b66ea2561a58b3", "source" : "workday", "language" : "en", "applyUrl" : "https://astrazeneca.wd3.myworkdayjobs.com/Careers/job/Shanghai-JingAn-Office/XMLNAME--Associate--Principal-Bioanalysis-Scientist_R-254201", "externalId" : "R-254201", "industryFunction" : { }, "locationPoint" : "35.8617,104.1954", "structuredLocations" : [ { "country" : "China", "continent" : "as", "workMode" : "onsite" } ], "locationText" : "China", "employmentType" : "FULL_TIME", "technicalSkills" : "PCR, LBA, ELISA, MSD, Flow cytometry, ddPCR, qPCR, VCN, RCL", "professionalSkills" : [ "Bioanalytical studies", "Lab management", "Method validation", "Regulatory filing" ], "hardSkillsList" : [ "Assay development", "Assay validation", "Sample testing", "Data review", "GLP/GCP compliance" ], "softSkillsList" : [ "Mentoring" ], "hardSkills" : [ { "name" : "Assay development", "level" : "intermediate" }, { "name" : "Assay validation", "level" : "intermediate" }, { "name" : "Sample testing", "level" : "intermediate" }, { "name" : "Data review", "level" : "intermediate" }, { "name" : "GLP/GCP compliance", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "Bioanalysis, Assay development, GxP environment", "majorSkillsList" : [ "Bioanalysis", "Assay development", "GxP environment" ], "coreResponsibilities" : "Lead clinical bioanalysis projects, Develop PCR-based assays, Develop LBA assays, Develop flow cytometry assays, Qualify PCR-based assays, Qualify LBA assays, Qualify flow cytometry assays, Validate PCR-based assays, Validate LBA assays, Validate flow cytometry assays, Implement PCR-based assays, Implement LBA assays, Implement flow cytometry assays, Manage in-house bioanalytical studies, Manage outsourced bioanalytical studies, Collaborate with internal teams, Collaborate with CROs, Support lab management, Optimize lab operations, Expand bioanalytical capability, Collaborate with US/UK bioanalytical teams, Transfer PK/IMG/PDiomarker assays, Troubleshoot PK/IMG/PDiomarker assays, Validate PK/IMG/PDiomarker assays, Test PK/IMG/PDiomarker samples, Report PK/IMG/PDiomarker data, Design experiments, Execute experiments, Review experiments, Develop ddPCR methods, Develop qPCR methods, Develop LBA methods, Develop flow cytometry methods, Validate ddPCR methods, Validate qPCR methods, Validate LBA methods, Validate flow cytometry methods, Review sample analysis data, Approve sample analysis data, Review method validation protocols, Approve method validation protocols, Review method validation reports, Approve method validation reports, Review bioanalytical sample testing reports, Approve bioanalytical sample testing reports, Review NDALA dossier sections, Approve NDALA dossier sections, Review SOPs, Approve SOPs, Mentor junior scientists, Present results at team/department meetings, Prepare controlled documents, Prepare study plans, Prepare reports, Contribute to regulatory submissions, Manage resources, Manage timelines, Ensure on-schedule delivery", "teamCollaboration" : "Internal teams; CROs; US/UK bioanalytical teams", "projectManagementSkills" : [ "Manage multiple projects", "Manage timelines" ], "domainKnowledge" : "Cell therapy projects; Biotherapeutic development; Regulatory filing; GxP environment; ICH M10 guidelines; FDA guidelines; EMA guidelines; GLP; GCP; NDALA submission", "domainList" : [ "cell-therapy-projects", "biotherapeutic-development", "regulatory-filing", "gxp-environment", "ich-m10-guidelines", "fda-guidelines", "ema-guidelines", "glp", "gcp", "ndala-submission" ], "domainSpecificKnowledge" : [ "Cell therapy projects", "Biotherapeutic development", "Regulatory filing", "GxP environment", "ICH M10 guidelines", "FDA guidelines", "EMA guidelines", "GLP", "GCP", "NDALA submission" ], "toolProficiency" : [ "MSD" ], "communicationSkills" : "Written communication; Oral communication; English; Chinese; Present results", "documentationSkills" : "Method validation protocols; Method validation reports; Bioanalytical sample testing reports; NDALA dossier sections; SOPs; Controlled documents; Study plans; Reports", "problemSolvingSkills" : "Troubleshooting", "qualificationsBasic" : "Degree in Biology, Biochemistry, Pharmacology, or related field, Experience in pharmaceuticals or biotech, Hands-on experience developing and validating LBA (ELISA, MSD), ddPCR/qPCR (VCN, RCL), and multi-parameter flow cytometry assays (cell counting, immunophenotyping, functional/intracellular staining) in a GxP environment, Experience with bioanalytical method validation per ICH M10, FDA, and EMA guidelines, Written and oral communication skills in English and Chinese, Ability to manage multiple projects and meet timelines", "qualificationsPreferred" : "B. Sc. with 10+ years of pharma/biotech experience, M. Sc. with 8+ years of pharma/biotech experience, Ph. D. with 6+ years of pharma/biotech experience, Experience with single-cell sequencing, Bioinformatic QC experience, Translational genomics experience, Familiarity with NDALA submission requirements, Experience overseeing CRO bioanalytical activities", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Bioanalysis Laboratory supports AstraZeneca R&D China by generating quality-compliant PK, PD, ADA, NAb, and biomarker data for cell therapy projects, biotherapeutic development and regulatory filing. The Associate Principal or Principal Bioanalysis Scientist is responsible for: * Leading clinical bioanalysis projects as principal investigator: development, qualification/validation, and implementation of PCR-based (VCN, RCL), LBA (ELISA, MSD)and flow cytometry assays in a GxP environment. * Managing in-house and outsourced bioanalytical studies in collaboration with internal teams and CROs. * Supporting lab management to optimize operations and expand bioanalytical capability. The job title and grade offered will be commensurate with the successful candidate's experience and qualifications **Typical Accountabilities** * Collaborate with US/UK bioanalytical teams for PK/IMG/PD/Biomarker assay transfer, troubleshooting, validation, sample testing, and reporting. * Design, execute, and review experiments for development and validation of ddPCR or qPCR (VCN, RCL), LBA (ELISA, MSD), and flow cytometry (absolute counting, immunophenotyping, receptor occupancy, functional assays) methods. * Review and approve sample analysis data, method validation protocols/reports, bioanalytical sample testing reports, NDA/BLA dossier sections, and SOPs in compliance with GLP/GCP requirements. * Mentor junior scientists on experiment planning, troubleshooting, and data interpretation. * Present results at team/department meetings; prepare controlled documents, study plans, reports, and regulatory submission contributions. * Manage resources and timelines to ensure on-schedule delivery. Essential * Degree in Biology, Biochemistry, Pharmacology, or related field. * Experience in pharmaceuticals or biotech. * Hands-on experience developing and validating LBA (ELISA, MSD), ddPCR/qPCR (VCN, RCL), and multi-parameter flow cytometry assays (cell counting, immunophenotyping, functional/intracellular staining) in a GxP environment. * Experience with bioanalytical method validation per ICH M10, FDA, and EMA guidelines. * Written and oral communication skills in English and Chinese. * Ability to manage multiple projects and meet timelines. Desirable * B.Sc. with 10+ years, M.Sc. with 8+ years, or Ph.D. with 6+ years of pharma/biotech experience. * Experience with single-cell sequencing, bioinformatic QC, or translational genomics is a plus. * Familiarity with NDA/BLA submission requirements. * Experience overseeing CRO bioanalytical activities (method transfer, audit support, data review). **Date Posted** 10-6月-2026 **Closing Date** 30-12月-2026 AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.", "summaryDescription" : "(Associate) Principal Bioanalysis Scientist at AstraZeneca. Skills: Bioanalysis, Assay development, GxP environment. Lead clinical bioanalysis projects. Develop PCR-based assays", "postedDate" : "2026-06-11T05:06:02.651", "createdAt" : "2026-06-12T05:06:02.636", "lastUpdated" : "2026-06-14T22:39:17.938", "ingestTimestamp" : "2026-06-12T05:06:02.636", "mongoId" : "6a2af78374d8ee00a073d64d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://astrazeneca.wd3.myworkdayjobs.com/Careers/job/Shanghai-JingAn-Office/XMLNAME--Associate--Principal-Bioanalysis-Scientist_R-254201", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Assay development", "Assay validation", "Sample testing", "Data review", "GLP/GCP compliance", "Mentoring", "Bioanalysis", "GxP environment", "Bioanalytical studies", "Lab management", "Method validation", "Regulatory filing", "Manage multiple projects", "Manage timelines", "Cell therapy projects", "Biotherapeutic development", "ICH M10 guidelines", "FDA guidelines", "EMA guidelines", "GLP", "GCP", "NDALA submission", "MSD" ], "skillCount" : 23, "jobCategory" : "engineering", "seniorityLevel" : "senior", "dataQualityScore" : 0.8888889, "_score" : 747.41675, "daysOld" : 3, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Biotechnology" }, { "id" : "69fe94ff4c40e2acd1121a1b", "title" : "Principal Applied Scientist, Automated Reasoning Group", "company" : "Amazon Development Center U.S., Inc.", "industry" : "Applied Science, Cloud Computing", "salary" : { "min" : 198900.0, "max" : 295900.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T04:31:43.125", "fingerprint" : "bd70313ba7287ab544965bc045c4f5100a7e8d3f757ef5c5680bd0cb2638eab4", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10414408/apply", "externalId" : "f61b56b1-d9fc-46bd-8fae-ab11b28b634c", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 6, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "O'Caml, Dafny, Haskell, Kotlin, Lean, Rust, Scala", "professionalSkills" : [ "Problem solving", "Scientific innovation", "Strategic problem solving", "Technical influence", "Strategic plans" ], "hardSkillsList" : [ "Automated reasoning", "Privacy", "Sovereignty" ], "softSkillsList" : [ "Mentoring" ], "hardSkills" : [ { "name" : "Automated reasoning", "level" : "intermediate" }, { "name" : "Privacy", "level" : "intermediate" }, { "name" : "Sovereignty", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "Automated reasoning, Privacy, Sovereignty", "majorSkillsList" : [ "Automated reasoning", "Privacy", "Sovereignty" ], "coreResponsibilities" : "Solve complex problems, Own strategic problem solving, Lead design for solutions, Lead implementation for solutions, Lead delivery for solutions, Provide cross-organizational technical influence, Develop strategic plans, Identify new solutions, Assist in career development, Mentor individuals, Mentor community", "teamCollaboration" : "Cross-organizational technical influence", "domainKnowledge" : "Automated reasoning; Privacy; Sovereignty; Security; Cloud computing", "domainList" : [ "automated-reasoning", "privacy", "sovereignty", "security", "cloud-computing" ], "domainSpecificKnowledge" : [ "Automated reasoning", "Privacy", "Sovereignty", "Security", "Cloud computing" ], "innovationCreativity" : "Scientific innovation", "problemSolvingSkills" : "Problem solving; Strategic problem solving", "outcomesObjectives" : "Long-term quantifiable impact", "qualificationsBasic" : "PhD in Computer Science, PhD in Mathematics, Experience in professional software development, Experience programming in O'Caml, Experience programming in Dafny, Experience programming in Haskell, Experience programming in Kotlin, Experience programming in Lean, Experience programming in Rust, Experience programming in Scala", "qualificationsPreferred" : "Deep understanding of security science, Deep understanding of privacy science, Deep understanding of sovereignty science, Experience distilling informal customer requirements, Experience dealing with ambiguity, Experience dealing with competing objectives, 6+ years experience leading scientists, 6+ years experience leading science teams, 6+ years experience leading science products", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. Basic Qualifications: - PhD in Computer Science, Mathematics, or a related technical field. - Experience in professional software development. - Experience programming in O'Caml, Dafny, Haskell, Kotlin, Lean, Rust, Scala or related language. Preferred Qualifications: - Deep understanding of the science underlying security, privacy, and sovereignty. - Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives. - 6+ years experience leading scientists, science teams, or science products in either academic or industrial setting. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, MA, BOSTON - 198,900.00 - 269,000.00 USD annually USA, MA, Boston - 198,900.00 - 269,000.00 USD annually USA, NY, New York City - 218,800.00 - 295,900.00 USD annually USA, NY, New york city - 218,800.00 - 295,900.00 USD annually USA, OR, PORTLAND - 198,900.00 - 269,000.00 USD annually USA, OR, Portland - 198,900.00 - 269,000.00 USD annually USA, TX, AUSTIN - 198,900.00 - 269,000.00 USD annually USA, TX, Austin - 198,900.00 - 269,000.00 USD annually USA, WA, SEATTLE - 198,900.00 - 269,000.00 USD annually USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually", "summaryDescription" : "Principal Applied Scientist, Automated Reasoning Group at Amazon Development Center U.S., Inc.. Skills: Automated reasoning, Privacy, Sovereignty. Solve complex problems. Own strategic problem solving", "postedDate" : "2026-06-13T15:01:16.636", "createdAt" : "2026-06-13T15:01:16.636", "lastUpdated" : "2026-06-15T04:31:43.125", "ingestTimestamp" : "2026-06-13T15:01:16.636", "mongoId" : "69fe94ff4c40e2acd1121a1b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10414408/apply", "salaryAnnualMin" : 198900, "salaryAnnualMax" : 295900, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Automated reasoning", "Privacy", "Sovereignty", "Mentoring", "Problem solving", "Scientific innovation", "Strategic problem solving", "Technical influence", "Strategic plans", "Security", "Cloud computing" ], "skillCount" : 11, "jobCategory" : "other", "dataQualityScore" : 1.0, "_score" : 744.8278, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "68c2e420f8b1b0376634c4da", "title" : "Principal Applied Scientist, AWS Agentic AI", "company" : "Amazon Development Center U.S., Inc.", "industry" : "Machine Learning Science, Applied Science, Cloud Computing", "salary" : { "min" : 179000.0, "max" : 309400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T02:22:46.044", "fingerprint" : "8f0187df86f43df38fa952b01ea9445da857b8a667c652e6d45dc05e058831d0", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3078193/apply", "externalId" : "18c18c46-a13a-40b3-bf50-33b33c88afd3", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 8, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Java, C++, Python, AI, Deep Learning, LLM, Graph learning, Static code analysis, Software engineering, NLP, NLU, Multi-modality models", "professionalSkills" : [ "Technology strategy", "Roadmap development", "Product development", "Prototype development", "Technology assessment" ], "hardSkillsList" : [ "Model building", "Deep learning", "LLM training", "Graph learning", "Static code analysis", "Software engineering" ], "softSkillsList" : [ "Mentoring" ], "hardSkills" : [ { "name" : "Model building", "level" : "intermediate" }, { "name" : "Deep learning", "level" : "intermediate" }, { "name" : "LLM training", "level" : "intermediate" }, { "name" : "Graph learning", "level" : "intermediate" }, { "name" : "Static code analysis", "level" : "intermediate" }, { "name" : "Software engineering", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "Agentic AI, Deep Learning, LLM, NLP/NLU", "majorSkillsList" : [ "Agentic AI", "Deep Learning", "LLM", "NLP/NLU" ], "coreResponsibilities" : "Develop breakthroughs in agentic architecture, Mentor and guide junior scientists, Develop technology strategy, Develop roadmap supporting product development, Develop prototypes for key technology, Oversee productization of prototype, Develop critical assessment for prototype, Write technical reports summarizing R&D progresses, Communicate R&D progresses with stakeholders", "domainKnowledge" : "Agentic AI; Natural Language Understanding; AI assisted code development; LLM training and fine-tuning; Applied Machine Learning; Conversational AI", "domainList" : [ "agentic-ai", "natural-language-understanding", "ai-assisted-code-development", "llm-training-and-fine-tuning", "applied-machine-learning", "conversational-ai" ], "domainSpecificKnowledge" : [ "Agentic AI", "Natural Language Understanding", "AI assisted code development", "LLM training and fine-tuning", "Applied Machine Learning", "Conversational AI" ], "documentationSkills" : "Technical reports", "innovationCreativity" : "Develop novel algorithms; Develop modeling techniques; Explore new technologies; Find creative solutions", "qualificationsBasic" : "PhD or Master's degree and 10+ years experience, 8+ years building models for business application, Experience in patents or publications, Experience programming in Java, C++, Python, Experience in AI, Deep Learning, LLM training, graph learning, static code analysis, software engineering", "qualificationsPreferred" : "Experience using Unix/Linux, Experience in professional software development", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "AWS Agentic AI is looking for a world-class Applied Scientist with a strong deep learning background to help build industry-leading Agentic AI (models, systems, and applications). Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Understanding (NLU), AI assisted code development, reasoning and planning with LLMs, LLM training and fine-tuning, and Applied Machine Learning (ML). As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in Agentic AI. Your work will directly impact millions of our customers in the form of products and services that make use AI technology. You will gain hands on experience with Amazon’s heterogeneous text, structured data sources, and large-scale computing resources to accelerate advances in language understanding. We are hiring in all areas of Agentic AI: NLP/NLU, Conversational AI, Reasoning and Planning, LLM model training, and application development. Key job responsibilities - Develop breakthroughs is agentic architecture in areas such as autonomy, self-validation, and continuous learning. - Mentor and guide junior scientists. - Develop technology strategy and roadmap supporting product development - Develop prototypes for key technology, oversee the productization of the prototype, and develop critical assessment for the prototype - Write technical reports summarizing R&D progresses and communicate such progresses with stakeholders About the team The Amazon Web Services (AWS) Agentic AI team uses generative AI and foundation models to advance application development. In the space of software development and life cycle management, we see the application of AI anywhere: from the IDE to web-based tools and services, AI helps engineers work many applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you. Basic Qualifications: - PhD, or Master's degree and 10+ years of CS, CE, ML or related field experience - 8+ years of building models for business application experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: AI (NLP or multi-modality models), Deep Learning, LLM model training, graph learning, static code analysis, software engineering. Preferred Qualifications: • Experience using Unix/Linux • Experience in professional software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Principal Applied Scientist, AWS Agentic AI at Amazon Development Center U.S., Inc.. Skills: Agentic AI, Deep Learning, LLM, NLP/NLU. Develop breakthroughs in agentic architecture. Mentor and guide junior scientists", "postedDate" : "2026-06-13T15:11:47.462", "createdAt" : "2026-06-13T15:11:47.462", "lastUpdated" : "2026-06-15T02:22:46.044", "ingestTimestamp" : "2026-06-13T15:11:47.462", "mongoId" : "68c2e420f8b1b0376634c4da", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3078193/apply", "salaryAnnualMin" : 179000, "salaryAnnualMax" : 309400, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Model building", "Deep learning", "LLM training", "Graph learning", "Static code analysis", "Software engineering", "Mentoring", "Agentic AI", "Deep Learning", "LLM", "NLP/NLU", "Technology strategy", "Roadmap development", "Product development", "Prototype development", "Technology assessment", "Natural Language Understanding", "AI assisted code development", "LLM training and fine-tuning", "Applied Machine Learning", "Conversational AI" ], "skillCount" : 21, "jobCategory" : "data", "dataQualityScore" : 1.0, "_score" : 739.12463, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a25145374d8ee00a00bb357", "title" : "Principal Applied Scientist, AWS Agentic AI", "company" : "Amazon Development Center U.S., Inc.", "industry" : "Applied Science, Cloud Computing", "salary" : { "min" : 218800.0, "max" : 295900.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "timestamp" : "2026-06-15T07:46:08.055", "fingerprint" : "a354eb18730e0915a334b9f95e73ad9e7db6bd2c555035ffcd69e1a001ba3164", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10441249/apply", "externalId" : "f62190a5-e1bd-4c29-bf61-f9b66904fe02", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, Machine Learning, Generative AI, Foundation models, LLMs, Computer vision, Agentic AI", "professionalSkills" : [ "Science leadership", "Research and development", "System architecture" ], "hardSkillsList" : [ "Model training", "Fine-tuning LLMs", "Multi-modal models", "Complex reasoning", "Workflow automation" ], "softSkillsList" : [ "Leadership", "Mentoring", "Strategic thinking" ], "hardSkills" : [ { "name" : "Model training", "level" : "intermediate" }, { "name" : "Fine-tuning LLMs", "level" : "intermediate" }, { "name" : "Multi-modal models", "level" : "intermediate" }, { "name" : "Complex reasoning", "level" : "intermediate" }, { "name" : "Workflow automation", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" }, { "name" : "Strategic thinking" } ], "majorSkills" : "Generative AI, Agentic AI, Foundation models, LLMs", "majorSkillsList" : [ "Generative AI", "Agentic AI", "Foundation models", "LLMs" ], "coreResponsibilities" : "Build multi-modal foundation models, Optimize multi-modal foundation models, Train state-of-the-art LLMs, Fine-tune state-of-the-art LLMs, Architect systems that scale efficiently", "teamCollaboration" : "Deep collaboration with engineering teams", "domainKnowledge" : "Enterprise AI; AI safety; Hallucination mitigation; Retrieval-augmented generation", "domainList" : [ "enterprise-ai", "ai-safety", "hallucination-mitigation", "retrieval-augmented-generation" ], "domainSpecificKnowledge" : [ "Enterprise AI", "AI safety", "Hallucination mitigation", "Retrieval-augmented generation" ], "communicationSkills" : "Communicate complex technical topics", "innovationCreativity" : "Hands-on innovation", "problemSolvingSkills" : "Complex reasoning", "outcomesObjectives" : "Enable intelligent agents; Automate multi-step workflows; Make enterprise users productive", "qualificationsBasic" : "Master's degree with 5+ years experience, Industry experience developing ML models, Experience with generative AI, Proven record of publications or patents, Proficiency in Python, Experience in NLP, LLMs, computer vision, or Agentic AI", "qualificationsPreferred" : "Experience applying generative AI to enterprise tasks, Experience applying generative AI to multi-modal tasks, Understanding of agentic architectures, Understanding of autonomous systems, Understanding of task orchestration, Hands-on experience with scalable ML infrastructure, Hands-on experience with distributed training, Hands-on experience with optimization of large models, Deep knowledge of AI safety, Deep knowledge of hallucination mitigation, Deep knowledge of retrieval-augmented generation, Experience mentoring junior scientists, Experience influencing cross-functional stakeholders, Ability to think strategically, Ability to communicate complex technical topics, Track record of shipping scientific innovations", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Amazon Web Services (AWS) is looking for a Principal Applied Scientist to join the Quick Science team. Quick is AWS’s enterprise generative AI assistant that helps users answer questions, summarize documents, generate content, take actions, and automate workflows using information across enterprise systems. As a key member of this team, you will lead research and development efforts in generative AI and Agentic AI to enable intelligent agents that perform complex reasoning, automate multi-step workflows, and make enterprise users significantly more productive. Key job responsibilities You’ll work on building and optimizing multi-modal foundation models, training and fine-tuning state-of-the-art LLMs, and architecting systems that scale efficiently across domains. This role blends science leadership, hands-on innovation, and deep collaboration with engineering teams to bring research into production. Basic Qualifications: - PhD in Machine Learning, Computer Science, Electrical Engineering, or a related technical field OR a Master’s degree with 5+ years of relevant industry or research experience. - Industry experience developing machine learning models for real-world applications. - Experience with generative AI, including model training or building systems with pre-trained foundation models. - Proven record of peer-reviewed publications or granted patents in AI/ML. - Proficiency in Python or similar programming languages. - Experience in at least one of the following areas: natural language processing (NLP), large language models (LLMs), computer vision, or Agentic AI. Preferred Qualifications: - Experience applying generative AI to enterprise or multi-modal tasks (e.g., code generation, document understanding, or task planning). - Strong understanding of agentic architectures, autonomous systems, or task orchestration. - Hands-on experience with scalable ML infrastructure, distributed training, or optimization of large models. - Deep knowledge of AI safety, hallucination mitigation, or retrieval-augmented generation (RAG). - Experience mentoring junior scientists and influencing cross-functional stakeholders. - Ability to think strategically and communicate complex technical topics to non-experts, including senior leadership. - Track record of shipping scientific innovations into customer-facing products at scale. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, Santa Clara - 228,700.00 - 309,400.00 USD annually USA, NY, New York - 218,800.00 - 295,900.00 USD annually USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually", "summaryDescription" : "Principal Applied Scientist, AWS Agentic AI at Amazon Development Center U.S., Inc.. Skills: Generative AI, Agentic AI, Foundation models, LLMs. Build multi-modal foundation models. Optimize multi-modal foundation models", "postedDate" : "2026-06-13T10:45:40.484", "createdAt" : "2026-06-13T10:45:40.484", "lastUpdated" : "2026-06-15T07:46:08.055", "ingestTimestamp" : "2026-06-13T10:45:40.484", "mongoId" : "6a25145374d8ee00a00bb357", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10441249/apply", "salaryAnnualMin" : 218800, "salaryAnnualMax" : 295900, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Model training", "Fine-tuning LLMs", "Multi-modal models", "Complex reasoning", "Workflow automation", "Leadership", "Mentoring", "Strategic thinking", "Generative AI", "Agentic AI", "Foundation models", "LLMs", "Science leadership", "Research and development", "System architecture", "Enterprise AI", "AI safety", "Hallucination mitigation", "Retrieval-augmented generation" ], "skillCount" : 19, "jobCategory" : "other", "dataQualityScore" : 1.0, "_score" : 733.7854, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "69fa14be4c40e2acd148dc37", "title" : "Principal Engineer, ML Engineering", "company" : "Amazon Development Center U.S., Inc.", "industry" : "Software Development, Cloud Computing", "salary" : { "min" : 200000.0, "max" : 270600.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Bellevue, Washington, USA", "locations" : [ "Bellevue, Washington, USA" ], "timestamp" : "2026-06-15T05:35:50.585", "fingerprint" : "f910bdd5d07b722f5f913f700be9bd6433cbf2d9f6ce4c4be8b2cf3675917d96", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10411392/apply", "externalId" : "188bb652-2565-4a5b-a1a5-4afe5b33bde1", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bellevue", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6144219,-122.1923370" } ], "locationText" : "Bellevue, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 10, "experienceMaxYears" : 99, "experienceLevel" : "Principal", "technicalSkills" : "ML Engineering, Applied AI, LLM, Generative AI", "professionalSkills" : [ "Systems thinking", "Technical strategy", "Science-engineering interface" ], "hardSkillsList" : [ "ML development platform", "Agentic AI development", "Model evaluation", "Model deployment", "Prompt optimization", "Model benchmarking", "Data quality evaluation", "Synthetic data generation" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "ML development platform", "level" : "intermediate" }, { "name" : "Agentic AI development", "level" : "intermediate" }, { "name" : "Model evaluation", "level" : "intermediate" }, { "name" : "Model deployment", "level" : "intermediate" }, { "name" : "Prompt optimization", "level" : "intermediate" }, { "name" : "Model benchmarking", "level" : "intermediate" }, { "name" : "Data quality evaluation", "level" : "intermediate" }, { "name" : "Synthetic data generation", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "ML Engineering, Agentic AI development, Model evaluation, Technical strategy", "majorSkillsList" : [ "ML Engineering", "Agentic AI development", "Model evaluation", "Technical strategy" ], "coreResponsibilities" : "Build production-grade 1P agents, Design evaluation frameworks, Create recommendation systems, Drive science-engineering interface, Translate research into production systems, Establish technical strategy, Prototype, scientists, Write production code, Review designs across multiple teams, Design agent architectures, Manage memory, Optimize prompts, Manage tool use, Orchestrate agentic systems, Own evaluation strategy, Develop LLM-as-Judge frameworks, Automate benchmarking, Assess model quality, Build ML-driven recommendation systems, Benchmark models, Select models, Deploy models, Customize models, Establish data quality pipelines, Generate synthetic data, Support model training, Support fine-tuning, Drive requirements, Develop technical roadmap, Translate research prototypes, Create engineering specifications, Define ML engineering strategy, Establish best practices, Mentor senior engineers, Conduct design reviews, Conduct technical deep-dives, Conduct bar-raising interviews, Present technical strategy, Present roadmap", "teamCollaboration" : "Cross-cutting leadership role; Work with science teams; Influence without authority; Work across multiple teams; Cross-organizational technical forums", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "AI Platforms; ML development platform; Agentic AI development; LLM-as-Judge; Model benchmarking; Synthetic data generation; Generative AI systems", "domainList" : [ "ai-platforms", "ml-development-platform", "agentic-ai-development", "llm-as-judge", "model-benchmarking", "synthetic-data-generation", "generative-ai-systems" ], "domainSpecificKnowledge" : [ "AI Platforms", "ML development platform", "Agentic AI development", "LLM-as-Judge", "Model benchmarking", "Synthetic data generation", "Generative AI systems" ], "communicationSkills" : "Present technical strategy; Present roadmap", "innovationCreativity" : "Translate innovative research", "problemSolvingSkills" : "Systems thinking", "outcomesObjectives" : "Deliver superior developer experiences", "qualificationsBasic" : "Experience in software development, Experience designing and shipping production-grade ML systems, Experience with model evaluation, Experience with recommendation systems, Demonstrated ability to work across multiple teams", "qualificationsPreferred" : "Master’s or PhD in Machine Learning, Experience building production LLM-powered agents, Experience with LLM-as-Judge, Experience with prompt engineering, Experience with synthetic data generation, Track record of driving science-engineering collaboration, Experience leading technical strategy, Publications, patents, or significant open-source contributions in ML/AI", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are looking for a Principal Engineer with deep ML engineering expertise to lead the ML and science engineering effort across the AI Platforms organization at AWS. This is a cross-cutting leadership role spanning the full breadth of our ML development platform: data preparation, model evaluation, model deployment and customization, and agentic AI development experience. In this role, you will be responsible for building production-grade 1P agents, designing comprehensive evaluation frameworks (including LLM-as-Judge), creating recommendation systems for model benchmarking and selection, and driving the science-engineering interface to deliver superior developer experiences at AWS scale. You will work closely with world-class science teams to translate innovative research into production systems and establish the technical strategy for ML engineering across the organization. You are not just an architect — you are a hands-on builder who can prototype alongside scientists, write production code, and review designs across multiple teams. You bring a rare combination of ML depth, systems thinking, and the ability to influence without authority at a global scale. Key job responsibilities • Design and build production-grade 1P agent architectures including memory management, prompt optimization, tool use, and agentic orchestration systems • Define and own the evaluation strategy for AI Platforms, including LLM-as-Judge frameworks, automated benchmarking, and model quality assessment pipelines • Build ML-driven recommendation systems for model benchmarking, selection, deployment, and customization from Model Hub • Establish data quality evaluation pipelines and synthetic data generation infrastructure to support model training and fine-tuning at scale • Drive requirements and technical roadmap with the science team; translate research prototypes into engineering specifications and production systems • Define the ML engineering technical strategy across AI Platforms, establishing best practices for agent development, model evaluation, and science-to-production pipelines • Mentor senior engineers across the organization; conduct design reviews, technical deep-dives, and bar-raising interviews • Present technical strategy and roadmap to VP-level stakeholders; represent AI Platforms ML engineering in cross-organizational technical forums Basic Qualifications: • Experience in software development with a significant focus on ML engineering or applied AI systems • Experience designing and shipping production-grade ML systems or AI agents that operate at scale (not just prototype or research systems) • Experience with model evaluation, benchmarking, or quality assessment of ML/AI systems in a production environment • Experience with recommendation systems, retrieval systems, or similar ML systems running in production • Demonstrated ability to work across multiple teams as a technical leader, influencer, or architect Preferred Qualifications: • Master’s or PhD in Machine Learning, Artificial Intelligence, Computer Science, or a related quantitative field • Experience building production LLM-powered agents including memory management, prompt optimization, tool use, and multi-step reasoning • Experience with LLM-as-Judge, automated evaluation methodologies, or building evaluation infrastructure for generative AI systems • Experience with prompt engineering and prompt optimization at scale (beyond single-model, to fleet-scale optimization) • Experience with synthetic data generation, data quality evaluation, or data labeling pipelines for ML model training • Track record of driving science-engineering collaboration: working with research scientists, interpreting research outputs, and translating findings into production systems • Experience leading technical strategy across multiple engineering teams or sub-organizations • Publications, patents, or significant open-source contributions in ML/AI (NeurIPS, ICML, ICLR, KDD, RecSys, EMNLP, ACL, or equivalent venues preferred) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, BELLEVUE - 200,100.00 - 270,600.00 USD annually", "summaryDescription" : "Principal Engineer, ML Engineering at Amazon Development Center U.S., Inc.. Skills: ML Engineering, Agentic AI development, Model evaluation, Technical strategy. Build production-grade 1P agents. Design evaluation frameworks", "postedDate" : "2026-06-13T14:07:40.070", "createdAt" : "2026-06-13T14:07:40.070", "lastUpdated" : "2026-06-15T05:35:50.585", "ingestTimestamp" : "2026-06-13T14:07:40.070", "mongoId" : "69fa14be4c40e2acd148dc37", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10411392/apply", "salaryAnnualMin" : 200000, "salaryAnnualMax" : 270600, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "ML development platform", "Agentic AI development", "Model evaluation", "Model deployment", "Prompt optimization", "Model benchmarking", "Data quality evaluation", "Synthetic data generation", "Leadership", "Mentoring", "ML Engineering", "Technical strategy", "Systems thinking", "Science-engineering interface", "Roadmap planning", "AI Platforms", "LLM-as-Judge", "Generative AI systems" ], "skillCount" : 18, "jobCategory" : "engineering", "dataQualityScore" : 1.0, "_score" : 732.34424, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2ac0ed74d8ee00a06f29d1", "title" : "Principal Scientist", "company" : "Bristol Myers Squibb", "industry" : "Healthcare", "salary" : { "min" : 149390.0, "max" : 181023.0, "currency" : "USD", "frequency" : "yearly" }, "location" : "United States of America", "locations" : [ "United States of America" ], "timestamp" : "2026-06-14T15:49:55.571", "fingerprint" : "8ecd52c0836775602e950395250e78e9fb2b33a0866f1e8cc6d568372e3a2b79", "source" : "workday", "language" : "en", "applyUrl" : "https://bristolmyerssquibb.wd5.myworkdayjobs.com/BMS/job/San-Diego---CA---US/Principal-Scientist_R1603281", "externalId" : "R1603281", "industryFunction" : { }, "locationPoint" : "51.43667,5.97917", "structuredLocations" : [ { "city" : "San Diego", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "32.7174202,-117.1627720" } ], "locationText" : "San Diego, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "Biochemistry, Enzymology, TR-FRET, AlphaScreen, DSF, SPR, ITC, CETSA", "professionalSkills" : [ "Scientific leadership", "Program strategy", "Portfolio objectives" ], "hardSkillsList" : [ "Biochemical assays", "Biophysical assays", "Small molecule discovery", "Assay development", "Data analysis", "Structure activity relationships" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Biochemical assays", "level" : "intermediate" }, { "name" : "Biophysical assays", "level" : "intermediate" }, { "name" : "Small molecule discovery", "level" : "intermediate" }, { "name" : "Assay development", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Structure activity relationships", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Biochemical assays, Biophysical assays, Small molecule discovery, Targeted protein degradation", "majorSkillsList" : [ "Biochemical assays", "Biophysical assays", "Small molecule discovery", "Targeted protein degradation" ], "coreResponsibilities" : "Design biochemical and biophysical assays, Conduct biochemical and biophysical assays, Evaluate small-molecule affinity, Evaluate mechanism of action, Evaluate structure activity relationships, Provide strategic insight into program support, Ensure robust solutions for assay development, Ensure innovative solutions for assay development, Develop suitable assays for hit triage, Develop assays for SAR support, Develop assays for MOA study, Drive scientific innovation, Identify new assay technologies, Advance new assay technologies, Identify new experimental approaches, Advance new experimental approaches, Provide technical leadership, Provide scientific leadership, Solve complex assay challenges, Improve assay robustness, Improve assay reproducibility, Improve assay throughput, Improve data quality, Contribute to regulatory documentation, Contribute to scientific documentation, Serve as scientific partner, Shape program strategy, Advance portfolio objectives, Mentor junior scientists, Develop junior scientists, Foster scientific excellence, Foster collaboration, Foster laboratory culture", "teamCollaboration" : "Multidisciplinary environment; Cross-functional teams; Medicinal chemistry; Structural biology; Cell biology; Pharmacology; Project leadership; External project teams; Outside collaborators; Commercial vendors", "domainKnowledge" : "Targeted protein degradation; Induced proximity modalities; Small molecule discovery; Biochemical assays; Biophysical assays; Assay development; Proximity-based assays; High throughput screening", "domainList" : [ "targeted-protein-degradation", "induced-proximity-modalities", "small-molecule-discovery", "biochemical-assays", "biophysical-assays", "assay-development", "proximity-based-assays", "high-throughput-screening" ], "domainSpecificKnowledge" : [ "Targeted protein degradation", "Induced proximity modalities", "Small molecule discovery", "Biochemical assays", "Biophysical assays", "Assay development", "Proximity-based assays", "High throughput screening" ], "toolProficiency" : [ "High throughput screening" ], "communicationSkills" : "Convey complex scientific results", "documentationSkills" : "Investigator brochures; IND-enabling materials; Project deliverables", "innovationCreativity" : "Drive scientific innovation; New assay technologies; New experimental approaches", "problemSolvingSkills" : "Problem solving skills; Solve complex assay challenges", "qualificationsBasic" : "Bachelor's Degree + 8+ years experience, Master's Degree + 6+ years experience, PhD + 4+ years experience, Track record on drug discovery programs, Expertise in biochemical/biophysical assay design, Problem solving skills, Data analysis and management experience, Experience applying modern technologies, Experience applying automation, Proficiency in biochemical assay development, Proficiency in proximity-based assays, Proficiency in biophysical assays", "qualificationsPreferred" : "Experience in targeted protein degradation, Experience in induced-proximity space, Supervisory experience, Team-building skills, Ability to manage external project teams, Ability to manage outside collaborators, Ability to manage commercial vendors", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "**Working with Us** Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible. Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: [careers.bms.com/working-with-us](https://careers.bms.com/working-with-us). **The Lead Discovery and Optimization Group in San Diego** focuses on delivering novel therapeutics for disease intervention by harnessing E3 ubiquitin ligases for targeted protein degradation and other induced-proximity modalities. We are seeking a highly motivated **Biochemist** with a strong scientific background and expertise in the discovery and characterization of small molecules. The successful candidate will work collaboratively in a multidisciplinary environment to develop and execute biochemical and biophysical assays in support of small molecule discovery and preclinical development. **Key Responsibilities** * Design and conduct biochemical and biophysical assays to evaluate small-molecule affinity, mechanism of action, and structure activity relationships across discovery programs. * Bring strategic insight into program support and ensuring robust and innovative solutions and approaches towards the development of suitable assays for hit triage, SAR support, and MOA study. * Drive scientific innovation in targeted protein degradation, induced proximity, and high throughput screening platforms by identifying and advancing new assay technologies and experimental approaches. * Provide technical and scientific leadership at the bench and in data analysis, solving complex assay challenges while improving assay robustness, reproducibility, throughput, and data quality across multiple programs in a fast-paced environment. * Contribute to regulatory and scientific documentation, including investigator brochures, IND-enabling materials, and other key project deliverables, as appropriate. * Serve as a key scientific partner to cross-functional teams, including medicinal chemistry, structural biology, cell biology, pharmacology, and project leadership, to shape program strategy and advance portfolio objectives. * Mentor and develop junior scientists, fostering scientific excellence, collaboration, and a strong laboratory culture. **Required Qualifications** * Bachelor's Degree + 8+ years of academic/industry experience OR Master's Degree + 6+ years of academic/industry experience OR PhD + 4+ years of academic/industry experience in biochemistry, enzymology, or a related scientific discipline. * A consistent track record of impact on drug discovery programs through the judicious use of science and technology. * Strong expertise in biochemical and biophysical assay design, problem solving skills, data analysis and management, along with experience applying modern technologies and automation. * Experience in drug discovery in the targeted protein degradation and/or induced-proximity space is highly preferred. * Proficiency in biochemical assay development including proximity-based assays (such as TR-FRET and AlphaScreen), and/or biophysical assays such as DSF, SPR, ITC, and CETSA. * Supervisory experience, strong team-building skills, and the ability to interact with and manage external project teams, outside collaborators, and/or commercial vendors are preferred. * Strong written and verbal communication skills with the ability to convey complex scientific results to a broad audience. #LI-Onsite _If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career._ ******Compensation Overview:****** San Diego - CA - US: $149,390 - $181,023 The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee’s work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience. Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit [ https://careers.bms.com/life-at-bms/.](https://careers.bms.com/life-at-bms/) Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include: * **Health Coverage:** Medical, pharmacy, dental, and vision care. * **Wellbeing Support:** Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP). * **Financial Well-being and Protection:** 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support. ** Work-life benefits include:** Paid Time Off * US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees) * Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays Based on eligibility*, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day. All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown. _***Eligibility Disclosure:**_T_ he summer hours program is for United States (U.S.) office-based employees due to the unique nature of their work. Summer hours are generally not available for field sales and manufacturing operations and may also be limited for the capability centers. Employees in remote-by-design or lab-based roles may be eligible for summer hours, depending on the nature of their work, and should discuss eligibility with their manager. Employees covered under a collective bargaining agreement should consult that document to determine if they are eligible. Contractors, leased workers and other service providers are not eligible to participate in the program._ **Uniquely Interesting Work, Life-changing Careers** With a single vision as inspiring as “Transforming patients’ lives through science™ ”, every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues. **On-site Protocol** BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role: Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function. **Supporting People with Disabilities** BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to [adastaffingsupport@bms.com](mailto:adastaffingsupport@bms.com). Visit [careers.bms.com/](https://careers.bms.com/eeo-accessibility)[eeo](https://careers.bms.com/eeo-accessibility)[-accessibility](https://careers.bms.com/eeo-accessibility) to access our complete Equal Employment Opportunity statement. **Candidate Rights** BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area. If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: [https://careers.bms.com/california-residents/](https://careers.bms.com/california-residents/) **Data Protection** We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at [https://careers.bms.com/fraud-protection](http://careers.bms.com/fraud-protection). Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations. If you believe that the job posting is missing information required by local law or incorrect in any way, please contact BMS at [TAEnablement@bms.com](mailto:TAEnablement@bms.com). Please provide the Job Title and Requisition number so we can review. Communications related to your application should not be sent to this email and you will not receive a response. Inquiries related to the status of your application should be directed to Chat with Ripley. R1603281 : Principal Scientist", "summaryDescription" : "Principal Scientist at Bristol Myers Squibb. Skills: Biochemical assays, Biophysical assays, Small molecule discovery, Targeted protein degradation. Design biochemical and biophysical assays. Conduct biochemical and biophysical assays", "postedDate" : "2026-06-09T03:25:19.476", "createdAt" : "2026-06-12T03:25:19.358", "lastUpdated" : "2026-06-14T15:49:55.571", "ingestTimestamp" : "2026-06-12T03:25:19.358", "mongoId" : "6a2ac0ed74d8ee00a06f29d1", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://bristolmyerssquibb.wd5.myworkdayjobs.com/BMS/job/San-Diego---CA---US/Principal-Scientist_R1603281", "salaryAnnualMin" : 149390, "salaryAnnualMax" : 181023, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Biochemical assays", "Biophysical assays", "Small molecule discovery", "Assay development", "Data analysis", "Structure activity relationships", "Leadership", "Mentoring", "Targeted protein degradation", "Scientific leadership", "Program strategy", "Portfolio objectives", "Induced proximity modalities", "Proximity-based assays", "High throughput screening" ], "skillCount" : 15, "jobCategory" : "engineering", "seniorityLevel" : "senior", "dataQualityScore" : 1.0, "_score" : 731.08856, "daysOld" : 5, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare" }, { "id" : "6a0de91358b93c861eb990aa", "title" : "CLINICAL OPEN HOUSE - CRYSTAL RIVER", "company" : "Tampa General Hospital", "industry" : "Healthcare", "salary" : { "min" : 45000.0, "max" : 65000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for entry-level healthcare roles in Crystal River, Florida, adjusted for industry and company size." }, "location" : "United States-Florida-Crystal River", "locations" : [ "United States-Florida-Crystal River", "
TGH Crystal River (TGHCR)
6201 N Suncoast Boulevard

Crystal River, 34428

" ], "certifications" : [ "Registered Nurse License Issued by Florida or Compact State", "Basic Life Support (BLS) through American Heart Association or American Red Cross", "Clinical Laboratory Technologist License Issued by Florida or Compact State", "Radiologic Technology", "American Registry of Radiologic Technologists (ARRT) (R - Radiography)", "American Registry of Radiologic Technologists (ARRT) (CT - Computerized Tomography)", "Basic Life Support (BLS) from American Heart Association or American Red Cross" ], "timestamp" : "2026-06-15T06:47:27.951", "fingerprint" : "14dadb25e0d8d1afe7d2cca7f5d77eef1b19b700dbebcf948d0c68bff59b72c5", "source" : "taleo", "language" : "en", "applyUrl" : "https://tas-tgh.taleo.net/careersection/ex/jobdetail.ftl?job=678893", "externalId" : "678893", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Crystal River", "state" : "Florida", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "28.9024790,-82.5926012" } ], "locationText" : "Crystal River, Florida, United States", "minimumEducation" : "Associate's", "professionalSkills" : [ "Clinical care", "Patient care" ], "hardSkillsList" : [ "Radiologic Technology", "Medical Laboratory Technology", "Computerized Tomography" ], "hardSkills" : [ { "name" : "Radiologic Technology", "level" : "intermediate" }, { "name" : "Medical Laboratory Technology", "level" : "intermediate" }, { "name" : "Computerized Tomography", "level" : "intermediate" } ], "majorSkills" : "Clinical care, Patient care", "majorSkillsList" : [ "Clinical care", "Patient care" ], "domainKnowledge" : "Emergency Department; ICU; OR; Med Surge; Cath Lab; PACU; Telemetry", "domainList" : [ "emergency-department", "icu", "or", "med-surge", "cath-lab", "pacu", "telemetry" ], "domainSpecificKnowledge" : [ "Emergency Department", "ICU", "OR", "Med Surge", "Cath Lab", "PACU", "Telemetry" ], "documentationSkills" : "Patient charting", "qualificationsBasic" : "Associate's degree Nursing, Registered Nurse License, Basic Life Support (BLS), Associate's degree Respiratory Therapy, Registered Respiratory Therapist, Certified Respiratory Therapist, Associate's Degree Medical Laboratory Technology, Bachelor's Degree Biology, Bachelor's Degree Chemistry, Clinical Laboratory Technologist License, Technical Program Radiologic Technology, Associate's Degree Imaging related field, General Radiographer, Nuclear Medicine Technologist, Radiation Therapy Technologist, American Registry of Radiologic Technologists (ARRT) (R - Radiography), American Registry of Radiologic Technologists (ARRT) (CT - Computerized Tomography)", "qualificationsPreferred" : "CT Technologist, Medical Laboratory Technologists", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Clinical Open House - Crystal River Tampa General Hospital Crystal River is seeking Clinical Nurses, Respiratory Therapists, Radiology Technologists, CT Technologists, Medical Laboratory Technologists and more to join our units throughout the hospital, including - Emergency Department, ICU, OR, Med Surge, Cath Lab, PACU, Telemetry, and more. Come meet our hiring managers in one of our series of sessions and learn more about the amazing opportunities at TGH to expand and grow your career. Tuesday June 16th, 2026 from 10:00am-2:00pm Interested? Follow these steps : 1. Apply here! Create your profile and apply to this job posting. 2. Our Talent Acquisition Team will reach out with an email invitation 3. Come prepared to shine! Interviews will take place at Tampa General Hospital Crystal River , 11537 W Emerald Oaks Drive, Crystal River, FL. Clinical Nurse Associate’s degree Nursing Registered Nurse License Issued by Florida or Compact State Basic Life Support (BLS) through American Heart Association or American Red Cross Respiratory Therapist Associate’s degree Respiratory Therapy Registered Respiratory Therapist Or Certified Respiratory Therapist Medical Laboratory Technologists Associate's Degree Medical Laboratory Technology or Bachelor's Degree Biology or Chemistry Clinical Laboratory Technologist License Issued by Florida or Compact State CT Technologist Technical Program Radiologic Technology or Associate's Degree Imaging related field such as Radiography, Nuclear Medicine, or Radiation Therapy General Radiographer, Nuclear Medicine Technologist, Radiation Therapy Technologist Issued by Florida or Compact State American Registry of Radiologic Technologists (ARRT) (R - Radiography) American Registry of Radiologic Technologists (ARRT) (CT - Computerized Tomography) Basic Life Support (BLS) from American Heart Association or American Red Cross Crystal River", "summaryDescription" : "CLINICAL OPEN HOUSE - CRYSTAL RIVER at Tampa General Hospital. Skills: Clinical care, Patient care", "createdAt" : "2026-06-14T02:02:40.197", "lastUpdated" : "2026-06-15T06:47:27.951", "ingestTimestamp" : "2026-06-14T02:02:40.197", "mongoId" : "6a0de91358b93c861eb990aa", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 45000, "salaryAnnualMax" : 65000, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Radiologic Technology", "Medical Laboratory Technology", "Computerized Tomography", "Clinical care", "Patient care", "Emergency Department", "ICU", "OR", "Med Surge", "Cath Lab", "PACU", "Telemetry", "Registered Nurse License Issued by Florida or Compact State", "Basic Life Support (BLS) through American Heart Association or American Red Cross", "Clinical Laboratory Technologist License Issued by Florida or Compact State", "American Registry of Radiologic Technologists (ARRT) (R - Radiography)", "American Registry of Radiologic Technologists (ARRT) (CT - Computerized Tomography)", "Basic Life Support (BLS) from American Heart Association or American Red Cross" ], "skillCount" : 18, "jobCategory" : "healthcare", "jobSubcategory" : "support", "seniorityLevel" : "Entry", "dataQualityScore" : 0.6666667, "_score" : 728.30035, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6a8a74d8ee00a090c85c", "title" : "Senior / Principal Scientist, ADC Conjugation Process Development", "company" : "Immunome, Inc.", "industry" : "Biotech", "salary" : { "min" : 146000.0, "max" : 188000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Bothell, Washington, United States", "locations" : [ "Bothell", "Washington", "United States" ], "timestamp" : "2026-06-16T01:27:46.638", "fingerprint" : "d2cc8a50652feedeac13c5d3a2129052957e3531e98df4a745b6b6a89ddb58b1", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/immunomeinc/jobs/5253227008", "externalId" : "5253227008", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bothell", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.7623204,-122.2054035" } ], "locationText" : "Bothell, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "rawDescription" : "Company Overview Immunome is a clinical-stage targeted oncology company committed to developing first-in-class and best-in-class targeted cancer therapies. We are advancing an innovative portfolio of therapeutics, supported by a leadership team with deep experience in the design, development, and commercialization of cutting-edge therapies, including antibody-drug conjugates. Our pipeline includes varegacestat, an investigational gamma secretase inhibitor for which an NDA has been submitted to the U. S. FDA; IM-1021, a clinical-stage ROR1 ADC; IM-3050, an IND-cleared FAP-targeted radiotherapy; and IM-1617, an IND-cleared solid tumor ADC. We are also advancing a broad portfolio of early-stage ADCs pursuing undisclosed solid tumor targets. Position Overview We are seeking an experienced and motivated Senior/Principal Scientist in ADC Conjugation Process Development to support our growing pipeline. This role will be responsible for the optimization of critical conjugation and purification process parameters for ADC Drug Substance (DS) Development. The preferred candidate will coordinate and execute strategies from milligram to multi-gram scales, including tox/GMP batches, while demonstrating practical expertise in different methodologies and purification strategies for clinical and commercial-stage ADC DS manufacturing. The ideal candidate will have experience with technology transfer, regulatory compliance, and coordination with CDMO partners at GMP manufacturing facilities. A strong working knowledge of different conjugation technologies and cytotoxic linker-payloads is essential, as is experience with standard analytical and characterization approaches used for both biologics and ADCs. Responsibilities Implement and execute ADC Conjugation Process Development (PD) strategies, including Design of Experiment (DOE) and One Factor at a Time (OFAT) approaches for critical reaction parameters. Oversee the progression of ADC batch sizes from milligram to >100 g scales to support not only PD optimization, but analytical and formulation development, DS/DP stability studies, and in vivo experiments (including critical GLP tox studies) for both IND- and BLA-stage activities. Lead the multi-gram scale purification optimization for both antibody intermediates and ADCs via ultrafiltration/diafiltration (UF/DF), and, if required, preparative chromatography or other approaches. Fulfill role as ADC DS subject matter expert (SME) on both internal cross-functional CMC teams and for external CDMO partners to ensure alignment on ADC program goals, deliverables, and objectives. Occasional travel to advise and oversee Development and GMP manufacturing processes will be expected. Prepare essential documentation (SOPs, protocols, and reports) to support tech transfers, GMP activities, and regulatory submissions for clinical development and commercialization. Stay current with emerging trends, innovations, and regulatory requirements for ADC DS, integrating necessary or potentially beneficial features into our internal company strategies and workflows. Lead/support authoring and reviewing of relevant module 3 sections of regulatory submissions (IND, IMPD, BLA, etc.), along with, if necessary, responding to information requests and interfacing with global health authorities. Qualifications A Bachelors, Masters, or Ph. D. degree in Chemistry, Chemical/Biochemical Engineering, Biotechnology, or a related field. A minimum of 5 years of biotech/biopharma industry experience with a Ph.D., 8 years with a Master’s, or 10 years with a Bachelor’s degree. An ADC or Conjugation/Bioconjugation Process Development focus is required. Demonstrated success with the development and scale-up of different ADC conjugation technologies and strategies, including a proven ability to work with a variety of different small molecule linker-payloads and antibody intermediate materials. Expected expertise in relevant laboratory operations and equipment necessary for successful execution of development activities. Prior experience with tech transfer, external CDMO engagement (encompassing both Development and GMP manufacturing activities), and internal coordination with relevant cross-functional teams. Knowledge and Skills A strong understanding of the common conjugation, purification, analytical, and characterization approaches used for ADCs, with a solid foundation in overcoming some of the challenges encountered in these workflows. Expertise in tangential flow filtration (TFF) at the multi-gram scale for the efficient removal of unreacted linker-payloads and to provide a stable ADC DS formulation. Good working knowledge of standard analytical and characterization techniques used for ADCs including, but not limited to, SEC, HIC, and RP U/HPLC chromatographic methods in addition to LC-MS, icIEF, and CE-SDS strategies for biomolecules and related conjugates. Knowledge of GMP standards and regulatory guidelines, with experience supporting IND, INDa, and BLA submissions. The ability to manage multiple projects simultaneously while being able to prioritize and balance hands-on tasks with strategic responsibilities. Exceptional communication skills, with an emphasis on effective collaborations with both internal stakeholders and external partners. Washington State Pay Range $146,000—$188,000 USD E/E/O Immunome, Inc. is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. E-Verify Immunome, Inc. is a participant in E-Verify. Please review the following notices: E-Verify Participation Poster | Right to Work Poster (English) | Right to Work Poster (Spanish).", "summaryDescription" : "Senior / Principal Scientist, ADC Conjugation Process Development at Immunome, Inc.", "postedDate" : "2026-06-14T20:01:49.008", "createdAt" : "2026-06-14T20:01:49.008", "lastUpdated" : "2026-06-16T01:27:46.638", "ingestTimestamp" : "2026-06-14T20:01:49.008", "mongoId" : "6a2c6a8a74d8ee00a090c85c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 146000, "salaryAnnualMax" : 188000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 724.2425, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.98 }, { "id" : "69164db070f0b99d586f3693", "title" : "Principal Applied Scientist, Artificial General Intelligence", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, Artificial Intelligence", "salary" : { "min" : 179000.0, "max" : 309400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Sunnyvale, California, USA", "locations" : [ "Sunnyvale, California, USA" ], "timestamp" : "2026-06-15T00:12:36.857", "fingerprint" : "7dea8d2de937da682823d635f00681c3c662c9d5cf4a119167f1c46d5d163229", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3120830/apply", "externalId" : "707427f7-01f9-4573-b172-1cbe2f7b627c", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Sunnyvale", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.3688301,-122.0363490" } ], "locationText" : "Sunnyvale, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, Java, C++, Artificial Intelligence, Natural Language Processing, Machine Learning, Generative AI", "professionalSkills" : [ "Algorithm design", "Model structure", "Scientific reviews", "Experimental design", "Research procedures", "Full-cycle development" ], "hardSkillsList" : [ "ML techniques", "Rigorous experiments", "Scalable science", "Engineering solutions" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "ML techniques", "level" : "intermediate" }, { "name" : "Rigorous experiments", "level" : "intermediate" }, { "name" : "Scalable science", "level" : "intermediate" }, { "name" : "Engineering solutions", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Artificial General Intelligence, Generative AI, Machine Learning", "majorSkillsList" : [ "Artificial General Intelligence", "Generative AI", "Machine Learning" ], "coreResponsibilities" : "Define research directions, Adopt new ML techniques, Invent new ML techniques, Conduct rigorous experiments, Publish research results, Translate research into practice, Develop long-term strategies, Persuade teams to adopt strategies, Propose goals, Deliver on goals, Participate in organizational planning, Participate in hiring, Participate in mentorship, Participate in leadership development, Build scalable science solutions, Build scalable engineering solutions, Serve as scientific resource, Lead scientific reviews, Scrutinize experimental design, Scrutinize modeling, Scrutinize verification, Scrutinize research procedures, Probe assumptions, Illuminate pitfalls, Foster shared understanding, Align teams toward strategies, Educate scientific community, Keep community updated, Guide career growth, Develop scientists, Develop leads, Drive development of GenAI, Handle Amazon-scale use cases, Impact customer experiences, Conceive solutions, Design solutions, Implement solutions, Test solutions, Document solutions, Deliver solutions, Maintain solutions", "teamCollaboration" : "Cross-functional projects; Organizational planning", "domainKnowledge" : "Artificial Intelligence; Natural Language Processing; Computational Cognitive Science; Generative AI", "domainList" : [ "artificial-intelligence", "natural-language-processing", "computational-cognitive-science", "generative-ai" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Natural Language Processing", "Computational Cognitive Science", "Generative AI" ], "communicationSkills" : "Written communication; Spoken communication; Executive presentations", "documentationSkills" : "Documentation", "innovationCreativity" : "Invent new ML techniques", "problemSolvingSkills" : "Decompose complex problems; Troubleshoot issues", "outcomesObjectives" : "Impact customer experiences", "qualificationsBasic" : "5+ years ML experience, Graduate degree in AI, NLP, ML, or computational cognitive science, 7+ years academic and research experience, Publication record, Track record of project delivery, Programming in Java, C++, Python, Excellent communication skills", "qualificationsPreferred" : "PhD in AI, NLP, ML, or computational cognitive science, 10+ years academic and research experience, First author research, Functional thought leader, Experience influencing executive level, Experience mentoring research scientists, Distilling customer requirements, Excellent communication skills", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "As a Principal Scientist in the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modeling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically exceptional with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). Basic Qualifications: - 5+ years of practical work applying ML to solve complex problems experience - Graduate degree in with specialization in artificial intelligence, natural language processing, machine learning, or computational cognitive science - 7+ years of combined academic and research experience - Strong publication record in top-tier journals and conferences - Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements - Experience programming in Java, C++, Python or related language - Excellent written and spoken communication skills Preferred Qualifications: - PhD with specialization in Artificial Intelligence, Natural Language Processing, Machine Learning, or Computational Cognitive Science - 10+ years of combined academic and research experience - First author research on scaling laws, evaluation metrics, data mixture optimization, data efficiency, or neural network architectures in top-tier journals and conferences - Functional thought leader and sought after for key tech decisions - Experience influencing decisions at an executive level - Experience mentoring and training the research scientist community on complex technical issues - Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives - Excellent written and spoken communication skills with successful delivery to customers Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Principal Applied Scientist, Artificial General Intelligence at Amazon.com Services LLC. Skills: Artificial General Intelligence, Generative AI, Machine Learning. Define research directions. Adopt new ML techniques", "postedDate" : "2026-06-13T00:20:37.410", "createdAt" : "2026-06-13T00:20:37.410", "lastUpdated" : "2026-06-15T00:12:36.857", "ingestTimestamp" : "2026-06-13T00:20:37.410", "mongoId" : "69164db070f0b99d586f3693", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3120830/apply", "salaryAnnualMin" : 179000, "salaryAnnualMax" : 309400, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "ML techniques", "Rigorous experiments", "Scalable science", "Engineering solutions", "Leadership", "Mentoring", "Artificial General Intelligence", "Generative AI", "Machine Learning", "Algorithm design", "Model structure", "Scientific reviews", "Experimental design", "Research procedures", "Full-cycle development", "Artificial Intelligence", "Natural Language Processing", "Computational Cognitive Science" ], "skillCount" : 18, "jobCategory" : "data", "dataQualityScore" : 1.0, "_score" : 723.88556, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "69fda4e34c40e2acd1b9974a", "title" : "Principal Applied Scientist, Sponsored Products and Brands", "company" : "Amazon.com Services LLC", "industry" : "Applied Science, Advertising", "salary" : { "min" : 228700.0, "max" : 309400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Palo Alto, California, USA", "locations" : [ "Palo Alto, California, USA" ], "timestamp" : "2026-06-15T06:34:06.169", "fingerprint" : "e48365b86c403c615a246893e6332d35e97417f8226f9370a866d50001d31b19", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10413683/apply", "externalId" : "486289d8-494c-400a-8e28-f2291fbb0c9e", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Palo Alto", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.4443293,-122.1598465" } ], "locationText" : "Palo Alto, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI/ML, GenAI, LLM, Analytics, Database, Storage", "professionalSkills" : [ "Product sense", "Science vision", "Execution" ], "hardSkillsList" : [ "ML", "LLM", "GenAI models" ], "hardSkills" : [ { "name" : "ML", "level" : "intermediate" }, { "name" : "LLM", "level" : "intermediate" }, { "name" : "GenAI models", "level" : "intermediate" } ], "majorSkills" : "Gen AI, Applied Science, Product Development", "majorSkillsList" : [ "Gen AI", "Applied Science", "Product Development" ], "coreResponsibilities" : "Manage projects at all stages, Tackle challenging problems, Coordinate high profile projects, Ensure customer and business goals are met, Interface across product, science, and engineering teams, Drive mechanisms for team efficiency, Operate with high degree of autonomy, Prioritize projects and features, Plan projects and features, Manage partners, Track external commitments, Recommend alternative technical approaches, Partner with product, science, and engineering teams, Meet timelines, Role model use of GenAI, Design Gen AI solutions, Implement Gen AI solutions, Create effective ad campaigns, Improve overall experience", "teamCollaboration" : "Cross functional teams; Ads and Retail organizations", "projectManagementSkills" : [ "Project management", "Roadmap strategy", "Roadmap definition" ], "domainKnowledge" : "Generative AI; Advertising landscape; Brand advertising", "domainList" : [ "generative-ai", "advertising-landscape", "brand-advertising" ], "domainSpecificKnowledge" : [ "Generative AI", "Advertising landscape", "Brand advertising" ], "innovationCreativity" : "Invent new product experiences", "qualificationsBasic" : "PhD in Electrical Engineering, Computer Science, Mathematics, or related technical field, 7+ years working with Data & AI technologies, 7+ years designing or architecting systems, 7+ years working directly with engineering teams, 7+ years technical product or program management experience", "qualificationsPreferred" : "8+ years hands-on managing complex technology projects, Experience managing projects across cross functional teams", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Sponsored Brands team at Amazon is building the next generation of brand advertising products and platforms for advertisers using Gen AI. This role presents an opportunity to join us at the ground floor of this transformation, which is a core part of Amazon's overall business strategy. You will be the Gen AI applied science leader that will determine what products and ads show up in the most critical ad placements across Amazon. You'll have opportunities to deliver at the highest technical level, working with science, product, engineering, and UX, all directly connected to a marketplace of supply and demand. In this highly visible role, you'll collaborate across multiple stakeholders within Ads and Retail. We are seeking a Gen AI Applied Science inventor who has strong product sense, with a proven track record with hands on science vision and execution while building high impact products from the ground up. you will have the opportunity to apply your deep subject matter expertise in the area of ML, LLM and GenAI models. You will invent new product experiences that enable novel advertiser and shopper experiences. This role will work on bringing state-of-the-art GenAI models to production. You will define the long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of applied scientists and engineers. Key job responsibilities You will play a pivotal role in managing projects at all stages: inception, design, development, deployment and subsequent improvements. You will tackle challenging problems and coordinate high profile projects across multiple teams to ensure customer and business goals are met. You will interface across product, science, and engineering teams within the advertising and retail organizations. You will drive mechanisms that allow the team to move quickly and deliver strong results. You will operate with a high degree of autonomy and efficiency. You'll be responsible for project management - prioritize, plan projects and features, manage partners, and track external commitments. You will recommend alternative technical approaches and partner with product, science, and engineering teams to meet timelines. You will actively role model the use of GenAI to make the team more efficient. About the team We are on a mission to make Amazon the best in class destination for shoppers to discover, engage, and purchase relevant products, from brands that are relevant to them. In this role, you will design and implement Gen AI solutions that help millions of advertisers create more effective ad campaigns with intelligent recommendations, while improving the overall experience at Amazon's global scale. Our team invents, defines, and delivers advertising products that drive brand discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon Store businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, fast-paced, and collaborative team with an entrepreneurial spirit. Basic Qualifications: - PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field - 7+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience - Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems - 7+ years of working directly with engineering teams experience - 7+ years of technical product or program management experience - Experience owning/driving roadmap strategy and definition Preferred Qualifications: - 8+ years of hands-on work managing complex technology projects experience - Experience managing projects across cross functional teams, building sustainable processes and coordinating release schedules Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, Palo Alto - 228,700.00 - 309,400.00 USD annually USA, NY, New York - 218,800.00 - 295,900.00 USD annually USA, WA, SEATTLE - 198,900.00 - 269,000.00 USD annually", "summaryDescription" : "Principal Applied Scientist, Sponsored Products and Brands at Amazon.com Services LLC. Skills: Gen AI, Applied Science, Product Development. Manage projects at all stages. Tackle challenging problems", "postedDate" : "2026-06-13T15:11:57.473", "createdAt" : "2026-06-13T15:11:57.473", "lastUpdated" : "2026-06-15T06:34:06.169", "ingestTimestamp" : "2026-06-13T15:11:57.473", "mongoId" : "69fda4e34c40e2acd1b9974a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10413683/apply", "salaryAnnualMin" : 228700, "salaryAnnualMax" : 309400, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "ML", "LLM", "GenAI models", "Gen AI", "Applied Science", "Product Development", "Product sense", "Science vision", "Execution", "Project management", "Roadmap strategy", "Roadmap definition", "Generative AI", "Advertising landscape", "Brand advertising" ], "skillCount" : 15, "jobCategory" : "other", "dataQualityScore" : 1.0, "_score" : 720.3449, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Advertising" }, { "id" : "6a2aa59674d8ee00a06b59ef", "title" : "Principal Data Scientist - Agent Builder", "company" : "Elastic", "industry" : "Technology", "salary" : { "min" : 140000.0, "max" : 210000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "The estimated salary is based on the market baseline for a Principal Data Scientist in the Technology industry in the United Kingdom, with adjustments for executive seniority and company size." }, "location" : "United Kingdom", "locations" : [ "United Kingdom" ], "timestamp" : "2026-06-14T22:14:33.989", "fingerprint" : "d6a33fc94bf0dc8857ef6f299d2c7327c50f0478b13eaf6cf26eb536b4df0044", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/referralsuseonly/jobs/7988143", "externalId" : "7988143", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United Kingdom", "continent" : "eu", "workMode" : "onsite" } ], "locationText" : "United Kingdom", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, PyTorch, Transformers, Pandas, Elasticsearch, ES|QL, RAG, Vector search, NLP, IR", "professionalSkills" : [ "Technical strategy", "Product strategy", "Experiment design", "Evaluation methodology", "Statistical rigor", "LLM systems" ], "hardSkillsList" : [ "Semantic search", "Ranking", "Retrieval systems", "Model comparison", "Offline metrics", "Online experimentation", "LLM-as-judge", "Groundedness", "Citation quality", "Sparse retrieval", "Dense retrieval", "Query understanding", "Context enrichment", "Re-ranking approaches", "Cost/latency trade-offs" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Semantic search", "level" : "intermediate" }, { "name" : "Ranking", "level" : "intermediate" }, { "name" : "Retrieval systems", "level" : "intermediate" }, { "name" : "Model comparison", "level" : "intermediate" }, { "name" : "Offline metrics", "level" : "intermediate" }, { "name" : "Online experimentation", "level" : "intermediate" }, { "name" : "LLM-as-judge", "level" : "intermediate" }, { "name" : "Groundedness", "level" : "intermediate" }, { "name" : "Citation quality", "level" : "intermediate" }, { "name" : "Sparse retrieval", "level" : "intermediate" }, { "name" : "Dense retrieval", "level" : "intermediate" }, { "name" : "Query understanding", "level" : "intermediate" }, { "name" : "Context enrichment", "level" : "intermediate" }, { "name" : "Re-ranking approaches", "level" : "intermediate" }, { "name" : "Cost/latency trade-offs", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Data Science, Machine Learning, AI, LLM", "majorSkillsList" : [ "Data Science", "Machine Learning", "AI", "LLM" ], "coreResponsibilities" : "Define evaluation strategy, Lead design of quality metrics, Build retrieval approaches, Compare retrieval approaches, Guide improvements across retrieval, Turn experimental results into decisions, Partner with engineering to productionize pipelines, Influence roadmap, Mentor data scientists, Mentor engineers, Share outcomes through docs, Share outcomes through notebooks, Share outcomes through PRs, Share outcomes through dashboards, Share outcomes through proposals, Share outcomes through reviews", "teamCollaboration" : "Backend engineering; Product; UX; Data scientists; Engineering teams; Leadership audiences", "domainKnowledge" : "Conversational AI; Agentic platform; RAG; Vector search; Search AI; Distributed data systems", "domainList" : [ "conversational-ai", "agentic-platform", "rag", "vector-search", "search-ai", "distributed-data-systems" ], "domainSpecificKnowledge" : [ "Conversational AI", "Agentic platform", "RAG", "Vector search", "Search AI", "Distributed data systems" ], "toolProficiency" : [ "PyTorch", "Transformers", "Pandas", "Notebooks", "Elasticsearch" ], "communicationSkills" : "Explain complex trade-offs", "documentationSkills" : "Clear docs; Technical proposals", "innovationCreativity" : "Frontier problems; Prototype", "problemSolvingSkills" : "Ambiguous problems; Cutting-edge problems; Ambiguous domains; Emerging domains", "outcomesObjectives" : "Improve chat quality; Measurable product improvements; Ship improvements customers can feel", "qualificationsBasic" : "8+ years of applied DS/ML experience, Deep expertise in IR, NLP, ranking, semantic search, RAG, or LLM-powered product experiences, Track record defining and leading evaluation for production AI/ML systems, Hands-on ability with Python, Hands-on ability with PyTorch/Transformers, Hands-on ability with Pandas, Hands-on ability with notebooks, Hands-on ability with reproducible experiments, Hands-on ability with versioned datasets, Hands-on ability with clean, reviewable code, Understanding of retrieval systems, Experience collaborating closely with engineering teams, Practical Elasticsearch experience, Excellent written communication, Excellent verbal communication", "qualificationsPreferred" : "PhD preferred, Specific ML framework experience, Cloud platform certs, ES|QL familiarity", "workSiteFlexibility" : "Flexible", "rawDescription" : "Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Search Conversational Experiences team builds Elastic’s new conversational and agentic platform that lets customers chat with their own data in Elasticsearch. We build the core quality layer for RAG, agents and tools, retrieval and citations, streaming, memory, and the evaluation signals that turn open-ended questions into grounded, reliable answers. As a Principal Data Scientist, you will help set the technical direction for how we evaluate, improve, and scale chat quality across Elastic’s agentic platform. You will define the evaluation strategy that guides product decisions, including which models we standardize on, how we route requests across agents, which tools we enable and when, and how we tailor agents to different Elastic use cases in search and beyond. You will work closely with backend engineering, product, UX, and other data scientists to turn ambiguous, cutting-edge problems into measurable product improvements. You’ll help lead work on frontier problems such as folding RAG and vector search into an agent’s knowledge base, dynamically enriching model context to improve groundedness, shaping reasoning strategies and tool-selection policies, lighting up agent-driven visualizations on top of Elasticsearch data, and exploring multimodality where it can create meaningful user value. This is an applied leadership role: you will prototype, evaluate, influence roadmap direction, and help teams ship improvements that customers can feel. What You Will Be Doing Define the evaluation strategy for conversational and agentic search, including offline and online evaluation, golden datasets, rubrics, LLM-as-judge calibration, groundedness and citation checks, and A/B testing. Lead the design of quality metrics and decision frameworks for RAG, agents, tools, model selection, agent routing, prompt behavior, and cost/latency trade-offs. Build, compare, and guide improvements across retrieval and re-ranking approaches, including sparse and dense retrieval, vector search, query understanding, semantic rewrites, and context enrichment. Turn experimental results into product and business decisions: which models to use, how to route requests efficiently, which tools should be exposed, and how agents should be customized for different Elastic use cases. Partner with engineering to productionize evaluation pipelines, telemetry, dashboards, CI guardrails, and regression detection for chat quality, helpfulness, dedication, latency, and cost. Influence the roadmap by identifying the highest-leverage quality gaps, proposing practical solutions, and communicating trade-offs clearly to product, engineering, and leadership. Mentor other data scientists and engineers in experiment design, evaluation methodology, statistical rigor, and practical approaches to improving LLM-powered systems. Share outcomes through clear docs, notebooks, PRs, dashboards, technical proposals, and cross-functional reviews. What You Bring 8+ years of applied DS/ML experience, with deep expertise in IR, NLP, ranking, semantic search, RAG, or LLM-powered product experiences. Strong track record defining and leading evaluation for production AI/ML systems, including offline metrics, online experimentation, LLM-as-judge approaches, groundedness, citation quality, and model comparison. Experience influencing product and technical strategy through data, especially in ambiguous or emerging domains where the “right” metric or approach is not obvious at the start. Hands-on ability with Python, PyTorch/Transformers, Pandas, notebooks, reproducible experiments, versioned datasets, and clean, reviewable code. Strong understanding of retrieval systems, including dense and sparse retrieval, re-ranking, vector search, query understanding, and evaluation metrics such as nDCG, MRR, Recall@k, precision,and latency/cost trade-offs. Experience collaborating closely with engineering teams to move from prototype to production, including telemetry design, dashboards, CI guardrails, and quality regression tracking. Practical Elasticsearch experience, or experience with similar search and distributed data systems. ES|QL familiarity is a plus. Excellent written and verbal communication, with the ability to explain complex scientific and technical trade-offs to engineering, product, design, and leadership audiences. A collaborative, low-ego style and a strong ability to mentor, raise standards, and develop transparency for others in a distributed team. Additional Information - We Take Care of Our People As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do. We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do. Competitive pay based on the work you do here and not your previous salary Health coverage for you and your family in many locations Ability to craft your calendar with flexible locations and schedules for many roles Generous number of vacation days each year Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service Up to 40 hours each year to use toward volunteer projects you love Embracing parenthood with minimum of 16 weeks of parental leave Different people approach problems differently. We need that. Elastic is an equal opportunity/affirmative action employer committed to diversity, equity, and inclusion. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation. We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email candidate_accessibility@elastic.co We will reply to your request within 24 business hours of submission. Applicants have rights under Federal Employment Laws, view posters linked below: Family and Medical Leave Act (FMLA) Poster; Pay Transparency Nondiscrimination Provision Poster; Employee Polygraph Protection Act (EPPA) Poster and Know Your Rights (Poster) Elasticsearch develops and distributes encryption software and technology that is subject to U. S. export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Russia, Syria, the Crimea Region of Ukraine, the Donetsk People’s Republic (“DNR”), and the Luhansk People’s Republic (“LNR”). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic. Please see here for our Privacy Statement.", "summaryDescription" : "Principal Data Scientist - Agent Builder at Elastic. Skills: Data Science, Machine Learning, AI, LLM. Define evaluation strategy. Lead design of quality metrics", "postedDate" : "2026-06-11T20:17:17.906", "createdAt" : "2026-06-11T20:17:17.906", "lastUpdated" : "2026-06-14T22:14:33.989", "ingestTimestamp" : "2026-06-11T20:17:17.906", "mongoId" : "6a2aa59674d8ee00a06b59ef", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Semantic search", "Ranking", "Retrieval systems", "Model comparison", "Offline metrics", "Online experimentation", "LLM-as-judge", "Groundedness", "Citation quality", "Sparse retrieval", "Dense retrieval", "Query understanding", "Context enrichment", "Re-ranking approaches", "Cost/latency trade-offs", "Leadership", "Mentoring", "Data Science", "Machine Learning", "AI", "LLM", "Technical strategy", "Product strategy", "Experiment design", "Evaluation methodology", "Statistical rigor", "LLM systems", "Conversational AI", "Agentic platform", "RAG", "Vector search", "Search AI", "Distributed data systems", "PyTorch", "Transformers", "Pandas", "Notebooks", "Elasticsearch" ], "skillCount" : 38, "jobCategory" : "other", "jobSubcategory" : "enterprise-search---workchat", "dataQualityScore" : 0.8888889, "_score" : 717.9627, "daysOld" : 3, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology" }, { "id" : "6a2a67d674d8ee00a0631878", "title" : "Principal Data Scientist - Gen AI", "company" : "Xometry", "salary" : { "min" : 225000.0, "max" : 325000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Principal Data Scientist in the United States, adjusted for executive seniority, the manufacturing industry, and the North Bethesda city tier." }, "location" : "North Bethesda, Maryland, United States", "locations" : [ "North Bethesda", "Maryland", "United States", "Boston", "Massachusetts", "United States" ], "timestamp" : "2026-06-14T21:29:36.253", "fingerprint" : "1b07923e591d2bb3836a19206aec99dba04530e786634d56f278d85ac02acb76", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/xometry/jobs/5160150007", "externalId" : "5160150007", "structuredLocations" : [ { "city" : "North Bethesda", "state" : "Maryland", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "39.0406500,-77.1233873" }, { "city" : "Waltham", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "42.3762385,-71.2355644" } ], "locationText" : "North Bethesda, Maryland, United States; Waltham, Massachusetts, United States", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, PyTorch, TensorFlow, pandas, numpy, Generative AI, Large Language Models, LLMs, Transformers, GPT, VLMs", "professionalSkills" : [ "Technical leadership", "Strategic planning", "Roadmap development", "Business value delivery", "Scientific direction" ], "hardSkillsList" : [ "Machine learning", "Statistical methodology", "Multimodal document understanding", "Structured data extraction", "Text processing", "Image processing", "Generative modeling", "Scientific computing" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Statistical methodology", "level" : "intermediate" }, { "name" : "Multimodal document understanding", "level" : "intermediate" }, { "name" : "Structured data extraction", "level" : "intermediate" }, { "name" : "Text processing", "level" : "intermediate" }, { "name" : "Image processing", "level" : "intermediate" }, { "name" : "Generative modeling", "level" : "intermediate" }, { "name" : "Scientific computing", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Generative AI, Machine learning, Large Language Models, Data extraction", "majorSkillsList" : [ "Generative AI", "Machine learning", "Large Language Models", "Data extraction" ], "coreResponsibilities" : "Own and drive a technical roadmap, Lead strategic planning, Lead roadmap development, Develop generative AI models, Deploy generative AI models, Develop large language models, Deploy large language models, Extract structured data, Lead exploration of data processing solutions, Lead development of data processing solutions, Train generative models, Fine-tune generative models, Train language models, Fine-tune language models", "teamCollaboration" : "Cross-functional ML initiatives; Cross-functional AI initiatives", "projectManagementSkills" : [ "Roadmap development" ], "domainKnowledge" : "Multimodal document processing; Technical drawings; Purchasing orders; Generative modeling", "domainList" : [ "multimodal-document-processing", "technical-drawings", "purchasing-orders", "generative-modeling" ], "domainSpecificKnowledge" : [ "Multimodal document processing", "Technical drawings", "Purchasing orders", "Generative modeling" ], "toolProficiency" : [ "PyTorch", "TensorFlow", "pandas", "numpy" ], "innovationCreativity" : "Innovation", "outcomesObjectives" : "Enhance Xometry's service offerings", "qualificationsBasic" : "Bachelor's degree required, 6+ years of relevant experience, Expert-level proficiency in Python, Proficient in Python, Proficient in PyTorch, Proficient in TensorFlow, Proficient in pandas, Proficient in numpy, Recognized depth in machine learning, Recognized depth in statistical methodology, Expertise in large-scale language models, Expertise in vision models, Experience with multimodal data processing, background in probability, background in statistics, background in optimization techniques", "qualificationsPreferred" : "Advanced degree (M. S. or PhD) preferred, PhD preferred, Experience with Transformers, Experience with GPT, Experience with VLMs, Experience combining text, image, and 3D data", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry’s digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. About the Role Xometry is seeking an exceptional Principal Data Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine-tuning generative and language models, multimodal document understanding, and structured data extraction. This role will also serve as a key technical leader for high-stakes strategic initiatives, including the DFM AI + IQE integration with Siemens. In this role, you will serve as a technical leader, owning a 12 month technical roadmap, driving large-scale cross-functional ML and AI initiatives, and setting the long-term scientific direction for AI-driven solutions that enhance Xometry's service offerings. This role requires a hybrid schedule (3 days a week) at our Waltham, MA or North Bethesda, MD office location. How You'll Contribute Technical Vision and Roadmap: Own and drive an 18-24 month technical roadmap that balances innovation with disciplined business value delivery. Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry’s business objectives. Generative AI Development: Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents. Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models. Technical Leadership or a PhD with 6-plus years of relevant experience. A bachelor’s degree is required, but an advanced degree (M. S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred. Technical Mastery: Expert-level proficiency in Python and advanced scientific computing, with a track record of building large-scale, production-grade ML systems. Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy. AI/ML Expertise: Recognized depth in machine learning and statistical methodology. Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs) and experience with multimodal data processing (e.g., combining text, image, and 3D data). Strong background in probability, statistics, and optimization techniques relevant to generative modeling. Strategic life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more. #LI-Hybrid Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.", "summaryDescription" : "Principal Data Scientist - Gen AI at Xometry. Skills: Generative AI, Machine learning, Large Language Models, Data extraction. Own and drive a technical roadmap. Lead strategic planning", "postedDate" : "2026-06-11T21:16:48.234", "createdAt" : "2026-06-11T21:16:48.234", "lastUpdated" : "2026-06-14T21:29:36.253", "ingestTimestamp" : "2026-06-11T21:16:48.234", "mongoId" : "6a2a67d674d8ee00a0631878", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 225000, "salaryAnnualMax" : 325000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Machine learning", "Statistical methodology", "Multimodal document understanding", "Structured data extraction", "Text processing", "Image processing", "Generative modeling", "Scientific computing", "Leadership", "Generative AI", "Large Language Models", "Data extraction", "Technical leadership", "Strategic planning", "Roadmap development", "Business value delivery", "Scientific direction", "Multimodal document processing", "Technical drawings", "Purchasing orders", "PyTorch", "TensorFlow", "pandas", "numpy" ], "skillCount" : 24, "jobCategory" : "engineering", "jobSubcategory" : "data-science-and-engineering-", "dataQualityScore" : 0.8888889, "_score" : 716.4373, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2a737c74d8ee00a064fdf5", "title" : "Principal Scientist, Machine Learning - Biomolecules", "company" : "Flagship Pioneering, Inc.", "industry" : "Biotechnology", "salary" : { "min" : 208000.0, "max" : 286000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Pioneering Intelligence", "locations" : [ "Pioneering Intelligence" ], "timestamp" : "2026-06-14T22:16:25.313", "fingerprint" : "8027560736bfa85a5fac81ee7a15a430e078c18181393963acda7504701a8a3e", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://boards.greenhouse.io/flagshippioneeringinc/jobs/8584537002?gh_jid=8584537002", "externalId" : "8584537002", "industryFunction" : { }, "locationText" : "Pioneering Intelligence", "experienceMinYears" : 10, "experienceMaxYears" : 99, "experienceLevel" : "Principal", "technicalSkills" : "Python, JAX, TensorFlow, PyTorch, LLM, DVC, LakeFS, MLflow, gnina, DiffDock, Airflow, Prefect, Argo, Redshift, Snowflake, FAISS, pgvector, FastAPI, Streamlit, Gradio", "professionalSkills" : [ "Program Leadership", "Technical Ownership", "Method Development", "Pipeline Development", "LLM Agent Workflow", "Benchmarking", "Scaling", "Systems Design", "Drug Design", "Molecular Modeling", "Systems Biology", "Protein Design", "Scientific Workflows", "Venture Portfolios", "Company Origination" ], "hardSkillsList" : [ "Computational Projects", "AI Strategy", "Model Development", "Data Contracts", "Experiment Tracking", "Pose Quality Metrics", "Workflow Orchestration", "Vector Search" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Computational Projects", "level" : "intermediate" }, { "name" : "AI Strategy", "level" : "intermediate" }, { "name" : "Model Development", "level" : "intermediate" }, { "name" : "Data Contracts", "level" : "intermediate" }, { "name" : "Experiment Tracking", "level" : "intermediate" }, { "name" : "Pose Quality Metrics", "level" : "intermediate" }, { "name" : "Workflow Orchestration", "level" : "intermediate" }, { "name" : "Vector Search", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Machine Learning, Computational Projects, LLM Agents, Scientific Workflows", "majorSkillsList" : [ "Machine Learning", "Computational Projects", "LLM Agents", "Scientific Workflows" ], "coreResponsibilities" : "Lead development of AI/ML projects, Implement AI/ML projects, Control AI/ML projects, Report on AI/ML projects, Oversee method development, Oversee pipeline development, Oversee LLM agent/workflow drive benchmarking, Oversee scaling of AI/ML projects, Oversee implementation into production systems, Promote operational excellence in AI projects, Educate cross-functional collaborators, Manage internal scientists/engineers, Coordinate internal scientists/engineers, Manage external scientists/engineers, Coordinate external scientists/engineers, Manage cross-functional project teams, Coordinate cross-functional project teams, Mentor early support, Support recruiting, Support interview processes, Plan surface risks, Plan surface tradeoffs, Propose new development strategies, Identify opportunities for PI, Identify opportunities for venture portfolios, Act as recognized subject matter expert, Actively participate in scientific conferences, Actively participate in meetings, Adapt complex findings, Present complex findings", "teamCollaboration" : "Cross-functional contributors; Cross-functional collaborators; Cross-functional project teams; Venture teams; External partners", "projectManagementSkills" : [ "Program Leadership", "Strategic Plans" ], "domainKnowledge" : "Biomolecules; Drug Design; Molecular Modeling; Systems Biology; Protein Design; Mass Spectrometry; Cheminformatics; Biophysics; Agentic Automation", "domainList" : [ "biomolecules", "drug-design", "molecular-modeling", "systems-biology", "protein-design", "mass-spectrometry", "cheminformatics", "biophysics", "agentic-automation" ], "domainSpecificKnowledge" : [ "Biomolecules", "Drug Design", "Molecular Modeling", "Systems Biology", "Protein Design", "Mass Spectrometry", "Cheminformatics", "Biophysics", "Agentic Automation" ], "toolProficiency" : [ "DVC", "LakeFS", "MLflow", "gnina", "DiffDock", "Airflow", "Prefect", "Argo", "FAISS", "pgvector", "FastAPI", "Streamlit", "Gradio" ], "communicationSkills" : "Present complex findings", "continuousLearning" : "Stretch across domains; Present at conferences", "innovationCreativity" : "Sustained independent thought; Creativity; Propose new development strategies; Identify opportunities", "problemSolvingSkills" : "Deep Diver; Risk Assessment; Tradeoff Analysis", "outcomesObjectives" : "Create a portfolio of AI-first companies; Transform breakthrough ideas; Accelerate fundamental research", "qualificationsBasic" : "5+ years industry AI/ML experience, Experience driving results through teams, Sustained independent thought and creativity, Leadership and contribution to decision making, Depth across modern ML frameworks, Depth across version databases, Depth across deep learning, Depth across relevant informatics software", "qualificationsPreferred" : "Breadth across protein modeling/design, Breadth across proteomics/mass spec, Breadth across cheminformatics/docking/ADMET, Breadth across biophysics/MD, Breadth across LLM/agentic automation, MLOps expertise, Experience mentoring early hires, Experience acting as interim Head of ML, Experience contributing to hiring plans, Experience contributing to interview processes", "rawDescription" : "ABOUT PIONEERING INTELLIGENCE Pioneering Intelligence builds on Flagship Pioneering’s legacy of founding cutting-edge science and computational ventures, harnessing recent advances in AI, machine learning, and data to accelerate fundamental research and create a portfolio of AI-first companies. As part of Flagship’s integrated model of science, entrepreneurship, and capital, it transforms breakthrough ideas into world-changing companies, elevating the AI advances happening across the ecosystem in human health, sustainability, and beyond. THE ROLE We are seeking a Principal Scientist (Embedded ML/Computational) to lead multiple AI/ML or computational projects across early stage ventures, as a part of Flagship’s company origination process. You will define and deliver pragmatic AI strategies, oversee method and platform development (e.g., systems design, drug design, molecular modeling, systems biology, protein design, LLM/agentic workflows), and ensure rigor in model development, benchmarking, scaling, and reporting. You will manage cross functional contributors as applicable, influence company direction, and represent PI to venture teams and external partners. The ideal candidate is a self-directed serial deep diver - someone who can move from protein design one week to mass spec or docking pipelines the next and then spin up LLM based agents that automate scientific workflows. KEY RESPONSIBILITIES Program Leadership: Lead development, implementation, control, and reporting of several AI/ML or computational projects within assigned ventures in line with broader strategic plans of PI and Flagship, budgets, and timelines. Technical Ownership: Take a specialized technical role on project teams to oversee method development, pipeline development, and LLM based agent/workflow design; drive benchmarking, scaling, and implementation into production grade systems. Best Practices: promote operational excellence in AI projects by educating cross-functional collaborators. Team Leadership: Manage and/or coordinate internal and external scientists/engineers and crossfunctional project teams as applicable; mentor early hires; support recruiting and interview. Planning surface risks and tradeoffs early with clear options. Landscape synthesize concepts to propose new development strategies and identify opportunities for PI and venture portfolios. Representation act as a recognized subject matter expert; actively participate in scientific conferences and meetings. Communication adapt and present complex findings to diverse audiences to support meaningful interpretation and action. PROFESSIONAL EXPERIENCE industry AI/ML experience preferred. Experience driving results directly or indirectly through teams of engineers/scientists in dynamic, fastpaced, entrepreneurial, and technical environments. Clear evidence of sustained independent thought and creativity driving high impact, cross disciplinary AI/ML projects. Successful track record of leadership and contribution to decision making on progression of AI/ML models within projects or programs. Depth across multiple core tools and concepts, including Python; modern ML frameworks (PyTorch or JAX/TensorFlow); version control; databases; deep learning architectures; and relevant informatics software. Consistent record of outstanding performance reflected in publications, patents, or high impact internal reports where applicable Preferred Qualifications Breadth across domains such as protein modeling/design, proteomics/mass spec, cheminformatics/docking/ADMET, biophysics/MD, and LLM/agentic automation. MLOps expertise: data contracts and lineage (e.g., DVC/LakeFS), experiment tracking (MLflow/W docking rescoring (e.g., gnina, DiffDock) and pose quality metrics. Workflow orchestration (Airflow/Prefect/Argo), data warehouses (Redshift/Snowflake), vector search (FAISS/pgvector), and lightweight internal tools (FastAPI, Streamlit/Gradio). Experience mentoring early hires, acting as interim Head of ML, and contributing to hiring plans and interview processes at startups. WHY PIONEERING INTELLIGENCE Operate at the frontier: Build and deploy AI/ML that directly powers discovery and decision making across multiple new ventures. Own the full stack: From scoping and data contracts to models, MLOps, and internal UIs—ship endtoend systems that scientists rely on daily. Compound impact: Convert one off wins into shared libraries and templates adopted across the PI portfolio. Work with founders: Partner closely with venture leadership and PI platform engineers; influence strategy through hands on delivery. Grow fast: Stretch across domains, take on situational leadership, present at conferences, and help shape first ML teams. ABOUT FLAGSHIP PIONEERING: Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com. At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact. We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship. Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto. #LI-MB1 The salary range for this role is $208,000 - $286,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Pioneering Intelligence currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Pioneering Intelligence’s good faith estimate as of the date of publication and may be modified in the future. Privacy Notice for Applicants: When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.", "summaryDescription" : "Principal Scientist, Machine Learning - Biomolecules at Flagship Pioneering, Inc.. Skills: Machine Learning, Computational Projects, LLM Agents, Scientific Workflows. Lead development of AI/ML projects. Implement AI/ML projects", "postedDate" : "2026-06-11T21:27:46.546", "createdAt" : "2026-06-11T21:27:46.546", "lastUpdated" : "2026-06-14T22:16:25.313", "ingestTimestamp" : "2026-06-11T21:27:46.546", "mongoId" : "6a2a737c74d8ee00a064fdf5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 208000, "salaryAnnualMax" : 286000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Computational Projects", "AI Strategy", "Model Development", "Data Contracts", "Experiment Tracking", "Pose Quality Metrics", "Workflow Orchestration", "Vector Search", "Leadership", "Mentoring", "Machine Learning", "LLM Agents", "Scientific Workflows", "Program Leadership", "Technical Ownership", "Method Development", "Pipeline Development", "LLM Agent Workflow", "Benchmarking", "Scaling", "Systems Design", "Drug Design", "Molecular Modeling", "Systems Biology", "Protein Design", "Venture Portfolios", "Company Origination", "Strategic Plans", "Biomolecules", "Mass Spectrometry", "Cheminformatics", "Biophysics", "Agentic Automation", "DVC", "LakeFS", "MLflow", "gnina", "DiffDock", "Airflow", "Prefect", "Argo", "FAISS", "pgvector", "FastAPI", "Streamlit", "Gradio" ], "skillCount" : 46, "jobCategory" : "other", "jobSubcategory" : "artificial-intelligence", "dataQualityScore" : 0.8888889, "_score" : 715.1052, "daysOld" : 3, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Biotechnology" }, { "id" : "6a2a5b9174d8ee00a0610fbf", "title" : "Principal Data Scientist, Health Informatics", "company" : "Waymark", "industry" : "Healthcare", "salary" : { "min" : 220000.0, "max" : 350000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline data for Principal Data Scientist in the US Healthcare industry, adjusted for executive seniority and remote work." }, "location" : "US - Remote ", "locations" : [ "US - Remote" ], "timestamp" : "2026-06-13T10:48:39.355", "fingerprint" : "708199bccfbcbfec0d73600f8b8da1c14f508d5c3da73ffa649e4b7bf35fd618", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/waymark/jobs/4703537005", "externalId" : "4703537005", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, FHIR, HL7, C-CDA, EHR, ADT, ML, AI, LLM", "professionalSkills" : [ "Health economics", "Clinical data", "ML/AI", "Health informatics", "Data quality", "Data normalization", "Clinical validity", "Risk adjustment", "Utilization measurement", "Cost attribution", "Quasi-experimental evaluation", "Outcomes measurement" ], "hardSkillsList" : [ "Clinical terminologies", "Value set curation", "Model validation", "Model deployment", "ML pipelines", "Model versioning", "Reproducible workflows" ], "hardSkills" : [ { "name" : "Clinical terminologies", "level" : "intermediate" }, { "name" : "Value set curation", "level" : "intermediate" }, { "name" : "Model validation", "level" : "intermediate" }, { "name" : "Model deployment", "level" : "intermediate" }, { "name" : "ML pipelines", "level" : "intermediate" }, { "name" : "Model versioning", "level" : "intermediate" }, { "name" : "Reproducible workflows", "level" : "intermediate" } ], "majorSkills" : "Clinical data, Applied ML/AI, Health economics", "majorSkillsList" : [ "Clinical data", "Applied ML/AI", "Health economics" ], "coreResponsibilities" : "Define standards for clinical data, Structure clinical data, Normalize clinical data, Validate clinical data, Build production ML/AI models, Validate production ML/AI models, Deploy production ML/AI models, Translate data into evidence, Advance machine and AI products, Set standards for team, Mentor junior data scientists", "teamCollaboration" : "Data science stakeholders; Engineering stakeholders; Product stakeholders; Clinical stakeholders", "projectManagementSkills" : [ "Project ownership" ], "domainKnowledge" : "Claims data; EHR data; ADT data; Clinical terminologies; ICD-10; SNOMED CT; LOINC; RxNorm; CPT/HCPCS; Healthcare data standards; Health economics; Outcomes methods; CMS reporting; NCQA reporting; MCO reporting; Medicaid populations; Dual-eligible populations", "domainList" : [ "claims-data", "ehr-data", "adt-data", "clinical-terminologies", "icd-10", "snomed-ct", "loinc", "rxnorm", "cpt-hcpcs", "healthcare-data-standards", "health-economics", "outcomes-methods", "cms-reporting", "ncqa-reporting", "mco-reporting", "medicaid-populations", "dual-eligible-populations" ], "domainSpecificKnowledge" : [ "Claims data", "EHR data", "ADT data", "Clinical terminologies", "ICD-10", "SNOMED CT", "LOINC", "RxNorm", "CPT/HCPCS", "Healthcare data standards", "Health economics", "Outcomes methods", "CMS reporting", "NCQA reporting", "MCO reporting", "Medicaid populations", "Dual-eligible populations" ], "toolProficiency" : [ "Epic", "Cerner", "Athena", "MLflow", "SageMaker Pipelines" ], "innovationCreativity" : "Generative AI products", "outcomesObjectives" : "Drive better care; Translate clinical data into predictions; Translate clinical data into outcomes evidence", "qualificationsBasic" : "Master's degree in Data Science, Biostatistics, Health Informatics, Computer Science, or a related field, 7-8+ years of hands-on experience in Python, Healthcare Data Expertise, Standards Fluency", "qualificationsPreferred" : "PhD in health informatics, statistics, data science, or computer science, Experience integrating EHR/HIE data via TEFCA, CommonWell, or comparable networks, Health Economics & Outcomes Methods experience, Prior experience building on Medicaid or dual-eligible populations, Peer-reviewed publications in healthcare ML, AI, biostatistics, or health economics", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Principal Data Scientist, Health Informatics Waymark is a team of healthcare providers, technologists, and builders whose mission is to bring the best healthcare to people with Medicaid benefits. Guided by the communities we serve, we bring support and technology-enabled care to help primary care providers keep Medicaid patients healthy. We are building the tools and designing an approach to enable care to reach the patients who can benefit most. Our core values embody the essence of what makes Waymark a unique team today, and what we look for, nurture, and sustain as a team. We are bold builders, believing that the greatest challenges in care delivery can be solved when we harness the power of community and technology. We are humble learners, seeking feedback and perspectives different from our own, and welcome challenges to our conclusions. We experiment to improve, actively seeking data to inform decisions and assess our own performance. We act with focused urgency, our commitment to our mission drives us to tirelessly pursue results. About This Role Waymark is seeking a Principal Data Scientist to own clinical data as a first-class input to modeling and to bring senior ML/AI and health economics judgment to our core data science products. As Waymark scales across health plan and health system partners, clinical data quality directly determines model accuracy. We need a senior owner accountable for data quality, normalization, and clinical validity across claims, EHR, and ADT. This role sits at the intersection of clinical data expertise, applied ML/AI, and health economics methods. You will own the clinical data strategy that enables our modeling, defining how EHR and ADT data, across formats including FHIR, HL7v2, and C-CDA, should be structured, normalized, and validated as modeling inputs, with hands-on fluency in how these systems are structured and what the data actually represents clinically. You will build and ship production models that advance our existing machine learning and generative AI products, and operate as a senior technical leader, making architectural trade-offs, aligning data science, engineering, product, and clinical stakeholders, and raising the technical bar of the team. This is a highly versatile role for someone who is equally fluent in clinical terminologies and production ML, and who can move work from prototype to deployment with rigor and speed. Responsibilities Own clinical data quality across claims, EHR, and ADT: Define standards for how clinical data is structured, normalized, and validated as modeling inputs across payer claims (medical, pharmacy, eligibility), EHR data (Epic, Cerner, Athena), and real-time ADT feeds. Bring deep familiarity with EHR data formats (FHIR, HL7, C-CDA) and how data from systems like Epic, Cerner, and Athena maps to clinical reality. Hold the bar for clinical accuracy and completeness across all three sources. Build and ship production ML/AI models: Develop, validate, and deploy risk stratification, care gap prediction, treatment effect estimation, and LLM/foundation model applications — with rigor around leakage, calibration, fairness, and clinical face validity. Apply health economics and outcomes methods: Translate raw clinical and claims data into decision-grade evidence through risk adjustment, utilization measurement, cost attribution, quasi-experimental evaluation, and outcomes measurement aligned with CMS, NCQA, and MCO reporting standards. Advance machine and AI products: Bring senior modeling judgment to the product roadmap, owning the clinical and methodological soundness of what ships. Set standards and mentor: Make architectural trade-offs, drive alignment across data science, engineering, product, and clinical stakeholders, and mentor junior data scientists to raise the technical bar of the team. Minimum Qualifications Healthcare Data Expertise: Deep, hands-on fluency with claims, EHR, and ADT data, and strong command of clinical terminologies (ICD-10, SNOMED CT, LOINC, RxNorm, CPT/HCPCS) and value set curation. Standards Fluency: Working experience with healthcare data standards and exchange formats — FHIR, HL7v2, and C-CDA. Education: Master's degree in Data Science, Biostatistics, Health Informatics, Computer Science, or a related field. Python Proficiency: 7-8+ years of hands-on experience in Python, including data science and ML libraries. Applied ML/AI Experience: Demonstrated ability to build, validate, and deploy production ML models on healthcare data, with end-to-end ownership from development through deployment and maintenance in a live environment. Experience with ML pipelines, model versioning, and reproducible workflows at scale. Project Ownership: Proven ability to manage complex technical projects independently, align multiple stakeholders, and deliver on timelines. Preferred Qualifications PhD in health informatics, statistics, data science, or computer science Experience integrating EHR/HIE data via TEFCA, CommonWell, or comparable networks. Health Economics & Outcomes Methods: Experience with risk adjustment, utilization and cost measurement, and quasi-experimental evaluation. Familiarity with MLOps best practices including experiment tracking and model registry (e. g. MLflow), CI/CD for ML pipelines, feature stores, and workflow orchestration tools such as SageMaker Pipelines. Prior experience building on Medicaid or dual-eligible populations. Peer-reviewed publications in healthcare ML, AI, biostatistics, or health economics. Why This Role Matters Waymark is scaling across health plan and health system partners, and the depth of clinical insight we can extract from our data directly determines whether our models drive better care. This role sits at the center of what makes Waymark's models accurate and clinically actionable. By taking ownership you will: Define and own clinical data quality standards across claims, EHR, and ADT. Build and ship production ML/AI models that translate clinical data into actionable predictions and outcomes evidence Advance our core DS and AI products with production-grade models and rigorous methods Raise the technical bar of the data science team through standards-setting and mentorship Hiring Range US Employees in San Francisco/Bay Area, New York City - $160,000 - $229,000 US Employees in Boston, Los Angeles, Seattle, Washington DC - $147,000 - $211,000 US Employees in Arlington, Denver, San Diego, Sacramento - $140,800 - $202,000 US Employees in Albany, Atlanta, Austin, Baltimore, Central/Southern, Charlotte, Chicago, Dallas/Fort Worth, Detroit, Houston, Las Vegas, Miami, Milwaukee, Philadelphia, Portland, Research Triangle, Salt Lake City, Twin Cities - $128,000 - $184,000 US Employees in Baton Rouge, Birmingham, Charleston, Cincinnati, Cleveland, Daytona Beach, Indianapolis, Nashville, New Orleans, Omaha, Phoenix, Pittsburgh, St. Louis, Tampa - $124,160 - $178,000 In addition to salary, we offer a comprehensive benefits package. Here’s what you can expect: Stock Options: Opportunity to invest in the company’s growth. Work-from-Home Stipend: A dedicated stipend for your first year to help set up your home office. Medical, Vision, and Dental Coverage: Comprehensive plans to keep you and your family healthy. Life Insurance: Basic life insurance to give you peace of mind. Paid Time Off: 20 vacation days, accrued over the year, plus 11 paid holidays. Parental Leave: 16 weeks of paid leave for birthing parents after six months of employment, and 8 weeks of bonding leave for non-birthing parents. Retirement Savings: Access to a 401(k) plan with a company contribution, subject to a vesting schedule. Commuter Benefits: Convenient options to support your commute needs. Professional Development Stipend: A dedicated stipend supports professional development and growth. Offer of employment is contingent upon successful completion of a background check. Employment history and advance degree verification (when applicable) are included as part of the standard background check process. Don’t check off every box in the requirements listed above? Please apply anyway! Studies have shown that some of us may be less likely to apply to jobs unless we meet every single qualification. Waymark is dedicated to building a supportive, equal opportunity, and accessible workplace that fosters a sense of belonging – so if you’re excited about this role but your past experience doesn’t align perfectly with every preferred qualification in the job description, we encourage you to still consider submitting an application. You may be just the right candidate for this role or another one of our openings!", "summaryDescription" : "Principal Data Scientist, Health Informatics at Waymark. Skills: Clinical data, Applied ML/AI, Health economics. Define standards for clinical data. Structure clinical data", "postedDate" : "2026-06-11T19:03:26.877", "createdAt" : "2026-06-11T19:03:26.877", "lastUpdated" : "2026-06-13T10:48:39.355", "ingestTimestamp" : "2026-06-11T19:03:26.877", "mongoId" : "6a2a5b9174d8ee00a0610fbf", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 220000, "salaryAnnualMax" : 350000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Clinical terminologies", "Value set curation", "Model validation", "Model deployment", "ML pipelines", "Model versioning", "Reproducible workflows", "Clinical data", "Applied ML/AI", "Health economics", "ML/AI", "Health informatics", "Data quality", "Data normalization", "Clinical validity", "Risk adjustment", "Utilization measurement", "Cost attribution", "Quasi-experimental evaluation", "Outcomes measurement", "Project ownership", "Claims data", "EHR data", "ADT data", "ICD-10", "SNOMED CT", "LOINC", "RxNorm", "CPT/HCPCS", "Healthcare data standards", "Outcomes methods", "CMS reporting", "NCQA reporting", "MCO reporting", "Medicaid populations", "Dual-eligible populations", "Epic", "Cerner", "Athena", "MLflow", "SageMaker Pipelines" ], "skillCount" : 41, "jobCategory" : "engineering", "jobSubcategory" : "data-science,-design,-engineering-&-product-management-", "dataQualityScore" : 0.8888889, "_score" : 714.0636, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Healthcare" }, { "id" : "6a2a67d674d8ee00a0631879", "title" : "Principal Data Scientist - Gen AI", "company" : "Xometry", "salary" : { "min" : 245000.0, "max" : 355000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Principal Data Scientist in the United States, adjusted for executive seniority, the manufacturing industry, and the North Bethesda city tier." }, "location" : "North Bethesda, Maryland, United States", "locations" : [ "North Bethesda", "Maryland", "United States", "Boston", "Massachusetts", "United States" ], "timestamp" : "2026-06-14T22:23:51.754", "fingerprint" : "abf4afb0b3806146e5dc73a11473d6ab71529cff684eea98700089bfe151b1a4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/xometry/jobs/5160148007", "externalId" : "5160148007", "structuredLocations" : [ { "city" : "North Bethesda", "state" : "Maryland", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "39.0406500,-77.1233873" }, { "city" : "Waltham", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "42.3762385,-71.2355644" } ], "locationText" : "North Bethesda, Maryland, United States; Waltham, Massachusetts, United States", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, PyTorch, TensorFlow, pandas, numpy, Generative AI, Large Language Models, LLMs, Transformers, GPT, VLMs", "professionalSkills" : [ "Technical Vision", "Roadmap development", "Strategic planning", "Business value delivery", "Generative AI Development", "Multimodal document processing", "Structured data extraction", "Text data processing", "Image data processing", "Data extraction", "ML systems", "Production-grade ML", "Scientific direction", "AI-driven solutions" ], "hardSkillsList" : [ "Machine learning", "Statistical methodology", "Probability", "Statistics", "Optimization techniques", "Generative modeling", "Scientific computing", "Data processing" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Statistical methodology", "level" : "intermediate" }, { "name" : "Probability", "level" : "intermediate" }, { "name" : "Statistics", "level" : "intermediate" }, { "name" : "Optimization techniques", "level" : "intermediate" }, { "name" : "Generative modeling", "level" : "intermediate" }, { "name" : "Scientific computing", "level" : "intermediate" }, { "name" : "Data processing", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Generative AI, Machine learning, Large Language Models, Data Science", "majorSkillsList" : [ "Generative AI", "Machine learning", "Large Language Models", "Data Science" ], "coreResponsibilities" : "Own and drive technical roadmap, Lead strategic planning, Develop generative AI models, Deploy generative AI models, Develop large language models, Deploy large language models, Extract structured data, Lead exploration of data processing solutions, Develop data processing solutions, Train generative models, Fine-tune generative models, Train language models, Fine-tune language models, Drive cross-functional ML initiatives, Drive cross-functional AI initiatives, Set scientific direction for AI solutions", "teamCollaboration" : "Cross-functional teams", "projectManagementSkills" : [ "Roadmap development" ], "domainKnowledge" : "Multimodal document understanding; Structured data extraction; Generative modeling; Large language models; Vision models", "domainList" : [ "multimodal-document-understanding", "structured-data-extraction", "generative-modeling", "large-language-models", "vision-models" ], "domainSpecificKnowledge" : [ "Multimodal document understanding", "Structured data extraction", "Generative modeling", "Large language models", "Vision models" ], "toolProficiency" : [ "PyTorch", "TensorFlow", "pandas", "numpy" ], "innovationCreativity" : "Innovation", "problemSolvingSkills" : "Problem solving", "outcomesObjectives" : "Enhance Xometry's service offerings", "qualificationsBasic" : "Bachelor's degree required, 6+ years of relevant experience, Expert-level proficiency in Python, Proficient in Python, Proficient in PyTorch, Proficient in TensorFlow, Proficient in pandas, Proficient in numpy, Recognized depth in machine learning, Recognized depth in statistical methodology, Expertise in large-scale language models, Expertise in vision models, Experience with multimodal data processing, background in probability, background in statistics, background in optimization techniques", "qualificationsPreferred" : "Advanced degree (M. S. or PhD) preferred, PhD preferred, Experience with Transformers, Experience with GPT, Experience with VLMs, Experience with combining text, image, and 3D data", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry’s digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. About the Role Xometry is seeking an exceptional Principal Data Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine-tuning generative and language models, multimodal document understanding, and structured data extraction. This role will also serve as a key technical leader for high-stakes strategic initiatives, including the DFM AI + IQE integration with Siemens. In this role, you will serve as a technical leader, owning a 12 month technical roadmap, driving large-scale cross-functional ML and AI initiatives, and setting the long-term scientific direction for AI-driven solutions that enhance Xometry's service offerings. This role requires a hybrid schedule (3 days a week) at our Waltham, MA or North Bethesda, MD office location. How You'll Contribute Technical Vision and Roadmap: Own and drive an 18-24 month technical roadmap that balances innovation with disciplined business value delivery. Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry’s business objectives. Generative AI Development: Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents. Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models. Technical Leadership or a PhD with 6-plus years of relevant experience. A bachelor’s degree is required, but an advanced degree (M. S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred. Technical Mastery: Expert-level proficiency in Python and advanced scientific computing, with a track record of building large-scale, production-grade ML systems. Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy. AI/ML Expertise: Recognized depth in machine learning and statistical methodology. Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs) and experience with multimodal data processing (e.g., combining text, image, and 3D data). Strong background in probability, statistics, and optimization techniques relevant to generative modeling. Strategic life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more. #LI-Hybrid Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.", "summaryDescription" : "Principal Data Scientist - Gen AI at Xometry. Skills: Generative AI, Machine learning, Large Language Models, Data Science. Own and drive technical roadmap. Lead strategic planning", "postedDate" : "2026-06-11T18:23:47.205", "createdAt" : "2026-06-11T18:23:47.205", "lastUpdated" : "2026-06-14T22:23:51.754", "ingestTimestamp" : "2026-06-11T18:23:47.205", "mongoId" : "6a2a67d674d8ee00a0631879", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 245000, "salaryAnnualMax" : 355000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Machine learning", "Statistical methodology", "Probability", "Statistics", "Optimization techniques", "Generative modeling", "Scientific computing", "Data processing", "Leadership", "Generative AI", "Large Language Models", "Data Science", "Technical Vision", "Roadmap development", "Strategic planning", "Business value delivery", "Generative AI Development", "Multimodal document processing", "Structured data extraction", "Text data processing", "Image data processing", "Data extraction", "ML systems", "Production-grade ML", "Scientific direction", "AI-driven solutions", "Multimodal document understanding", "Large language models", "Vision models", "PyTorch", "TensorFlow", "pandas", "numpy" ], "skillCount" : 33, "jobCategory" : "engineering", "jobSubcategory" : "data-science-and-engineering-", "dataQualityScore" : 0.8888889, "_score" : 710.59454, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true }, { "id" : "69fe94ff4c40e2acd1121a1f", "title" : "Sr. Principal Scientist, Stores Economics and Science", "company" : "Amazon.com Services LLC", "industry" : "Applied Science, Technology, core ai", "salary" : { "min" : 240100.0, "max" : 324800.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T00:00:48.089", "fingerprint" : "552f8d04abbb98c0f713be8076a9748404c182c50620108c624992e4f150f7f1", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10414402/apply", "externalId" : "49ad8287-3f40-435c-8e77-604d4421a595", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "R, Python, Matlab, STATA", "professionalSkills" : [ "Economic analysis", "Data science", "Business analysis" ], "hardSkillsList" : [ "Statistical analysis", "Machine learning", "Econometrics" ], "hardSkills" : [ { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Econometrics", "level" : "intermediate" } ], "majorSkills" : "Machine learning, Economics, Data analysis", "majorSkillsList" : [ "Machine learning", "Economics", "Data analysis" ], "coreResponsibilities" : "Provide structure around complex business problems, Work with machine learning scientists to estimate and, Help business and tech partners turn analysis results, Own the development of scientific models, Manage data analysis, modeling, and experimentation, Estimate and validate models, Work with business partners to communicate analysis/modeling properties, Incorporate feedback and requests into projects", "teamCollaboration" : "Business and tech partners; Scientists and engineers; Business teams", "domainKnowledge" : "Stores economy; Buyer and seller economy; Econometrics", "domainList" : [ "stores-economy", "buyer-and-seller-economy", "econometrics" ], "domainSpecificKnowledge" : [ "Stores economy", "Buyer and seller economy", "Econometrics" ], "communicationSkills" : "Convey complicated process and systems", "innovationCreativity" : "Creative thinkers", "problemSolvingSkills" : "Complex business problems", "outcomesObjectives" : "Major impact on Amazon's business", "qualificationsBasic" : "PhD in Economics, Computer Science, Operations Research or highly related field, Experience in industry, consulting, government, or academic research, Coding ability in a scripting language such as R, Python, Matlab, or STATA", "qualificationsPreferred" : "Written and verbal communications skills, Considerably more and broader experience, Track record in performing high-quality analysis of data at scale", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are looking for a science leader who is able to provide structure around complex business problems, work with machine learning scientists to estimate and validate their models on large scale data, and who can help business and tech partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas. At the senior level, we expect you be able to own the development of scientific models and to manage, in close collaboration with scientists and engineers, the data analysis, modeling, and experimentation that is necessary for estimating and validating your model. You will need to work with our business partners to communicate the properties of your analysis/modeling and be able to work to incorporate their feedback and requests into your project. Experience in applied economic analysis is essential, and you should be familiar with modern tools for data science and business analysis. About the team The Stores Economics and Science (SEAS) organization uses economics, statistics, and machine learning to understand and design the complex economy of Amazon’s network of buyers and sellers. We are an interdisciplinary team, committed to use of cutting edge technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon. Our team is composed in equal parts of software engineers and scientists trained in diverse fields including ML, robotics, computer vision (CV), natural language processing (NLP), distributed systems and econometrics. Our mission is to drive adoption of AI science and technology across Amazon by partnering with business teams on science-heavy problems, incubating products with high AI research risk, reducing friction and manual effort with AI tooling, and raising the scientific bar across all teams at Amazon. Basic Qualifications: - PhD in Economics, Computer Science, Operations Research or highly related field (Physics, Statistics, Mathematics). - Experience in industry, consulting, government, or academic research. - Coding ability in a scripting language such as R, Python, Matlab, or STATA. Preferred Qualifications: - Written and verbal communications skills to convey complicated process and systems to business partners and senior leadership. - Applicants with considerably more and broader, experience are also strongly encouraged. - Strong track record in performing high-quality analysis of data at scale. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, Mountain View - 276,100.00 - 350,000.00 USD annually USA, WA, Seattle - 240,100.00 - 324,800.00 USD annually", "summaryDescription" : "Sr. Principal Scientist, Stores Economics and Science at Amazon.com Services LLC. Skills: Machine learning, Economics, Data analysis. Provide structure around complex business problems. Work with machine learning scientists to estimate and", "postedDate" : "2026-06-13T06:47:02.767", "createdAt" : "2026-06-13T06:47:02.767", "lastUpdated" : "2026-06-15T00:00:48.089", "ingestTimestamp" : "2026-06-13T06:47:02.767", "mongoId" : "69fe94ff4c40e2acd1121a1f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10414402/apply", "salaryAnnualMin" : 240100, "salaryAnnualMax" : 324800, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Statistical analysis", "Machine learning", "Econometrics", "Economics", "Data analysis", "Economic analysis", "Data science", "Business analysis", "Stores economy", "Buyer and seller economy" ], "skillCount" : 10, "jobCategory" : "other", "dataQualityScore" : 1.0, "_score" : 705.3878, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2c7fe274d8ee00a0956bbc", "title" : "Sr. Principal Scientist, Analytical Development (Small Molecule)", "company" : "Antares Therapeutics", "industry" : "Pharma", "salary" : { "min" : 205000.0, "max" : 240000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, Massachusetts, United States", "locations" : [ "Boston", "Massachusetts", "United States" ], "timestamp" : "2026-06-15T07:53:19.521", "fingerprint" : "9191e6d7037cb3a1055ea876c17ebe9b9442330771ffa2f0346876520baadd7b", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/antaresrx/jobs/6020291004", "externalId" : "6020291004", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 15, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Analytical development, Small molecule, Drug substance, Drug product, Analytical method development, Analytical validation, Solid state characterization, Formulations", "professionalSkills" : [ "Technical leadership", "Strategic direction", "Scientific alignment", "Technical achievement", "Scientific community leadership", "Technical problem solving", "Innovative solutions", "Project planning", "Resource allocation", "External collaborations", "Internal collaborations", "Stakeholder management" ], "hardSkillsList" : [ "Analytical method development", "Method validation", "Solid state characterization", "Formulation development", "Regulatory submissions" ], "softSkillsList" : [ "Leadership", "Mentorship" ], "hardSkills" : [ { "name" : "Analytical method development", "level" : "intermediate" }, { "name" : "Method validation", "level" : "intermediate" }, { "name" : "Solid state characterization", "level" : "intermediate" }, { "name" : "Formulation development", "level" : "intermediate" }, { "name" : "Regulatory submissions", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentorship" } ], "majorSkills" : "Analytical Development, Small Molecule, Drug Substance, Drug Product", "majorSkillsList" : [ "Analytical Development", "Small Molecule", "Drug Substance", "Drug Product" ], "coreResponsibilities" : "Provide technical leadership, Provide strategic direction, Lead analytical efforts, Support drug substance development, Support drug product development, Ensure successful execution, Leverage internal capabilities, Leverage external partners, Drive alignment, Lead cross-functional teams, Contribute to cross-functional teams, Manage technical issues, Manage risks, Maintain scientific expertise, Advance technical expertise, Apply innovative approaches, Solve complex challenges, Provide oversight, Review analytical documentation, Support regulatory submissions, Establish project plans, Manage project timelines, Manage project budgets, Manage resource allocation, Build collaborations, Maintain collaborations, Manage CDMO partnerships, Manage technical stakeholders", "teamCollaboration" : "Cross-functional teams; External partners; CDMOs; Technical stakeholders", "projectManagementSkills" : [ "Project plans", "Timelines", "Budgets", "Resource allocation" ], "domainKnowledge" : "Small molecule programs; Drug substance; Drug product; Phase-appropriate development; Control strategies; Pre-development activities; Pre-formulation; Solid state characterization; Formulations for animal studies; Quality guidelines; Regulatory guidelines; Regulatory submissions", "domainList" : [ "small-molecule-programs", "drug-substance", "drug-product", "phase-appropriate-development", "control-strategies", "pre-development-activities", "pre-formulation", "solid-state-characterization", "formulations-for-animal-studies", "quality-guidelines", "regulatory-guidelines", "regulatory-submissions" ], "domainSpecificKnowledge" : [ "Small molecule programs", "Drug substance", "Drug product", "Phase-appropriate development", "Control strategies", "Pre-development activities", "Pre-formulation", "Solid state characterization", "Formulations for animal studies", "Quality guidelines", "Regulatory guidelines", "Regulatory submissions" ], "communicationSkills" : "Written communication; Verbal communication", "documentationSkills" : "Analytical development documentation; Regulatory submissions", "innovationCreativity" : "Innovative approaches; New technologies", "problemSolvingSkills" : "Technical problem-solving; Complex challenges", "qualificationsBasic" : "PhD in chemistry, 15+ years relevant experience, Analytical development experience, Biotech or pharmaceutical settings, Phase-appropriate small molecule analytical method development, Validation experience, Advanced analytical principles, Laboratory techniques for drug substance, Drug product techniques, Control strategies application, Pre-development activities experience, Pre-formulation experience, Solid state characterization, Formulations for animal studies, Quality and regulatory guidelines, Analytical sections of regulatory submissions, Lead in cross-functional matrix environments, Set clear goals, Manage tasks, resources, priorities, Implement new technologies, Innovative approaches within development, Develop and manage project plans, Manage timelines and budgets, Internal and external teams management, Build effective collaborations, CDMO collaborations, Technical leads collaborations, Project teams collaborations, Mentoring direct reports", "qualificationsPreferred" : "Experience mentoring direct reports", "workSiteFlexibility" : "Onsite", "rawDescription" : "Senior Principal Scientist, Analytical Development (Small Molecule) Salary Band: $205,000-$240,000 Location: Downtown Boston, MA Position Overview The Senior Principal Scientist will provide technical leadership of analytical development within the CMC function across the Antares portfolio. Analytical Development is responsible for analytical activities spanning late-stage discovery (lead optimization and candidate nomination) through early clinical development and late-stage commercial readiness for small molecule programs. This individual will ensure success across drug substance and drug product deliverables by effectively leveraging internal and external resources, while driving strategic and scientific alignment of analytical development activities with overall program needs. The ideal candidate brings a strong track record of leadership, mentorship, and technical achievement within matrixed environments, and will act as a recognized leader in the scientific community—capable of resolving complex technical challenges while advancing innovative solutions across programs. Key Responsibilities Provide technical leadership and strategic direction for analytical development activities across programs Lead analytical efforts supporting drug substance and drug product development from discovery through commercial readiness Ensure successful execution of analytical deliverables by leveraging internal capabilities and external partners (e.g., CDMOs/CROs) Drive alignment between analytical development strategies and overall program objectives Lead and contribute to cross-functional teams, effectively managing technical issues and risks within a matrix environment Maintain and advance state-of-the-art scientific and technical expertise, applying innovative approaches to solve complex challenges Provide oversight and review of analytical development documentation to support regulatory submissions Establish and manage project plans, timelines, budgets, and resource allocation for analytical activities Build and maintain strong internal and external collaborations, including partnerships with CDMOs and technical stakeholders Qualifications PhD in chemistry, chemical technologies, or related field with 15+ years of relevant industry experience in analytical development within biotech or pharmaceutical settings Demonstrated expertise in phase-appropriate small molecule analytical method development and validation Extensive knowledge of advanced analytical principles and laboratory techniques for drug substance and drug product, including application of control strategies across all stages of development Experience with pre-development activities, including pre-formulation, solid state characterization, and formulations for animal studies Strong understanding of quality and regulatory guidelines, with experience supporting analytical sections of regulatory submissions Proven ability to lead in cross-functional matrix environments, set clear goals, and manage tasks, resources, and priorities Excellent written and verbal communication skills, with strong organizational, planning, and technical problem-solving capabilities Demonstrated ability to implement new technologies and innovative approaches within development programs Experience developing and managing project plans, timelines, and budgets across internal and external teams Proven track record of building effective collaborations with CDMOs, technical leads, and project teams Prior experience mentoring and potentially managing direct reports The anticipated annual salary range for this position is $205,000-$240,000 annually. The actual salary offered will be based on a number of factors, including but not limited to the qualifications of the applicant, years of relevant experience, level of education attained, certifications or other professional licenses held, and if applicable, the location in which the applicant lives and/or from which they will be performing the job.", "summaryDescription" : "Sr. Principal Scientist, Analytical Development (Small Molecule) at Antares Therapeutics. Skills: Analytical Development, Small Molecule, Drug Substance, Drug Product. Provide technical leadership. Provide strategic direction", "postedDate" : "2026-06-13T20:36:53.857", "createdAt" : "2026-06-13T20:36:53.857", "lastUpdated" : "2026-06-15T07:53:19.521", "ingestTimestamp" : "2026-06-13T20:36:53.857", "mongoId" : "6a2c7fe274d8ee00a0956bbc", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 205000, "salaryAnnualMax" : 240000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Analytical method development", "Method validation", "Solid state characterization", "Formulation development", "Regulatory submissions", "Leadership", "Mentorship", "Analytical Development", "Small Molecule", "Drug Substance", "Drug Product", "Technical leadership", "Strategic direction", "Scientific alignment", "Technical achievement", "Scientific community leadership", "Technical problem solving", "Innovative solutions", "Project planning", "Resource allocation", "External collaborations", "Internal collaborations", "Stakeholder management", "Project plans", "Timelines", "Budgets", "Small molecule programs", "Drug substance", "Drug product", "Phase-appropriate development", "Control strategies", "Pre-development activities", "Pre-formulation", "Formulations for animal studies", "Quality guidelines", "Regulatory guidelines" ], "skillCount" : 36, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 1.0, "_score" : 698.5522, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.95 }, { "id" : "68ed10ae70f0b99d58e7bcd1", "title" : "Principal Applied Scientist, Prime Video Personalization & Discovery", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, entertainment", "salary" : { "min" : 179000.0, "max" : 309400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Sunnyvale, California, USA", "locations" : [ "Sunnyvale, California, USA" ], "timestamp" : "2026-06-15T11:06:10.456", "fingerprint" : "635dfd8d7b9bc449f976ee094597d80695eac92026ecc70e2df38bea74c371c5", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3104623/apply", "externalId" : "b7f3a3b1-37d3-4118-a181-ca91ab249c9f", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Sunnyvale", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.3688301,-122.0363490" } ], "locationText" : "Sunnyvale, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, Java, C++, TensorFlow, PyTorch, Deep learning, Generative AI, Reinforcement learning, Optimization", "professionalSkills" : [ "System design", "MLOps" ], "hardSkillsList" : [ "Recommendation systems", "Search relevance", "Personalization systems", "A/B testing", "Data analysis" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Recommendation systems", "level" : "intermediate" }, { "name" : "Search relevance", "level" : "intermediate" }, { "name" : "Personalization systems", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Machine learning, Recommendation systems, Generative AI, Personalization", "majorSkillsList" : [ "Machine learning", "Recommendation systems", "Generative AI", "Personalization" ], "coreResponsibilities" : "Invent, prototype, and productionize AI solutions, Provide technical leadership, Influence product vision, Design and lead A/B tests, Validate hypotheses, Guide product decisions, Drive technical bar-raising, Mentor scientists, Review designs, Publish research internally and externally", "teamCollaboration" : "Collaborate with engineers; Collaborate with product managers; Collaborate with senior leaders", "domainKnowledge" : "Personalization systems; Discovery ecosystem; Recommendation systems; Generative AI", "domainList" : [ "personalization-systems", "discovery-ecosystem", "recommendation-systems", "generative-ai" ], "domainSpecificKnowledge" : [ "Personalization systems", "Discovery ecosystem", "Recommendation systems", "Generative AI" ], "communicationSkills" : "Technical leadership; Publish research", "continuousLearning" : "Stay ahead of industry trends", "innovationCreativity" : "Invent groundbreaking AI solutions; Push boundaries", "problemSolvingSkills" : "Data analysis", "outcomesObjectives" : "Deliver AI-powered customer experiences; Drive business goals", "qualificationsBasic" : "PhD or Master's with 10+ years experience, 8+ years ML model experience, Proven leadership in ML/AI initiatives, Proficiency in Python, Java, or C++, Experience with ML frameworks", "qualificationsPreferred" : "Strong publication record, PhD preferred", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you interested in shaping the future of entertainment through cutting-edge AI? Prime Video’s technology teams are redefining the digital video experience at scale. As a Principal Applied Scientist at Prime Video, you will be a technical and strategic leader responsible for inventing, developing, and deploying groundbreaking AI solutions that power personalized, relevant, and delightful experiences for millions of global customers. You will help shape the vision and direction of key ML systems that support Prime Video’s mission to deliver AI-powered customer experiences. This role demands a unique blend of deep technical expertise in machine learning and recommendation systems, industry leadership, and strong collaboration skills. You will guide the development of high-impact systems end-to-end—leading innovation from foundational research through production deployment—while mentoring scientists and influencing product and engineering roadmaps. We are looking for a thought leader who brings a strong track record of delivering ML innovations at scale, along with the curiosity and drive to push boundaries. This is a rare opportunity to drive meaningful impact at one of the largest streaming services in the world. Key job responsibilities -Invent, prototype, and productionize large-scale AI solutions across Prime Video’s personalization and discovery ecosystem using deep learning, generative AI, reinforcement learning, and optimization techniques; -Provide technical leadership and influence product vision by collaborating closely with engineers, product managers, and senior stakeholders; -Design and lead high-impact A/B tests and data analyses to validate hypotheses and guide product direction; -Drive technical bar-raising across science and engineering teams through mentorship, design reviews, and collaboration; -Stay ahead of industry trends and emerging research; leverage them to evolve long-term strategy and architecture; -Publish impactful research internally and externally (e.g. top-tier conferences and journals). About the team Prime Video Personalization and Discovery (PVPD) is dedicated to creating a highly personalized content discovery experience that not only delights our customers but also drives both short-and long-term business goals. Our scope includes personalized recommendations, search, marketing, and the advanced machine learning technology and infrastructure that underpins these experiences. Our mission is to automate and enhance customer engagement through personalization, using ML and Generative AI. Basic Qualifications: -PhD (or Master’s with 10+ years of applied experience) in machine learning, computer science, statistics, or a related field -8+ years of experience designing, building, and deploying ML models for real-world business applications at scale -Proven leadership in driving cross-functional ML/AI initiatives from ideation through production Proficiency in Python, Java, or C++, and experience with ML frameworks (e.g., TensorFlow, PyTorch) -Deep expertise in recommendation systems, search relevance, or large-scale personalization systems Preferred Qualifications: -Strong publication record in top-tier conferences (e.g. NeurIPS, ICML, KDD, RecSys, SIGIR) -Experience with large-scale distributed systems (e.g. Hadoop, Spark) -Demonstrated ability to influence technical roadmaps and mentor other scientists and engineers -Experience defining and delivering strategic AI vision for consumer-facing products Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Principal Applied Scientist, Prime Video Personalization & Discovery at Amazon.com Services LLC. Skills: Machine learning, Recommendation systems, Generative AI, Personalization. Invent, prototype, and productionize AI solutions. Provide technical leadership", "postedDate" : "2026-06-13T19:45:52.067", "createdAt" : "2026-06-13T19:45:52.067", "lastUpdated" : "2026-06-15T11:06:10.456", "ingestTimestamp" : "2026-06-13T19:45:52.067", "mongoId" : "68ed10ae70f0b99d58e7bcd1", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3104623/apply", "salaryAnnualMin" : 179000, "salaryAnnualMax" : 309400, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Recommendation systems", "Search relevance", "Personalization systems", "A/B testing", "Data analysis", "Leadership", "Mentoring", "Machine learning", "Generative AI", "Personalization", "System design", "MLOps", "Discovery ecosystem" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Executive", "dataQualityScore" : 1.0, "_score" : 694.7419, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "68e6b1d870f0b99d58d66a84", "title" : "Principal Applied Scientist, Hardware Silicon and Systems Group", "company" : "ADCI", "industry" : "Machine Learning Science, Applied Science, alexa and amazon devices", "salary" : { "min" : 6000000.0, "max" : 9000000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Principal Applied Scientist in Bengaluru, India, adjusted for executive seniority and technology industry." }, "location" : "Bengaluru, Karnataka, IND", "locations" : [ "Bengaluru, Karnataka, IND" ], "timestamp" : "2026-06-16T04:14:17.090", "fingerprint" : "de28bd31718a0a3a760c707970e79f984e16268c138d3264f4dc82a4f411e979", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3103322/apply", "externalId" : "601eb834-4d4c-46c8-a0b4-013265096258", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bengaluru", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, Karnataka, India", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Machine learning, Deep learning, Computer architecture, Inference algorithms, TensorFlow, PyTorch, ONNX", "professionalSkills" : [ "Model architecture design", "Model optimization", "Model deployment", "Hardware acceleration", "Efficient inference", "Model compression", "Quantization", "Pruning", "Distillation", "Multimodal optimization" ], "hardSkillsList" : [ "Hardware-aware quantization", "Low-precision arithmetic" ], "hardSkills" : [ { "name" : "Hardware-aware quantization", "level" : "intermediate" }, { "name" : "Low-precision arithmetic", "level" : "intermediate" } ], "majorSkills" : "ML models, Hardware optimization, Model compression, On-device ML", "majorSkillsList" : [ "ML models", "Hardware optimization", "Model compression", "On-device ML" ], "coreResponsibilities" : "Own technical architecture, Optimize ML models, Develop novel model architectures, Establish methodologies for model compression, Create evaluation framework, Implement multimodal optimization techniques, Define technical standards, Drive research initiatives, Develop novel ML architectures, Write critical optimization code, Create proof-of-concept implementations, Influence architecture decisions, Establish standards for model optimization, Mentor others", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "On-device ML models; ML innovation; Silicon design; Resource-constrained devices; Consumer AI devices; Model training; Vision tasks; Language tasks; Multi-modal tasks; Custom silicon; Edge devices", "domainList" : [ "on-device-ml-models", "ml-innovation", "silicon-design", "resource-constrained-devices", "consumer-ai-devices", "model-training", "vision-tasks", "language-tasks", "multi-modal-tasks", "custom-silicon", "edge-devices" ], "domainSpecificKnowledge" : [ "On-device ML models", "ML innovation", "Silicon design", "Resource-constrained devices", "Consumer AI devices", "Model training", "Vision tasks", "Language tasks", "Multi-modal tasks", "Custom silicon", "Edge devices" ], "innovationCreativity" : "Industry-first model architectures; Breakthrough efficiency gains", "qualificationsBasic" : "Masters degree in Computer Science, 8+ years of experience in machine learning, Expertise in developing deep learning models, Background in computer architecture, Hands-on experience with model compression techniques, Proficiency with deep learning frameworks", "qualificationsPreferred" : "PhD in Computer Science, 10+ years of experience in machine learning, Proven expertise in co-designing ML models, In-depth understanding of model compression, Experience working on resource-constrained embedded systems, Demonstrated ability to influence technical strategy, Mentor cross-functional teams", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Hardware Silicon and Systems Group leads the development and optimization of on-device ML models for Amazon's hardware products, including audio, vision, and multi-modal AI features. We work at the critical intersection of ML innovation and silicon design, ensuring AI capabilities can run efficiently on resource-constrained devices. Currently, we enable production ML models across multiple device families, including Echo, Ring/Blink, and other consumer devices. Our work directly impacts Amazon's customer experiences in consumer AI device market. The solutions we develop determine which AI features can be offered on-device versus requiring cloud connectivity, ultimately shaping product capabilities and customer experience across Amazon's hardware portfolio. This is a unique opportunity to help shape the future of AI in consumer devices at unprecedented scale. You'll be at the forefront of developing industry-first model architectures and compression techniques that will power AI features across millions of Amazon devices worldwide. Your innovations will directly enable new AI features that enhance how customers interact with Amazon products every day. As Principal Applied Scientist you will blend expertise at the intersection of ML and hardware optimization for model training, build cutting-edge architectures for vision, language, and multi-modal tasks. Role requires a specialist in hardware-aware quantization, with hands-on experience in model compression techniques like pruning and distillation. You will be responsible for computer architecture, ML accelerator designs, efficient inference algorithms and low-precision arithmetic. Key job responsibilities As a Principal Applied Scientist, you will: • Own the technical architecture and optimization strategy for ML models deployed across Amazon's device ecosystem, from existing to yet-to-be-shipped products. • Develop novel model architectures optimized for our custom silicon, establishing new methodologies for model compression and quantization. • Create an evaluation framework for model efficiency and implement multimodal optimization techniques that work across vision, language, and audio tasks. • Define technical standards for model deployment and drive research initiatives in model efficiency to guide future silicon designs. • Spend the majority of your time doing deep technical work - developing novel ML architectures, writing critical optimization code, and creating proof-of-concept implementations that demonstrate breakthrough efficiency gains. • Influence architecture decisions impacting future silicon generations, establish standards for model optimization, and mentor others in advanced ML techniques. Basic Qualifications: Basic Qualifications: • Masters degree in Computer Science, Electrical Engineering, or a related technical field • 8+ years of experience in machine learning, with a focus on model architecture design, optimization, and deployment • Expertise in developing and deploying deep learning models for real-world applications, including vision, language, and multi modal tasks • Strong background in computer architecture, hardware acceleration, and efficient inference algorithms • Hands-on experience with model compression techniques such as pruning, quantization, and distillation • Proficiency with deep learning frameworks like TensorFlow, PyTorch, or ONNX Preferred Qualifications: • PhD in Computer Science, Electrical Engineering, or a related technical field • 10+ years of experience in machine learning, with a track record of developing novel model architectures and optimization techniques • Proven expertise in co-designing ML models and hardware accelerators for efficient on-device inference • In-depth understanding of the latest advancements in model compression, including techniques like knowledge distillation, network pruning, and hardware-aware quantization • Experience working on resource-constrained embedded systems and deploying ML models on edge devices • Demonstrated ability to influence technical strategy and mentor cross-functional teams • Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical stakeholders Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Principal Applied Scientist, Hardware Silicon and Systems Group at ADCI. Skills: ML models, Hardware optimization, Model compression, On-device ML. Own technical architecture. Optimize ML models", "postedDate" : "2026-06-14T19:48:18.334", "createdAt" : "2026-06-14T19:48:18.334", "lastUpdated" : "2026-06-16T04:14:17.090", "ingestTimestamp" : "2026-06-14T19:48:18.334", "mongoId" : "68e6b1d870f0b99d58d66a84", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3103322/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Hardware-aware quantization", "Low-precision arithmetic", "ML models", "Hardware optimization", "Model compression", "On-device ML", "Model architecture design", "Model optimization", "Model deployment", "Hardware acceleration", "Efficient inference", "Quantization", "Pruning", "Distillation", "Multimodal optimization", "On-device ML models", "ML innovation", "Silicon design", "Resource-constrained devices", "Consumer AI devices", "Model training", "Vision tasks", "Language tasks", "Multi-modal tasks", "Custom silicon", "Edge devices" ], "skillCount" : 26, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 1.0, "_score" : 691.49615, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ac0ec74d8ee00a06f2966", "title" : "Principal Scientist, Radiopharmaceutical Development/CMC", "company" : "RayzeBio", "industry" : "Biotechnology", "salary" : { "min" : 124449.0, "max" : 150803.0, "currency" : "USD", "frequency" : "yearly" }, "location" : "United States of America", "locations" : [ "United States of America" ], "timestamp" : "2026-06-14T19:13:46.951", "fingerprint" : "5bfa6e5082ec5bbd04bb5c37abbe23848851e8d64e4975b6ae25182c72909932", "source" : "workday", "language" : "en", "applyUrl" : "https://bristolmyerssquibb.wd5.myworkdayjobs.com/BMS/job/Indianapolis---RayzeBio---IN/Principal-Scientist--Radiopharmaceutical-Development-CMC_R1603030", "externalId" : "R1603030", "industryFunction" : { }, "locationPoint" : "51.43667,5.97917", "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "onsite" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI", "professionalSkills" : [ "Radiopharmaceutical development", "CMC", "Drug product development", "Process development", "Scale-up", "GMP manufacturing", "Technology transfer", "Root cause analysis", "Continuous process improvement", "Regulatory filings", "IND submissions", "NDA submissions", "Supply Chain", "R&D" ], "hardSkillsList" : [ "Formulation development", "Automation development", "Technical writing", "Problem-solving", "Project management" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Formulation development", "level" : "intermediate" }, { "name" : "Automation development", "level" : "intermediate" }, { "name" : "Technical writing", "level" : "intermediate" }, { "name" : "Problem-solving", "level" : "intermediate" }, { "name" : "Project management", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Radiopharmaceutical development, CMC, GMP manufacturing", "majorSkillsList" : [ "Radiopharmaceutical development", "CMC", "GMP manufacturing" ], "coreResponsibilities" : "Provide scientific and technical leadership, Drive end-to-end process development, Drive scale-up, Translate novel processes into GMP manufacturing operations, Lead scientific experiments, Design scientific experiments, Plan scientific experiments, Execute scientific experiments supporting development, Execute scientific experiments supporting scale-up, Execute scientific experiments supporting automation, Drive technology transfer of drug products, Drive technology transfer of APIs, Define user requirements, Define technical specifications, Influence equipment design, Influence equipment selection, Investigate manufacturing gaps, Investigate manufacturing deviations, Lead development of corrective actions, Lead execution of corrective actions, Lead continuous process improvement initiatives, Author technical reports, Author development summaries, Author source documents, Support regulatory filings, Collaborate cross-functionally, Ensure scientific alignment, Ensure operational alignment, Mentor junior scientists, Develop junior scientists, Foster a culture of scientific excellence, Foster a culture of continuous learning, Foster a culture of operational rigor, Support commercialization activities, Contribute to successful transition to commercial-scale manufacturing", "teamCollaboration" : "Cross-functional teams; Discovery teams; Pharmacology teams; CMC teams; Toxicology teams; Clinical teams; Regulatory teams; Quality teams; Supply Chain teams; R&D teams", "projectManagementSkills" : [ "Project management" ], "domainKnowledge" : "Radiopharmaceuticals; GMP regulations; NRC regulations; Alpha/gamma emitting radionuclides", "domainList" : [ "radiopharmaceuticals", "gmp-regulations", "nrc-regulations", "alpha-gamma-emitting-radionuclides" ], "domainSpecificKnowledge" : [ "Radiopharmaceuticals", "GMP regulations", "NRC regulations", "Alpha/gamma emitting radionuclides" ], "communicationSkills" : "Technical writing", "documentationSkills" : "Technical writing; Regulatory filings", "problemSolvingSkills" : "Problem-solving; Root cause analysis", "specialRequirements" : "Travel up to 20%, Work in laboratory environment, Wear protective clothing, Wear gloves, Wear safety glasses, Work with radioactive materials, Occasionally lift and/or move up to 15 pounds", "qualificationsBasic" : "Ph.D., M.S., or B.S. in Chemistry, Chemical Engineering, Pharmaceutical Sciences, or related field, 8+ years of experience in drug development, manufacturing, CMC or related fields, Demonstrated experience in radiopharmaceutical formulation development, Demonstrated experience in radiopharmaceutical process development, Demonstrated experience in radiopharmaceutical GMP manufacturing, Proven track record of leading and executing IND-enabling studies, Proven track record of supporting regulatory submissions (IND, NDA, or equivalent), Experience with technology transfer from preclinical to clinical manufacturing environments, Working knowledge of GMP regulations (FDA, EMA, ICH guidelines), Working knowledge of NRC regulatory requirements", "qualificationsPreferred" : "Experience in radiopharmaceuticals, Experience working in hot cell environments, Experience with automated synthesis platforms", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "At RayzeBio, every day is an opportunity to ignite meaningful change. As a wholly-owned subsidiary of Bristol Myers Squibb, RayzeBio blends the nimble, pioneering spirit of an emergent biotech with the global expertise and resources of a leading innovator in oncology. Our mission is to develop transformative radiopharmaceutical therapies that offer new hope for patients living with cancer. Here, you’ll join a multidisciplinary team where your ideas are valued, your expertise is amplified, and collaboration is at the heart of everything we do. From day one, expect to make an immediate impact—on our science, on our teams, and most importantly, on patients. Learn more about RayzeBio: [https://careers.bms.com/rayzebio/](https://careers.bms.com/rayzebio/) # **Summary** The Principal Scientist, Radiopharmaceutical Development/CMC will play a key role in driving pre-clinical, early-, and late-stage development and lifecycle management of radiopharmaceuticals for clinical use. As a scientific and technical leader, this individual will be instrumental in advancing RayzeBio's innovative drug products from bench to clinic and beyond. The Principal Scientist will provide leadership across multiple stages of drug development — including formulation development and optimization, IND-enabling studies, and scale-up and automation development — while collaborating cross-functionally with discovery, pharmacology, CMC, toxicology, and clinical teams to accelerate novel therapeutics toward patients in need. # **Job Responsibilities** Essential duties and responsibilities include the following. Other duties may be assigned. ·Provide scientific and technical leadership across RayzeBio's drug product development platform, driving end-to-end process development, scale-up, and the translation of novel processes into robust, repeatable GMP manufacturing operations. ·Lead, design, plan, and execute scientific experiments supporting the development, scale-up, and automation of radiopharmaceutical drug product and API manufacturing processes. ·Drive the technology transfer of drug products and APIs from preclinical through clinical manufacturing stages, ensuring seamless transitions and sustained process continuity. ·Partner with Engineering and Operations to define user requirements and technical specifications, influence equipment design and selection for drug product manufacturing. ·Investigate manufacturing gaps and deviations through rigorous root cause analysis, leading the development and execution of corrective actions and continuous process improvement initiatives. ·Author technical reports, development summaries, and source documents to support regulatory filings, including CMC sections for IND and NDA submissions to the FDA, as well as filings for international regulatory jurisdictions (e.g., EMA, Health Canada). ·Collaborate cross-functionally with Regulatory, Quality, Supply Chain, Clinical, and R&D teams to ensure scientific and operational alignment with program milestones and corporate objectives. ·Mentor and develop junior scientists, fostering a culture of scientific excellence, continuous learning, and operational rigor. ·Support commercialization activities for radiopharmaceutical products, contributing to the successful transition from clinical to commercial-scale manufacturing. ·Travel up to 20% as required to support program needs and site activities. # **Education and Experience** ·Ph.D., M.S., or B.S. in Chemistry, Chemical Engineering, Pharmaceutical Sciences, or a related field, with requisite industry experience. ·8+ years of experience in drug development, manufacturing, CMC or related fields in a pharmaceutical industry, preferably radiopharmaceuticals. ·Demonstrated experience in radiopharmaceutical formulation development, process development, and GMP manufacturing. ·Proven track record of leading and executing IND-enabling studies and supporting regulatory submissions (IND, NDA, or equivalent). ·Experience with technology transfer from preclinical to clinical manufacturing environments. ·Working knowledge of GMP regulations (FDA, EMA, ICH guidelines) and NRC regulatory requirements. ·Experience working in hot cell environments and with automated synthesis platforms is highly desirable. # **Skills and Qualifications** ·Strong understanding of GMP, FDA/EMA regulations, and ICH guidelines. ·Strong problem-solving abilities and the ability to manage multiple projects in a fast-paced environment. ·Excellent project management and cross-functional collaboration skills. ·Excellent technical writing skills. ·Experience with alpha/gamma emitting radionuclides. ·Applies AI to improve team execution and decision‑making **Physical Demands** While performing the duties of this job, the employee is regularly required to sit, reach with hands and arms, and talk or hear. The employee must occasionally lift and/or move up to 15 pounds. Specific vision abilities required by this job include close vision and distance vision. This is a position that requires working in a laboratory environment, protective clothing, gloves, and safety glasses are required while working in a laboratory environment _with radioactive materials_. **Work****Environment** The noise level in the work environment is usually moderate. #LI-Onsite _If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career._ ******Compensation Overview:****** Indianapolis - RayzeBio - IN: $124,449 - $150,803 The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee’s work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience. Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit [ https://careers.bms.com/life-at-bms/.](https://careers.bms.com/life-at-bms/) Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include: * **Health Coverage:** Medical, pharmacy, dental, and vision care. * **Wellbeing Support:** Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP). * **Financial Well-being and Protection:** 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support. ** Work-life benefits include:** Paid Time Off * US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees) * Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays Based on eligibility*, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day. All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown. _***Eligibility Disclosure:**_T_ he summer hours program is for United States (U.S.) office-based employees due to the unique nature of their work. Summer hours are generally not available for field sales and manufacturing operations and may also be limited for the capability centers. Employees in remote-by-design or lab-based roles may be eligible for summer hours, depending on the nature of their work, and should discuss eligibility with their manager. Employees covered under a collective bargaining agreement should consult that document to determine if they are eligible. Contractors, leased workers and other service providers are not eligible to participate in the program._ **RayzeBio and Bristol Myers Squibb** RayzeBio was acquired by Bristol Myers Squibb (BMS) in 2024 and is a wholly-owned subsidiary of BMS; however, RayzeBio will continue to operate as a standalone organization. **Supporting People with Disabilities** BMS and RayzeBio are dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to [adastaffingsupport@bms.com](mailto:adastaffingsupport@bms.com). Visit [careers.bms.com/](https://careers.bms.com/eeo-accessibility)[eeo](https://careers.bms.com/eeo-accessibility)[-accessibility](https://careers.bms.com/eeo-accessibility) to access our complete Equal Employment Opportunity statement. **Candidate Rights** BMS and RayzeBio will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area. If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: [https://careers.bms.com/california-residents/](https://careers.bms.com/california-residents/) **Data Protection** We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at [https://careers.bms.com/fraud-protection/](https://careers.bms.com/fraud-protection/) Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations. If you believe that the job posting is missing information required by local law or incorrect in any way, please contact BMS at [TAEnablement@bms.com](mailto:TAEnablement@bms.com). Please provide the Job Title and Requisition number so we can review. Communications related to your application should not be sent to this email and you will not receive a response. R1603030 : Principal Scientist, Radiopharmaceutical Development/CMC", "summaryDescription" : "Principal Scientist, Radiopharmaceutical Development/CMC at RayzeBio. Skills: Radiopharmaceutical development, CMC, GMP manufacturing. Provide scientific and technical leadership. 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Senior management", "projectManagementSkills" : [ "Program management", "Product development cycles", "Release schedules" ], "domainKnowledge" : "Enterprise engineering; Endpoint management; Collaboration tools; Productivity experiences; Global scale", "domainList" : [ "enterprise-engineering", "endpoint-management", "collaboration-tools", "productivity-experiences", "global-scale" ], "domainSpecificKnowledge" : [ "Enterprise engineering", "Endpoint management", "Collaboration tools", "Productivity experiences", "Global scale" ], "communicationSkills" : "Executive communication; Listening skills; Writing skills", "documentationSkills" : "Writing specifications", "problemSolvingSkills" : "Analytical talent", "qualificationsBasic" : "7+ years technical product management, 7+ years program management, 10+ years working with engineering teams, 5+ years software development, Managing programs across cross functional teams, Building processes, Coordinating release schedules", "qualificationsPreferred" : "8+ years hands-on complex technology projects, Managing projects across cross functional teams, Building sustainable processes, Coordinating release schedules", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Enterprise Engineering builds and operates the internal tools, platforms, and AI-powered services that enable over 1.5 million Amazonians to do their best work every day — from endpoint management and collaboration to cutting-edge productivity experiences, all at massive global scale. We're seeking a Principal Technical Program Manager to lead high-impact, cross-functional, company wide projects. This role requires working closely with product management to define strategy and requirements, collecting business and systems requirements from customers and business units, writing specifications, and leading development teams from design through delivery and subsequent operation. You will be expected to make appropriate trade-offs to optimize launch timelines, clearly communicate goals, roles, responsibilities, and desired outcomes to internal cross-functional project teams. This position involves regular communication with senior management on status, risks, and product strategy. Excellent listening, writing skills, executive communication and very strong technical competency are essential. The ideal candidate will possess a strong program management background, will have demonstrated experience leading medium to large projects through multiple complete product development cycles, and will have a well-rounded technical background in current technologies. You must be able to thrive and succeed in an entrepreneurial environment, and not be hindered by ambiguity or competing priorities. This means you are not only able to develop and drive high-level strategic initiatives, but can also roll up your sleeves, dig in, and get the job done. You will anticipate bottlenecks, provide escalation management, anticipate and make trade-offs, and balance the business needs versus technical constraints. An ability to take large, complex projects and break them down into manageable pieces, develop detailed functional and test specifications, schedule, and deploy new feature sets in a successful and timely manner is expected. Maturity, high product judgment, negotiation skills, ability to influence, analytical talent, and leadership are essential to success in this role. Basic Qualifications: - 7+ years of technical product or program management experience - 10+ years of working directly with engineering teams experience - 5+ years of software development experience - Experience managing programs across cross functional teams, building processes and coordinating release schedules Preferred Qualifications: - 8+ years of hands-on work managing complex technology projects experience - Experience managing projects across cross functional teams, building sustainable processes and coordinating release schedules Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Seattle - 177,000.00 - 239,400.00 USD annually", "summaryDescription" : "Principal TPM, Enterprise Engineering at Amazon Development Center U.S., Inc.. Skills: Technical program management, Enterprise engineering, AI-powered services. Build internal tools. 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5-7 Central Ave", "locations" : [ "Eveleigh, NSW - 5-7 Central Ave", "Australia" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "dbt Certified" ], "timestamp" : "2026-06-12T15:34:34.046", "fingerprint" : "26a0491211e5a6137b288775348118c2180d1993d846c613e2e274491fa35456", "source" : "workday", "language" : "en", "applyUrl" : "https://cba.wd3.myworkdayjobs.com/CommBank_Careers/job/Eveleigh-NSW---5-7-Central-Ave/Principal-Data-Scientist_REQ258214", "externalId" : "REQ258214", "industryFunction" : { }, "locationPoint" : "-33.89559,151.19235", "structuredLocations" : [ { "city" : "Eveleigh", "state" : "New South Wales", "country" : "Australia", "continent" : "oc", "source" : "llm", "workMode" : "onsite", "geo" : "-33.8950000,151.1913889" } ], "locationText" : "Eveleigh, New South Wales, Australia", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "Generative AI, Machine Learning, Natural Language Processing, Unsupervised Clustering, Classification algorithms, Spark, Python, R, TensorFlow, PyTorch, SQL, ETL processes, Data pipeline construction, Docker, AWS, Azure, GitHub", "professionalSkills" : [ "Technical Leadership", "Coordination", "Financial Crime domain" ], "hardSkillsList" : [ "Prompt engineering", "Retrieval-Augmented Generation", "Guardrail design", "Orchestration design", "Evals frameworks", "Feature engineering", "Model selection", "Hyperparameter tuning", "Model evaluation", "Deployment", "Data pipeline construction" ], "softSkillsList" : [ "Intellectual curiosity", "Inclusion", "Continuous learning" ], "hardSkills" : [ { "name" : "Prompt engineering", "level" : "intermediate" }, { "name" : "Retrieval-Augmented Generation", "level" : "intermediate" }, { "name" : "Guardrail design", "level" : "intermediate" }, { "name" : "Orchestration design", "level" : "intermediate" }, { "name" : "Evals frameworks", "level" : "intermediate" }, { "name" : "Feature engineering", "level" : "intermediate" }, { "name" : "Model selection", "level" : "intermediate" }, { "name" : "Hyperparameter tuning", "level" : "intermediate" }, { "name" : "Model evaluation", "level" : "intermediate" }, { "name" : "Deployment", "level" : "intermediate" }, { "name" : "Data pipeline construction", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Intellectual curiosity" }, { "name" : "Inclusion" }, { "name" : "Continuous learning" } ], "majorSkills" : "Generative AI, Machine Learning, Agentic AI, Financial Crime", "majorSkillsList" : [ "Generative AI", "Machine Learning", "Agentic AI", "Financial Crime" ], "coreResponsibilities" : "Lead GenAI and Agentic system design and development, Prototype GenAI and Agentic solutions, Design GenAI and Agentic solutions, Develop GenAI and Agentic solutions, Deploy GenAI and Agentic solutions, Design monitoring for GenAI and Agentic solutions, Develop Machine Learning Models, Implement Machine Learning Models, Prototype Machine Learning Models, Design Machine Learning Models, Build Machine Learning Models, Deploy Machine Learning Models, Monitor Machine Learning Models, Expand Data/AI Science Usage, Identify AI opportunities, Drive Continuous Improvement, Drive Business Outcomes, Understand risk and operational pain points, Drive adoption of AI and GenAI, Enhance detection, Improve investigative outcomes, Shape the future operating model", "teamCollaboration" : "Cross-functional squads; Data Science community", "domainKnowledge" : "Financial Crime; Banking", "domainList" : [ "financial-crime", "banking" ], "domainSpecificKnowledge" : [ "Financial Crime", "Banking" ], "toolProficiency" : [ "LangChain", "LangGraph", "GitHub" ], "continuousLearning" : "Continuous learning", "innovationCreativity" : "Prototype development; Experimentation", "outcomesObjectives" : "Transform prevention of Financial Crime; Transform detection of Financial Crime; Transform investigation of Financial Crime; Enhance detection; Improve investigative outcomes; Shape the future operating model", "qualificationsBasic" : "5+ years experience, SQL proficiency, Python experience", "qualificationsPreferred" : "PhD preferred, AWS or Azure Cloud architecture experience, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, dbt Certified certification", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "**Business & Team: **Financial Crime AI Team, COO **See yourself in our team:** At the heart of the Chief Operations Office, we’re driving CBA’s ambition to detect, deter and ultimately eliminate financial crime through the power of transformative AI solutions. As a Principal Data Scientist in Financial Crime domain, you’ll be a hands-on technical leader working in cross-functional squads with engineers and other experts to design and deliver innovative, responsible and high impact AI solutions. You’ll stay at the forefront of emerging technologies, fostering a culture of curiosity, inclusion, and continuous learning in the team, and translating complex ideas into high-impact outcomes for our customers and colleagues. You’ll contribute strongly to guide the team on technically demanding problems across Fin Crime domain as AI continues to evolve. _If you’re passionate about shaping the future of AI while helping others thrive, we’d love you to lead with us._ **Key Responsibilities:** * **Lead GenAI and Agentic system design and development:** Prototype, design, develop, deploy and design monitoring for innovative GenAI and Agentic solutions that transform the prevention, detection and investigation of Financial Crime in the bank while setting technical direction and best practices across the domain. * **Develop and implement Machine Learning Models:** Prototype, design, build, deploy and monitor a variety of machine learning models * **Expand Data/AI Science Usage** : Identify potential AI opportunities across Fin Crime for future focus * **Drive Continuous Improvement and Business Outcomes:** Work closely with financial crime stakeholders to understand risk and operational pain points, driving adoption of AI and GenAI to enhance detection, improve investigative outcomes, and shape the future operating model **We’re interested in hearing from people with the following skills.** **Technical Leadership and Coordination:** * Ability to coordinate effectively across the Fin Crime and COO Data Science community to unify efforts and drive collaborative outcomes. * Demonstrated capability in driving outcomes that are reusable and can be leveraged across the group. * Intellectual curiosity and ability and willingness to learn, experiment and lead new to the world concepts **Technical Skills and Tools:** * **Generative AI:** Experience designing and deploying various aspects of Generative AI, including prompt engineering, Retrieval-Augmented Generation (RAG), guardrail design, orchestration design, skills, evals frameworks, and tools such as LangChain and LangGraph. * **Machine Learning** : Expertise in the design and construction of machine learning models, including natural language processing, unsupervised clustering and classification algorithms including feature engineering, model selection, hyperparameter tuning, model evaluation, and deployment of models into production environments. * **Cutting-Edge AI** : Work on projects leveraging traditional AI, Generative AI, and agentic AI to pave the path for how banking and broader industry functions in the future. * **Version Control and CI/CD:** Experience with version control and CI/CD pipelines such as GitHub. * **Tooling** : Hands-on experience with data science tools such as Spark, Python, R, TensorFlow, PyTorch, and SQL. * **Data Engineering:** Knowledge of ETL processes and data pipeline construction, ensuring efficient data flow and integration. * **Deployment** : Familiar with Docker for containerization and deployment of applications. * **Cloud Architecture: **Grounded understanding in AWS or Azure Cloud architecture and integration, demonstrating experience in deploying and managing cloud-based solutions. **Working with us:****** Our people bring their diverse backgrounds and unique perspectives to build a respectful, inclusive, and flexible workplace with an ultimate flexibility to work from any of our engineering hubs within Australia. One where we’re driven by our values, and supported to share ideas, initiatives, and energy. One where making a positive impact for customers, communities and each other is part of our every day. If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through [Sidekick](https://sidekick.hr.cba) to submit a valid application. We’re keen to support you with the next step in your career. We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696. Advertising End Date: 18/06/2026", "summaryDescription" : "Principal Data Scientist at The Heart Of The Chief Operations Office. Skills: Generative AI, Machine Learning, Agentic AI, Financial Crime. Lead GenAI and Agentic system design and development. 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Leeds, England, United Kingdom; Manchester, England, United Kingdom; London, England, United Kingdom; United Kingdom; Bulgaria", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI, Claude Code, Claude Opus", "professionalSkills" : [ "System design", "Architecture", "Decision making", "Review judgement", "Force multiplier", "SME", "Intellectual honesty", "Pragmatism", "Bias toward delivery", "Curiosity", "Context engineering", "Knowledge bases", "Machine-readable specs", "Non-determinism", "Value stream", "Fallback path" ], "hardSkillsList" : [ "Deep engineering foundations", "System thinking", "AI fluency", "Context engineering", "Code review", "Tool selection", "Non-determinism handling", "Evals", "Golden datasets", "Structured outputs" ], "softSkillsList" : [ "Outcome obsessed", "Intellectually honest", "Deeply pragmatic", "Relentlessly curious" ], "hardSkills" : [ { "name" : "Deep engineering foundations", "level" : "intermediate" }, { "name" : "System thinking", "level" : "intermediate" }, { "name" : "AI fluency", "level" : "intermediate" }, { "name" : "Context engineering", "level" : "intermediate" }, { "name" : "Code review", "level" : "intermediate" }, { "name" : "Tool selection", "level" : "intermediate" }, { "name" : "Non-determinism handling", "level" : "intermediate" }, { "name" : "Evals", "level" : "intermediate" }, { "name" : "Golden datasets", "level" : "intermediate" }, { "name" : "Structured outputs", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Outcome obsessed" }, { "name" : "Intellectually honest" }, { "name" : "Deeply pragmatic" }, { "name" : "Relentlessly curious" } ], "majorSkills" : "Architecture, Deep engineering, AI fluency, System thinking", "majorSkillsList" : [ "Architecture", "Deep engineering", "AI fluency", "System thinking" ], "coreResponsibilities" : "Set AI up for success, Architect systems with clean interfaces, Review code, Pick right tool for job, Build with AI components, Handle non-determinism, Build with guardrails, Build with quality gates, Justify technical opinions commercially, Immerse in client environment", "teamCollaboration" : "Cross-functional teams; Client sites; CreateFuture offices", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Enterprise clients; Scale-up businesses; AI models; Inference calls", "domainList" : [ "enterprise-clients", "scale-up-businesses", "ai-models", "inference-calls" ], "domainSpecificKnowledge" : [ "Enterprise clients", "Scale-up businesses", "AI models", "Inference calls" ], "toolProficiency" : [ "Claude Code", "Claude Opus" ], "communicationSkills" : "Hold a room; Client SME", "documentationSkills" : "Specs; Knowledge bases; Machine-readable specs", "continuousLearning" : "Professional growth; Personal growth", "innovationCreativity" : "R&D projects", "problemSolvingSkills" : "Root cause analysis; Troubleshooting; System thinking", "specialRequirements" : "Occasional travel, On-site work", "outcomesObjectives" : "Produce quality work at speed; Compound into systems that work; Unblock value stream", "qualificationsBasic" : "Complete package: architecture, Deep engineering foundations, System thinking, Judgement to direct intelligence, AI as first-class competency, Context engineering as craft, Architect systems with clean interfaces, Read far more code than write, Pick right tool for job, Build with AI components, Fluent with AI, On-site work", "qualificationsPreferred" : "Client enterprise experience, Scale-up business experience", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "CreateFuture is fast becoming the UK’s most recognisable digital consultancy, with years of experience building digital products and services for major organisations whilst putting our people first. We have offices in the centre of Edinburgh, Leeds, Manchester and London as well as remote employees located throughout the country. We are a team of creators - whether that’s code, project plans, go to market strategies, culture initiatives, marketing campaigns, large language models or people policies. And together, with our clients, we create the future. This has seen us collaborate and partner across a multitude of industries and sectors, with the likes of PayPal, Adidas, NatWest, FanDuel and Money Saving Expert to name just a few. Our reputation as a partner determined to deliver high-quality, robust and thoughtful products has enabled us to scale to over 500 people in the last couple of years, and it is our amazing people - along with the safe, supportive and friendly culture we have built - that makes CreateFuture a great place to work. Don’t just take our word for it though, we have been recognised by Best Workplaces UK multiple years in a row - across a number of categories - and our employee exit rate is astonishingly low. Join us on our journey… Let’s create something awesome, together, today. Principal Engineer About this role The bar has moved. Five years ago a strong engineer was measured by what they could build and how well they could mentor others to build it. Today, with Claude Code and agents, we produce quality work at a speed that would have looked superhuman in 2022. What separates exceptional from good is no longer typing speed or local craftsmanship. It is the complete package: architecture, deep engineering foundations, communication, system thinking, and the judgement to direct both your own intelligence and AI toward outcomes that matter. Exceptional people at this level are not the best implementer in the room; they are the person whose specifications, decisions, and review judgement compound into systems that work in production and that others (and agents) can build on. They are a force multiplier, they hold a room at the highest levels, and clients treat them as the SME by default. Your mindset The mindset is the engine, and it is almost impossible to teach retrospectively. You are outcome obsessed, not output obsessed and you care whether the problem was actually solved - you resist the ego instinct to admire a clever solution and ask whether it was needed at all. You are intellectually honest about uncertainty, taking a trust-but-verify approach and assuming the surprising bug is the one that will burn. You are deeply pragmatic, which matters at CreateFuture where pace counts: you have outgrown the religious wars about platforms, languages and patterns, you hold opinions loosely, and you decide for the systems in front of you, not the ones you wish you had. You have a bias toward delivery: the smallest thing that works, then iterate, treating documents and meetings as means to that end. And you are relentlessly curious beyond any immediate need, wanting to know how the database actually stores things or why a Claude Opus inference call costs what it does, which keeps you several layers ahead while the rest of the team is still reading the API docs. AI as the accelerant For a Principal to be truly exceptional, this is now already a first-class competency in your arsenal, not a side skill. An engineer who is brilliant by last year's standards but not fluent with AI is not exceptional in 2026. In practice that means: Setting AI up to succeed. You treat context engineering as a craft (the right files, specs, examples and constraints), and you architect systems with clean interfaces, good naming, machine-readable specs and knowledge bases so the codebase is a quality baseline AI can work on later. No separate ivory-tower architect required. Reviewing and choosing well. You read far more code than you write, and your value is in the quality of review: catching the silent assumption, the security flaw, the architectural drift, knowing where models fail and looking there first. You pick the right tool for the job (Claude Code for a deep refactor, an inline assistant when that is enough, a sub-agent for parallel work, the right model for analysis versus generation) and you know the constraints differ by client, an enterprise like PayPoint or Natwest versus a scale-up type business like Zuto or OAG. Working with non-determinism. You see where AI moves the bottleneck and help people left and right of you unblock the value stream. You build with AI components but know success is no longer a binary, reaching for evals, golden datasets, structured outputs and fallback paths as naturally as you reach for unit tests. Technical breadth across the full stack Exceptional means depth in at least one area but competence everywhere the system reaches. Backend: an instinct for distributed systems (what fails, what is eventually consistent, where queues back up), APIs that age well, thoughtful data modelling, and an understanding that languages are mostly syntax differences you can close with AI. Cloud: cost-aware and security-aware by default, reaching for IaC, composing the primitives rather than stitching together managed services and hoping it works. Data: modern pipelines, governance and lineage, increasingly vector stores and embeddings, with data quality treated as seriously as production code because garbage in, garbage out is far worse once AI features depend on it. Web and mobile: past the framework arguments, with a clear view on what you would pick today, and able to build \"good enough\" front ends yourself with AI. Full-stack here means seeing the platform as one system and knowing which levers matter most. It does not mean front-end work with a few Node.js servers. System thinking, consulting and commercial judgement At CreateFuture we work in a consultancy context, where many otherwise excellent IC engineers can struggle. You know technology is roughly 30% of the picture; the rest is design, argument and reasoning, commercial and political acumen, and the clarity to frame outcomes for a COO, CTO, CIO or CEO in their own language. You know when gold-plating is wasteful, you can name when a project's real problem is not technical and say so even when it is awkward, and you have a strong sense of what is durable versus what is fashion. You are not the engineer who introduced the team to seven new technologies last year; you are the one who removed three and quietly made the remaining stack stronger. Leadership mentality Technical work is necessary but no longer sufficient. By default you raise the level of everyone around you, regardless of discipline. Communicate clearly and frequently (documents, decisions, post-mortems, design notes); the written artefact is the machine-readable context we can feed to AI later. Make decisions and own them. You don't escalate everything or hoard control, and you are willing to be the benevolent dictator when it is your turn. Mentor in AI fluency, not just code: tooling, prompting and review discipline, so your team is twice as productive a year from now. Need little line management. You communicate upwards, raise by exception, self-resolve, and can be trusted with financial controls. Disagree well. You tell people they are wrong with evidence and no ego, and you change your own mind when you are shown to be wrong. What we're not looking for The gifted engineer who sits in a silo. This is a team game. The one who is fluent with AI but ships without the guardrails and quality gates enterprise clients expect. The one with strong technical opinions who cannot justify them commercially and gets defensive when challenged. The pure manager who wants to orchestrate teams rather than get involved. This is about setting a new standard, not coordinating it. The engineer who will not immerse in a client environment. This role will mean on-site work and trusted relationships built in person. We are not going back to working away from the client and being bypassed. What we’ll offer you: We trust people to do their best work. That means flexibility over rigid rules, impact over activity, and real investment in your growth both professionally and personally. You’ll be part of a supportive, and friendly culture, surrounded by smart, curious people who care deeply about what they do. We offer flexible working, including hybrid and remote options. Our office hubs are located in Edinburgh, Leeds, Manchester, London and Bulgaria, with occasional travel to client sites or CreateFuture offices when needed. We trust you to manage your time balancing collaboration with client time and focused work. What matters is the impact you have, not how busy you look. Our hiring process We try to keep our hiring process clear, fair and respectful of your time. We aim to get back to everyone who applies and we will be upfront about where you are in the process. It usually looks like this: Call with our Talent Acquisition Team Role specific capability interview Depending on the role, we might also ask you to do a short presentation, a practical or technical task or have a values focused conversation. We will explain what is involved before anything happens. Inclusion at CreateFuture We believe diverse teams build better workplaces and better products. We want CreateFuture to be a place where people feel able to be themselves and do their best work. If you need any adjustments or support during the application process, just. We will do what we can to help. We look forward to your application!", "summaryDescription" : "Principal Engineer at CreateFuture. Skills: Architecture, Deep engineering, AI fluency, System thinking. Set AI up for success. Architect systems with clean interfaces", "postedDate" : "2026-06-14T04:24:28.772", "createdAt" : "2026-06-14T04:24:28.772", "lastUpdated" : "2026-06-15T05:24:45.498", "ingestTimestamp" : "2026-06-14T04:24:28.772", "mongoId" : "6a2c79f174d8ee00a0943d36", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Deep engineering foundations", "System thinking", "AI fluency", "Context engineering", "Code review", "Tool selection", "Non-determinism handling", "Evals", "Golden datasets", "Structured outputs", "Outcome obsessed", "Intellectually honest", "Deeply pragmatic", "Relentlessly curious", "Architecture", "Deep engineering", "System design", "Decision making", "Review judgement", "Force multiplier", "SME", "Intellectual honesty", "Pragmatism", "Bias toward delivery", "Curiosity", "Knowledge bases", "Machine-readable specs", "Non-determinism", "Value stream", "Fallback path", "Roadmap planning", "Enterprise clients", "Scale-up businesses", "AI models", "Inference calls", "Claude Code", "Claude Opus" ], "skillCount" : 37, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 1.0, "_score" : 687.1849, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2af78274d8ee00a073d61f", "title" : "Director, Principal Patient Safety Scientist", "company" : "AstraZeneca", "industry" : "Pharma", "salary" : { "min" : 120000.0, "max" : 180000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Director, Principal Patient Safety Scientist in Barcelona, Spain, adjusted for industry and seniority." }, "location" : "Spain", "locations" : [ "Spain" ], "timestamp" : "2026-06-14T22:50:05.949", "fingerprint" : "327e7d7381b4683d1eeb640cceb5b2f84c8341f08143893c415a6a79afd52687", "source" : "workday", "language" : "en", "applyUrl" : "https://astrazeneca.wd3.myworkdayjobs.com/Careers/job/Spain---Barcelona/Director--Principal-Patient-Safety-Scientist_R-254242", "externalId" : "R-254242", "industryFunction" : { }, "locationPoint" : "40.4637,-3.7492", "structuredLocations" : [ { "city" : "Barcelona", "country" : "Spain", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "41.3825802,2.1770730" } ], "locationText" : "Barcelona, Spain", "employmentType" : "FULL_TIME", "minimumEducation" : "Life sciences/pharmacy/nursing degree", "experienceLevel" : "Director", "professionalSkills" : [ "Risk management planning", "Pharmacovigilance strategy", "Drug development" ], "hardSkillsList" : [ "Safety document strategy", "Regulatory reporting", "Risk evaluation", "Safety issue resolution" ], "softSkillsList" : [ "Leadership", "Mentorship" ], "hardSkills" : [ { "name" : "Safety document strategy", "level" : "intermediate" }, { "name" : "Regulatory reporting", "level" : "intermediate" }, { "name" : "Risk evaluation", "level" : "intermediate" }, { "name" : "Safety issue resolution", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentorship" } ], "majorSkills" : "Patient Safety, Pharmacovigilance, Risk Management", "majorSkillsList" : [ "Patient Safety", "Pharmacovigilance", "Risk Management" ], "coreResponsibilities" : "Lead strategy for proactive pharmacovigilance, Lead risk management planning, Prepare safety aspects of Global Risk Management Plans, Prepare Risk Evaluation and Mitigation Strategies (REMS), Provide subject matter expertise, Lead cross-functional process improvement initiatives, Perform duties as Safety Strategy and Management Team, Lead presentation of complex issues, Lead safety strategy for periodic regulatory documents, Lead safety strategy for regulatory submissions, Lead negotiations for contracts/agreements, Provide expertise to PS component of contracts, Lead resolution of complex safety issues, Mediate cross-functional agreement, Participate in due diligence activities, Provide training to GSPs, Provide mentorship to PV Scientists", "teamCollaboration" : "Cross-functional process improvement; Safety Information Review Committee; Global Safety Physician partnership", "domainKnowledge" : "Pharmacovigilance regulations; Drug development stages; Risk Management Strategies; Regulatory submissions", "domainList" : [ "pharmacovigilance-regulations", "drug-development-stages", "risk-management-strategies", "regulatory-submissions" ], "domainSpecificKnowledge" : [ "Pharmacovigilance regulations", "Drug development stages", "Risk Management Strategies", "Regulatory submissions" ], "communicationSkills" : "Executive presentations", "documentationSkills" : "Safety documents; Regulatory reports", "problemSolvingSkills" : "Complex safety issues", "qualificationsBasic" : "Life sciences/pharmacy/nursing degree, Advanced Patient Safety experience, Advanced Clinical Drug Development experience, Fluent in English, Advanced knowledge of PV regulations", "qualificationsPreferred" : "MD/MSc/PhD in scientific discipline, Advanced understanding of epidemiology", "remoteFriendly" : false, "workSiteFlexibility" : "Hybrid", "rawDescription" : "**Location:** Barcelona - Spain (3 days working from the office and 2 days working from home) **Introduction:** The Director, Principal Patient Safety Scientist role provides expertise to multiple and/or single but complex products in different stages of development as needed. He/she provides oversight of safety documents and deliverables for these projects in collaboration with the Global Safety Physician (GSP) and other PV Scientists. He/she leads PV strategy for safety documents and regulatory reports. **Main Responsibilities:** * Leads the strategy for proactive pharmacovigilance and risk management planning of complex or multiple products, including preparation of the safety aspects of Global Risk Management Plans and Risk Evaluation and Mitigation Strategies (REMS) in partnership with the GSP and others as appropriate. * Provides subject matter expertise in the therapeutic area and across multiple products. * Has the ability to lead cross-functional process improvement or other initiatives on behalf of the Patient Safety organization. * Performs duties as a Safety Strategy and Management Team (SSaMT) Leader for complex and/or multiple products. * As a Safety expert leads presentation of complex issues to Safety Information Review Committee (SIRC). * Leads safety strategy for multiple or complex periodic regulatory documents (PBRERs, PSURs, DSURs) according to the agreed process and timelines. * Leads safety strategy for regulatory submissions of new products, formulations or indications (NDA/BLA, MAA), in partnership with the GSP and other functional experts. * Leads negotiations and provides expertise to the PS component of contracts/agreements with third parties to ensure quality and integrity of agreements. * Takes accountability and leads resolution of complex safety issues and mediates cross-functional agreement. * Has the ability to participate in due diligence activities. * As a safety expert, provides training and mentorship to new GSPs and PV Scientists in approved processes and systems. **Requirements – Education and Experience** * A life sciences/pharmacy/nursing degree, and advanced Patient Safety and/or Clinical/ Drug Development experience * Fluent in written and verbal English * Advanced knowledge of PV regulations * MD/MSc/PhD in scientific discipline, preferred * Advanced understanding of epidemiology, preferred **Date Posted** 10-jun-2026 **Closing Date** 23-jun-2026 AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.", "summaryDescription" : "Director, Principal Patient Safety Scientist at AstraZeneca. Skills: Patient Safety, Pharmacovigilance, Risk Management. Lead strategy for proactive pharmacovigilance. 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Example: Professional Engineer (PE or P.Eng) license. Extensive experience in project execution Proficient computer skills in Microsoft Office as well as standard design software. Must be comfortable being viewed as a technical expert in engineering analysis and design and have proven background of technical leadership on these types of projects An attitude and commitment to being an active participant of our employee-owned culture What We Believe HDR is our company. Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve. Our Commitment As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day. Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees. At HDR, the health and safety of our employees is of the upmost importance. In accordance with local safety, health, and environmental legislation, HDR is committed to developing, maintaining, and enforcing proactive safe work policies, procedures, and standards. In accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and other applicable legislation, we are committed to meeting the accessibility needs of persons with disabilities. Candidates with disabilities may request reasonable accommodation throughout the recruitment and selection process by contacting our Human Resources team. 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Work with ODMs; Work with vendors; Cross-boundary triaging; Resolve issues across organization", "domainKnowledge" : "Cloud server infrastructure; Machine Learning Acceleration; SoCs; Servers; Systems; IC package; Air-cooled systems; Liquid-cooled systems; Heatsink solutions; Thermal Interface Materials; Liquid cooling technologies; Thermal control algorithms; Power management algorithms", "domainList" : [ "cloud-server-infrastructure", "machine-learning-acceleration", "socs", "servers", "systems", "ic-package", "air-cooled-systems", "liquid-cooled-systems", "heatsink-solutions", "thermal-interface-materials", "liquid-cooling-technologies", "thermal-control-algorithms", "power-management-algorithms" ], "domainSpecificKnowledge" : [ "Cloud server infrastructure", "Machine Learning Acceleration", "SoCs", "Servers", "Systems", "IC package", "Air-cooled systems", "Liquid-cooled systems", "Heatsink solutions", "Thermal Interface Materials", "Liquid cooling technologies", "Thermal control algorithms", "Power management algorithms" ], "toolProficiency" : [ "Ansys Icepak", "FloTherm", "Cadence Celsius", "PTC Creo", "Solidworks" ], "innovationCreativity" : "Accelerates innovation; Design silicon and software; Build next generation infrastructure; Integration of emergent technologies", "problemSolvingSkills" : "Troubleshooting; Debugging", "outcomesObjectives" : "Deliver world-class customer experience; Improve product performance; Improve product quality; Improve product cost", "qualificationsBasic" : "BS or MS degree, 10+ years industry experience, 3+ years SoC Thermal modelling, Experience with Chip package, Collaborate effectively with teams, Work with ODMs, vendors, teams", "qualificationsPreferred" : "Knowledge of SoC thermal/mechanical design, Programming experience: Bash script, Shell script, Linux, Python, and Lua, Working knowledge on fans, valves, chillers, and CDUs, Knowledge of various types of technologies, Develop detailed CFD and compact RC models, Knowledge of hardware and software based thermal / power management, Optimize thermal solutions under PPA, Simulate and prototype thermal control strategies, Validate thermal models through measurements", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Annapurna Labs (our organization within AWS Utility Computing) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. We are seeking experienced Hardware Design Engineers to build the next generation of our cloud server infrastructure. Our success depends on our world-class server infrastructure; we’re handling massive scale and rapid integration of emergent technologies. As a member of the Machine Learning Acceleration team you’ll be responsible for the design and optimization of hardware in our data centers. You’ll provide leadership in the application of new technologies to large scale server deployments in a continuous effort to deliver a world-class customer experience. This is a fast-paced, intellectually challenging position, and you’ll work with thought leaders in multiple technology areas. You’ll have high standards for yourself and everyone you work with, and you’ll be constantly looking for ways to improve your products performance, quality and cost. We’re changing an industry, and we want individuals who are ready for this challenge and want to reach beyond what is possible today. Key job responsibilities As a Mechanical Engineer, you design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You develop from the lowest levels of circuit design to large system design including thermal solutions and see those systems all the way through to high volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of AWS users. About the team In 2015, Annapurna Labs was acquired by Amazon Web Services (AWS). Since then, we have accelerated its innovation and developed a number of products that benefit cloud customers, including AWS Nitro technology, Inferentia custom Machine Learning chips, and AWS Graviton2 processors. Annapurna Labs is a silicon/system and software organization that is delivering all the chips used by AWS customers. Today this includes: Graviton, driving innovation for general purpose compute; Nitro, driving networking and storage scale, security and Hypervisor offload, and Machine Learning (ML) Trainium and Inferentia that are enabling customers to train and run GenAI applications permanently while keeping costs under control. Basic Qualifications: * BS or MS degree in Mechanical/Thermal Engineering * 10+ years industry experience in Mechanical and Thermal design of Systems * Experience in thermal and performance measurements and characterization on SoCs, Servers, and Systems * 3+ years of experience SoC Thermal modelling and IC package transient thermal response * Experience with Chip package, System Mechanical & Thermal design for air-cooled and liquid-cooled systems * Collaborate effectively with teams spanning multiple sites and develop detailed specifications for product teams to use * Work with ODMs, heatsink vendors, and internal design teams on cross-boundary triaging, debugging, and resolving issues across organization. Preferred Qualifications: * Knowledge of SoC thermal/mechanical design methodology, power modeling and thermal analysis techniques * Tool Familiarity: Ansys Icepak, FloTherm, Cadence Celsius, PTC Creo, and Solidworks * Programming experience: Bash script, Shell script, Linux, Python, and Lua. Familiarity with working in Linux environment is an added advantage * Working knowledge on fans, valves, chillers, and CDUs * Knowledge of various types of technologies used for Heatsink solutions, Thermal Interface Materials (TIMs) and liquid cooling technologies * Develop detailed CFD and compact RC models for SoC and Package thermal analysis * Knowledge of hardware and software based thermal / power management control algorithms * Optimize thermal solutions under PPA and system design constraints * Simulate and prototype thermal control strategies * Validate thermal models through power/thermal measurements on Hardware Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, Cupertino - 217,800.00 - 294,700.00 USD annually USA, TX, Austin - 189,400.00 - 256,200.00 USD annually", "summaryDescription" : "Principal Engineer at Annapurna Labs. Skills: Mechanical Engineering, Thermal Engineering, System Design, Data Center Infrastructure. Design and build systems. 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"Provide technical guidance, Mentor team members, Coach team members, Take responsibility for technical development, Liaise with key clients, Discuss design solutions, Discuss technical solutions, Liaise with Practice Managers, Ensure projects are resourced, Delegate work to team members, Program deliverables, Monitor progress, Identify project commercial risks, Respond to project commercial risks, Identify project commercial opportunities, Respond to project commercial opportunities, Support business in work winning, Represent business at networking events, Prepare bids, Prepare tenders, Establish client relationships, Maintain client relationships, Develop client relationships", "teamCollaboration" : "Cross-practice teams; Multi-discipline teams", "projectManagementSkills" : [ "Programming deliverables", "Monitoring progress" ], "domainKnowledge" : "Highway infrastructure", "domainList" : [ "highway-infrastructure" ], "domainSpecificKnowledge" : [ "Highway infrastructure" ], "communicationSkills" : "Client communication; Stakeholder communication; Technical communication", "continuousLearning" : "Professional development", "problemSolvingSkills" : "Analytical thinking; Problem solving; Complex issue resolution", "specialRequirements" : "Security clearance, 5 years UK residency", "qualificationsBasic" : "5+ years experience, Experience developing client relationships, Experience understanding client requirements, Experience working with clients to achieve objectives", "qualificationsPreferred" : "Security clearance required", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "### **Job Description** ## Overview **Shape a faster, smarter, safer future.** You might know us for the great work we do across our wide variety of projects. We're proud to say it's thanks to our people's diversity of thought, expertise and knowledge. And when you join us, you'll be a part of this genuinely collaborative environment, where everyone's voice is valued and treated equally. We're passionate about what we do, but we don't take ourselves too seriously. Simply put, this a great place to be. So, when it comes to your life outside of work, ask us about our flexible and remote working policies designed to help you get the most out of life. As a Principal Engineer in our Transportation team, you'll be pivotal in implementing ideas that shape the future of how we move. You'll collaborate across new build, renewal, maintenance, and assessment works, from our largest, most high-profile to our more progressive and specialised. Our clients include Department for Infrastructure, National Transport Authority, Highways England and Local Authority councils across UK and Ireland. With such size, scope and scale, you'll have plenty of opportunities to keep yourself challenged. ## Your role * Providing technical guidance on highway infrastructure projects. * Mentoring and coaching team members and taking responsibility for their technical development. * Liaise with key clients and be capable of discussing design / technical solutions to stakeholders including technical and non-technical Clients. * Liaising with Practice Managers, ensure that projects are sufficiently resourced. * Delegating work to team members, programming deliverables and monitoring progress. * Identify and respond to project commercial risks and opportunities. * Support the business in work winning including representing the business at networking events, preparing bids and tenders and establish, maintain and develop relationships with existing and prospective internal and external clients. ## About you * Able to demonstrate experience of developing strong and sustainable relationships with Clients, understanding their requirements and aspirations, and working effectively with them to achieve their objectives. * Excellent communication skills and stakeholder engagement. * Highly developed interpersonal and leadership skills with proven ability to build and motivate teams working across the practices. * A hard working and flexible individual, who is a team player, is reliable, proactive and shows initiative whilst able to keep cool under pressure and when working to often demanding deadlines. * A disciplined thinker and analytical, numerate, problem solver who has strategic judgement and the capacity to think complex issues through and develop effective solutions in a timely fashion. * A resourceful, articulate and clear communicator who can influence others through the use of sound judgement and good sense – a natural team player. * Self-motivated and able to work both independently as well as within a larger multi-discipline team in leading and managing packages of work to completion. * A high expectation of performance for themselves and other members of the team. ## Rewards & benefits Explore the rewards and benefits that help you thrive – at every stage of your life and your career. Enjoy competitive salaries, employee rewards and a brilliant range of benefits you can tailor to suit your own health, wellbeing, financial and lifestyle choices. Make the most of a myriad of opportunities for training and professional development to grow your skills and expertise. And combine our hybrid working culture and flexible holiday allowances to balance a great job and fulfilling personal life. [Be rewarded. Find out more.](https://careers.atkinsrealis.com/total-reward-uk) ## About AtkinsRéalis We're [AtkinsRéalis](https://careers.atkinsrealis.com/), a world-class engineering services and nuclear organization. We connect people, data and technology to transform the world's infrastructure and energy systems. Together, with our industry partners and clients, and our global team of consultants, designers, engineers and project managers, we can change the world. We're committed to leading our clients across our various end markets to engineer a better future for our planet and its people. [Find out more.](https://careers.atkinsrealis.com/) ## Additional information **Security clearance** This role may require security clearance and offers of employment will be dependent on obtaining the relevant level of clearance. If this is necessary, it will be discussed with you at interview. The vetting process is delivered by United Kingdom Security Vetting (UKSV) and may require candidates to provide proof of residency in the UK of 5 years or longer. If applying to this role please do not make reference to (in conversation) or include in your application or CV, details of any current or previously held security clearance. We are committed to creating a culture where everyone feels that they belong - a place where we can all be ourselves, thrive and develop to be the best we can be. So, we offer a range of family friendly, inclusive employment policies, flexible working arrangements and employee resource groups to support all employees. As an Equal Opportunities Employer, we value applications from all backgrounds, cultures and ability. **#LI-UK#LI-ATKINS #LI-Transportation #LI-UKI** ### **Worker Type** Employee ### **Job Type** Regular _At_ _AtkinsRéalis_ _, we seek to hire individuals with diverse characteristics, backgrounds and perspectives. We strongly believe that world-class talent makes no distinctions based on gender, ethnic or national origin, sexual identity and orientation, age, religion or disability, but enriches itself through these differences._", "summaryDescription" : "Principal Engineer at AtkinsRéalis. Skills: Highway infrastructure, Client relationship management, Team leadership. Provide technical guidance. 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editing", "majorSkillsList" : [ "Therapeutics Engineering", "Cellular assays", "Molecular biology", "Gene editing" ], "coreResponsibilities" : "Conduct cellular screening assays, Optimize cellular screening assays, Troubleshoot cellular screening assays, Expression characterization of biologics, Functional characterization of biologics, Drive development of cutting-edge assays, Pilot development of cutting-edge assays, Oversee development of cutting-edge assays, Design combinatorial libraries, Procurement combinatorial libraries, Maintenance combinatorial libraries, Identification of external partners, Management of external partners, Execute molecular biology techniques, Culture mammalian cell lines, Maintain mammalian cell lines, Develop cell lines, Analyze assay data, Interpret assay data, Maintain laboratory notebooks, Communicate results in team meetings, Drive optimization of screening protocols, Drive automation of screening protocols, Develop DNA assets for molecular library design", "teamCollaboration" : "Cross-functional scientific team; Close-knit team; Experimental scientists; Computational scientists", "domainKnowledge" : "Epigenetic editing platform; Gene expression modification; Novel medicines; Drug discovery; Pharmaceutical R&D; Biologics modalities; Cell systems; Gene delivery technologies; CRISPR; Gene editing technologies", "domainList" : [ "epigenetic-editing-platform", "gene-expression-modification", "novel-medicines", "drug-discovery", "pharmaceutical-r-d", "biologics-modalities", "cell-systems", "gene-delivery-technologies", "crispr", "gene-editing-technologies" ], "domainSpecificKnowledge" : [ "Epigenetic editing platform", "Gene expression modification", "Novel medicines", "Drug discovery", "Pharmaceutical R&D", "Biologics modalities", "Cell systems", "Gene delivery technologies", "CRISPR", "Gene editing technologies" ], "toolProficiency" : [ "GraphPad Prism", "Benchling", "SnapGene" ], "communicationSkills" : "Communicate results clearly; Written communication; Verbal communication; Convey results; Convey scientific data", "documentationSkills" : "Maintain accurate laboratory notebooks", "innovationCreativity" : "Emphasis on innovation; Innovative; Novel epigenetic editing platform; Novel biologics modalities; Cutting-edge assays", "problemSolvingSkills" : "Proactively troubleshoot assays; Analyze assay data; Interpret assay data", "outcomesObjectives" : "Treat a variety of diseases; Bring novel medicines to patients; Product generation engine", "qualificationsBasic" : "PhD in Cell or Molecular Biology, Biochemistry, or related disciplines, 2+ years relevant experience in biotech or pharma, Hands-on experience in cell-based assays, Hands-on experience in library screening assays, Extensive experience in gene design, Extensive experience in vector construction, Extensive experience in protein expression, Possession of communication skills, both written and verbal", "qualificationsPreferred" : "Industry experience in drug discovery, Industry experience in pharmaceutical R&D", "rawDescription" : "About FL114: FL114 is an innovative, privately held biotechnology company developing our novel epigenetic editing platform to treat a variety of diseases through precise, tunable modification of gene expression. FL114 was founded by Flagship Pioneering, where companies such as Moderna Therapeutics (NASDAQ: MRNA) and Seres Therapeutics (NASDAQ: MCRB) were conceived and created. With a strong emphasis on innovation and experimental execution, FL114 cultivates a highly dynamic and entrepreneurial environment. About the Role: FL114, Inc. is seeking a Senior Scientist to join our integrated Platform as a key contributor in our Therapeutics Engineering efforts. The successful candidate will be an essential member of a close-knit team of experimental and computational scientists driving FL114’s product generation engine and supporting a broad set of therapeutic programs. We are looking for enthusiastic, detail-oriented, adaptive, and highly motivated individuals with a passion for bringing novel medicines to patients. Applicants should be comfortable working on a fast-paced, cross-functional scientific team. Key Responsibilities: Independently conduct, optimize and proactively troubleshoot cellular screening assays in a wide range of primary and transformed cell lines. Expression and functional characterization of novel biologics modalities using various cell systems and techniques (cell-based assays, RNA/DNA/protein isolation and detection techniques, RT-qPCR, flow cytometry, etc.) Drive, pilot, and oversee development of a wide range of cutting-edge assays. Design, procurement, and maintenance of combinatorial libraries for relevant cell-based and cell-free assays. Identification and management of external partners (CROs, CMOs, etc). Required Skills: Execute routine and advanced molecular biology techniques, including plasmid preparation, RT-qPCR, cloning, RNA/DNA extraction, gel electrophoresis, oligo pool work, etc. Culture and maintain a wide variety of mammalian cell lines, including transient and stable transfections. Develop cell lines as necessary. Analyze and interpret assay data, maintain accurate laboratory notebooks, and communicate results clearly in team meetings. Drive optimization and automation of screening protocols, including the use of liquid handling systems and plate readers. Experience developing DNA assets for molecular library design. Experience with gene delivery technologies (for example LNP, lentivirus, etc.). Exposure to CRISPR-based or other gene editing technologies. Exposure to NGS data sets and its interpretation. Familiarity with data analysis tools such as GraphPad Prism, Benchling, SnapGene, etc. Adaptive and detail-oriented with excellent time management and organizations skills. Exceptional teamwork and communication skills. Required Qualifications: PhD in Cell or Molecular Biology, Biochemistry, or related disciplines with 2+ years of relevant experience in biotech or pharma. Strong background in cellular and molecular biology with hands-on experience in the development and optimization of cell-based assays and library screening assays. Extensive experience in gene design, vector construction, and protein expression. Possession of strong communication skills, both written and verbal, to clearly convey results and scientific data to senior leaders, teams and partners. Industry experience in drug discovery or pharmaceutical R&D preferred. About Flagship Flagship Pioneering is a scientific innovation engine that invents and builds companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps in human health, sustainability, and beyond. What sets Flagship apart is our ability to advance biotechnology by uniting life science innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our team of scientists, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and create breakthroughs for the benefit of people and planet. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been named four times to Fast Company’s annual list of the World’s Most Innovative Companies. At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background. Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto. Privacy Notice for Applicants: When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com. The salary range for this role is $126,000 - $159,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL114 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL114's good faith estimate as of the date of publication and may be modified in the future. Privacy Notice for Applicants: When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.", "summaryDescription" : "Senior Scientist, Therapeutics Engineering at Flagship Pioneering, Inc.. Skills: Therapeutics Engineering, Cellular assays, Molecular biology, Gene editing. Conduct cellular screening assays. 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Hiring teams; Recruiter and researcher teams; Technical and business leaders", "projectManagementSkills" : [ "Executive search processes" ], "domainKnowledge" : "Senior engineering talent; Technology sectors; Technical domains; Principal Engineers; Senior Principal Engineers", "domainList" : [ "senior-engineering-talent", "technology-sectors", "technical-domains", "principal-engineers", "senior-principal-engineers" ], "domainSpecificKnowledge" : [ "Senior engineering talent", "Technology sectors", "Technical domains", "Principal Engineers", "Senior Principal Engineers" ], "toolProficiency" : [ "HRIS", "ATS" ], "communicationSkills" : "Client updates; Market conditions", "problemSolvingSkills" : "Root cause analysis", "outcomesObjectives" : "Shape future engineering community; Improve talent acquisition capabilities", "qualificationsBasic" : "7+ years recruiting experience, Bachelor's degree or above, Recruit and hire engineering candidates, Manage complex executive search, Provide strategic talent counsel", "qualificationsPreferred" : "Experience with HRIS, Experience with ATS, Experience with interview process, Experience with onboarding process", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "As a client lead recruiter, you'll have the unique opportunity to impact leadership teams across Amazon's diverse technology landscape, building relationships with Directors and VPs while shaping the future of Amazon's senior engineering community. Key job responsibilities • Serve as the primary talent advisor to Directors and VPs, educating leaders on the external senior engineering talent landscape and market dynamics • Define and deliver recruiting strategies for highly-critical, sometimes confidential roles with broad cross-organizational impact • Identify and engage highly passive senior engineering candidates through creative, research-driven sourcing strategies • Build and cultivate robust talent networks across technology sectors, leveraging deep industry knowledge and relationships • Lead client update meetings on active searches, providing clear, data-driven insights on progress and market conditions • Provide candid guidance to executive leadership on matters related to top technical talent • Make sound judgments about candidate fit based on comprehensive analysis of technical depth and leadership impact • Conduct thorough candidate assessments, participate in debriefs, perform comprehensive reference checks, and present/negotiate employment offers • Coach leaders to continuously improve their talent acquisition capabilities at the senior level • Set exceptionally high standards for search quality, candidate experience, and recruiting excellence • Investigate deeply into technical domains, candidate backgrounds, and market trends to inform strategy A day in the life Your day begins with strategic planning sessions discussing talent gaps and market intelligence for critical Principal Engineer searches. You'll spend time researching and engaging passive candidates through personalized outreach, leveraging your extensive network and industry knowledge. Mid-day might involve leading a client update meeting where you present market analysis and candidate pipeline progress, followed by conducting in-depth technical assessments with potential candidates. You'll collaborate with your team of recruiters and researchers, sharing insights on emerging talent pools and coaching colleagues. Afternoons often include candidate debriefs with hiring teams, where you provide perspective on technical depth and leadership potential. You'll also dedicate time to building relationships with industry leaders and technical communities, staying ahead of market trends. Throughout the day, you'll make high-stakes decisions with incomplete information, balancing urgency with thoroughness to secure world-class engineering talent. About the team The Global Specialty Recruiting (GSR) team partners with technical and business leaders across all of Amazon's businesses to hire the company's most senior engineering talent. Our team specializes in recruiting Principal Engineers and Senior Principal Engineers– Amazon's most senior technical contributors who set the standard for engineering excellence and drive innovation across the company. Basic Qualifications: - 7+ years of progressive corporate or search firm recruiting work with a focus on passive engineering candidate generation in a high tech market experience - Bachelor's degree or above - • Demonstrated ability to recruit and hire engineering candidates. - • Proven track record of managing complex executive search processes including client management, candidate development, and offer negotiation - • Experience working with senior executives and providing strategic talent counsel Preferred Qualifications: - Experience with executive recruiting in either a blue-chip, global in-house executive search team, or a top executive search firm - Deep expertise in technology recruiting with ability to quickly learn new technical and product domains - Experience mentoring and developing other recruiters Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, SANTA CLARA - 157,100.00 - 212,600.00 USD annually USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually", "summaryDescription" : "Senior Recruiter, Principal Engineer Recruiting, PE Recruiting at Amazon.com Services LLC. Skills: Principal Engineer recruiting, Senior engineering talent, Talent strategy. Serve as talent advisor. Define recruiting strategies", "postedDate" : "2026-06-12T00:00:00.000", "createdAt" : "2026-06-14T09:29:11.531", "lastUpdated" : "2026-06-15T06:43:19.728", "ingestTimestamp" : "2026-06-14T09:29:11.531", "mongoId" : "6a2cc3ad74d8ee00a0a0a206", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10447918/apply", "salaryAnnualMin" : 142800, "salaryAnnualMax" : 193200, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Engineering candidate generation", "Technical assessments", "Reference checks", "Leadership", "Principal Engineer recruiting", "Senior engineering talent", "Talent strategy", "Talent advising", "Client management", "Candidate development", "Offer negotiation", "Market analysis", "Talent acquisition", "Executive search", "Executive search processes", "Technology sectors", "Technical domains", "Principal Engineers", "Senior Principal Engineers", "HRIS", "ATS" ], "skillCount" : 21, "jobCategory" : "operations", "jobSubcategory" : "hr", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "_score" : 653.71735, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2a60b674d8ee00a062058c", "title" : "Principal Scientist, Biologics Discovery & Innovation", "company" : "Sanofi", "industry" : "Biotechnology", "salary" : { "min" : 1200000.0, "max" : 2000000.0, "currency" : "CNY", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Principal Scientist in Biotech in Suzhou, China, adjusted for executive seniority and company size." }, "location" : "China", "locations" : [ "China" ], "timestamp" : "2026-06-12T14:14:54.685", "fingerprint" : "eea7f2dd512c03c9a1c7f202b8f3c2c6a32f41389008cb2a01bbf4b705ed9024", "source" : "workday", "language" : "en", "applyUrl" : "https://sanofi.wd3.myworkdayjobs.com/SanofiCareers/job/Suzhou-Jiangsu/R-D---Intrepide-Principal-Scientist-I--Biologics-Discovery---Innovation---SZ_R2859783", "externalId" : "R2859783", "industryFunction" : { }, "locationPoint" : "35.8617,104.1954", "structuredLocations" : [ { "city" : "Suzhou", "country" : "China", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "31.3111230,120.6212881" } ], "locationText" : "Suzhou, China", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Antibody discovery, Biologics discovery, Biologics engineering, Technology platforms, Antigen design, Recombinant protein design, Hapten conjugation, Cell-based immunization, Antibody discovery platforms, Display screening, Antibody formats, Single cell cloning, Bispecific antibodies, Multispecific antibodies, Antibody engineering, Affinity maturation, Humanization, Liability assessment, AI-driven screening, Machine learning, Automated workflows, Phage display, Yeast display, Ribosome display, Hybridoma technology", "professionalSkills" : [ "Technical leadership", "Program delivery", "Scientific execution", "Strategic execution", "Scientific insights", "Program milestones", "Discovery lead", "Hit identification", "Lead selection", "Program objectives", "Success criteria", "Milestone plans", "Discovery workflows", "Therapeutic pipelines", "Discovery platform", "Target biology", "Program requirements", "External landscape", "Discovery field", "Screening strategies", "Selection strategies", "Multi-target engagement", "Emerging modality", "Format innovation", "CRO partnerships", "Project scopes", "Quality standards", "Operational efficiency", "Scientific output", "Internal stakeholders", "External discovery", "Technical challenges", "Operational challenges", "Performance reviews", "Scientific standards", "Optimization", "Innovation", "Developable candidates", "Candidate progression", "Computational screening", "Laboratory automation" ], "hardSkillsList" : [ "Immunology", "Biochemistry", "Bioengineering", "Antigen engineering", "Functional screening", "Lead nomination", "Developability optimization" ], "softSkillsList" : [ "Leadership", "Mentorship" ], "hardSkills" : [ { "name" : "Immunology", "level" : "intermediate" }, { "name" : "Biochemistry", "level" : "intermediate" }, { "name" : "Bioengineering", "level" : "intermediate" }, { "name" : "Antigen engineering", "level" : "intermediate" }, { "name" : "Functional screening", "level" : "intermediate" }, { "name" : "Lead nomination", "level" : "intermediate" }, { "name" : "Developability optimization", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentorship" } ], "majorSkills" : "Biologics Discovery, Antibody Discovery, CRO Management, Platform Expertise", "majorSkillsList" : [ "Biologics Discovery", "Antibody Discovery", "CRO Management", "Platform Expertise" ], "coreResponsibilities" : "Serve as discovery lead or co-lead on critical, Oversee antigen design and immunization strategy, Oversee hit identification, screening, and lead selection, Design antigen engineering strategies, Execute antigen engineering strategies, Define clear program objectives, Define success criteria, Define milestone plans, Oversee hybrid discovery workflows, Integrate novel antibody technologies into therapeutic pipelines, Resolve bottlenecks to maintain program momentum, Provide authoritative technical leadership across antibody discovery platforms, Lead single cell cloning workflows campaigns, Optimize single cell cloning workflows, Guide teams on scientific applicability and limitations of, Scan external landscape for breakthrough technologies, Lead discovery campaigns for bispecific and multispecific antibodies, Apply specialized screening and selection strategies, Evaluate emerging modality-specific discovery approaches, Implement emerging modality-specific discovery approaches, Strategically coordinate external CRO partnerships, Define project scopes for CROs, Define deliverables for CROs, Define quality standards for CROs, Define timelines for CROs, Serve as primary interface between internal stakeholders and, Ensure seamless communication with external discovery resources, Ensure alignment of objectives with external discovery resources, Resolve technical or operational challenges with external discovery, Conduct regular performance reviews of CRO partners, Drive continuous improvement with CRO partners, Apply antibody engineering expertise to advance discovery leads, Champion adoption of innovative approaches, Champion AI-driven screening, Champion machine learning-assisted design, Champion automated workflows", "teamCollaboration" : "Cross-functional teams; External CRO resources; External discovery partners; Internal scientific capabilities; CRO deliverables; External partner commitments", "projectManagementSkills" : [ "Program management", "Project management" ], "domainKnowledge" : "Biologics discovery; Antibody discovery; Oncology; Immunology; Ophthalmology; CNS; Antibody modalities; Therapeutic pipelines", "domainList" : [ "biologics-discovery", "antibody-discovery", "oncology", "immunology", "ophthalmology", "cns", "antibody-modalities", "therapeutic-pipelines" ], "domainSpecificKnowledge" : [ "Biologics discovery", "Antibody discovery", "Oncology", "Immunology", "Ophthalmology", "CNS", "Antibody modalities", "Therapeutic pipelines" ], "communicationSkills" : "Translate complex discovery science", "innovationCreativity" : "Emerging biologics technologies; Innovative approaches; Transformative approaches; AI-driven screening; Machine learning-assisted design; Automated workflows", "problemSolvingSkills" : "Proactive resolution of technical or operational challenges; Creative problem-solving", "outcomesObjectives" : "Accelerated program delivery; Tangible program milestones; Critical development milestones; Streamline and accelerate discovery-to-candidate progression", "qualificationsBasic" : "5+ years antibody discovery, Ph.D. in Immunology, Biochemistry, Bioengineering, Deep, hands-on expertise in at least two of the following discovery platforms: phage display, yeast display, ribosome display, single cell cloning, or hybridoma technology, Proven experience in antigen design and immunization strategy, Hit identification and lead selection capabilities, Skilled and experienced in leading or co-leading cross-functional discovery teams", "qualificationsPreferred" : "Extensive industrial or advanced academic research experience, Proven experience in bispecific/multispecific antibody discovery, Nanobody/VHH programs experience, Hands-on experience with bispecific/multispecific antibody discovery formats, Nanobody/VHH discovery workflows experience, Working knowledge of antibody engineering disciplines", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "**Principal Scientist, Biologics Discovery & Innovation** **Location:** Suzhou, China **Position Summary** We are seeking an accomplished Principal Scientist with broad biologics knowledge and technical leadership expertise to drive global R&D projects through internal–CRO hybrid models. In this role, you will be a subject-matter expert for biologics discovery, engineering, and relevant technology platforms, validating new approaches and ensuring accelerated program delivery in areas such as oncology, immunology, ophthalmology, or CNS. Success requires managing multidisciplinary teams and external resources, applying advanced scientific and project skills to validate and co-lead biologics programs from concept to key milestones. This is a unique opportunity to operate at the intersection of scientific excellence and strategic execution. You will apply deep domain expertise to evaluate and champion emerging biologics technologies, translating scientific insights into tangible program milestones. Success in this role requires the ability to orchestrate multidisciplinary internal teams alongside external CRO resources, driving biologics programs from early concept through critical development milestones with rigor, agility, and collaborative leadership. **Key Responsibilities** **1\\. Antibody Discovery Program Leadership** * Serve as discovery lead or co-lead on critical antibody programs, overseeing the full arc from antigen design and immunization strategy through hit identification, screening, and lead selection. * Design and execute antigen engineering strategies—including recombinant protein design, hapten conjugation, and cell-based immunization approaches—to maximize the quality and diversity of immune responses. * Define clear program objectives, success criteria, and milestone plans to align cross-functional stakeholders and external discovery partners. * Oversee hybrid discovery workflows (internal + external) that integrate novel antibody technologies into therapeutic pipelines, proactively identifying and resolving bottlenecks to maintain program momentum. **2\\. Discovery Platform Expertise** * Provide authoritative technical leadership across a broad range of antibody discovery platforms, including display screening for diverse antibody formats. * Lead and optimize single B cell cloning workflows campaigns, ensuring robust hit identification and efficient progression to lead candidates. * Guide teams on the scientific applicability, limitations, and optimal deployment of each discovery platform within the context of specific target biology and program requirements. * Stay at the forefront of the discovery field, continuously scanning the external landscape for breakthrough technologies and methodologies that could accelerate or differentiate the pipeline. **3\\. Advanced Antibody Modalities** * Lead discovery campaigns for bispecific and multispecific antibodies, applying specialized screening and selection strategies tailored to complex, multi-target engagement requirements. * Evaluate and implement emerging modality-specific discovery approaches, ensuring the organization remains at the cutting edge of antibody format innovation. **4\\. CRO Management & Hybrid Workflow Execution** * Strategically coordinate external CRO partnerships—defining project scopes, deliverables, quality standards, and timelines—to maximize operational efficiency and scientific output across discovery programs. * Serve as the primary interface between internal stakeholders and external discovery resources, ensuring seamless communication, alignment of objectives, and proactive resolution of technical or operational challenges. * Conduct regular performance reviews of CRO partners, driving continuous improvement and ensuring deliverables consistently meet internal quality and scientific standards. **5\\. Engineering-Supported Optimization & Innovation** * Apply antibody engineering expertise—including affinity maturation, humanization, and liability assessment—as a supporting capability to advance discovery leads toward developable candidates. * Champion the adoption of innovative and transformative approaches, including AI-driven screening, machine learning-assisted design, and automated workflows, to meaningfully streamline and accelerate discovery-to-candidate progression. **Qualifications** **Educational Background & Experience** * Ph.D. in Immunology, Biochemistry, Bioengineering, or a closely related discipline; extensive industrial or advanced academic research experience strongly preferred. * 5+ years of experience in antibody discovery, with demonstrated primary expertise in display technologies, B cell-based discovery, hit identification, and lead selection. * Proven experience in bispecific/multispecific antibody discovery and/or nanobody/VHH programs strongly preferred. * Demonstrated success managing complex, multi-stakeholder discovery programs, ideally involving CRO partnerships in a global and cross-cultural context. **Technical & Scientific Expertise — Discovery-Primary** * Primary (Required): Deep, hands-on expertise in at least two of the following discovery platforms: phage display, yeast display, ribosome display, single B cell cloning, or hybridoma technology. * Primary (Required): Proven experience in antigen design and immunization strategy, with a track record of generating high-quality, diverse antibody hits against challenging targets. * Primary (Required): Strong hit identification and lead selection capabilities, including functional screening design, triage strategies, and lead nomination criteria. * Advanced Modalities (Strongly Preferred): Hands-on experience with bispecific/multispecific antibody discovery formats and/or nanobody/VHH discovery workflows. * Supporting (Complementary): Working knowledge of antibody engineering disciplines—affinity maturation, humanization, liability engineering, and developability optimization—to support lead progression. * Proven ability to critically evaluate, validate, and implement new discovery platforms or methodologies, consistently balancing scientific rigor with practical development timelines. * Strong track record of scientific contributions, including peer-reviewed publications, patents, or significant internal program milestones demonstrating creative problem-solving in antibody discovery. **Program & Collaboration Skills** * Skilled and experienced in leading or co-leading cross-functional discovery teams, effectively aligning internal scientific capabilities with CRO deliverables and external partner commitments. * Strong organizational and project management abilities, with a consistent record of ensuring discovery milestones are met, risks are proactively managed, and resources are efficiently deployed. * Exceptional communicator who can fluently translate complex discovery science into clear, actionable plans for diverse stakeholders—including bench scientists, project managers, and senior leadership. **Innovation & Mentorship** * Adept at identifying and working with novel solutions—such as AI-based antigen design, computational screening, and laboratory automation—to meaningfully accelerate discovery programs. * Deeply committed to developing scientific talent, generously sharing discovery expertise, and cultivating a team culture defined by continuous innovation, intellectual openness, and collaborative excellence. **** # Pursue _progress_ , discover _extraordinary_ Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people. At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, ability or gender identity. Watch our [ALL IN video](https://www.youtube.com/watch?v=SkpDBZ-CJKw&t=67s) and check out our Diversity Equity and Inclusion actions at [sanofi.com](https://www.sanofi.com/en/our-responsibility/equality-and-inclusiveness)!", "summaryDescription" : "Principal Scientist, Biologics Discovery & Innovation at Sanofi. Skills: Biologics Discovery, Antibody Discovery, CRO Management, Platform Expertise. Serve as discovery lead or co-lead on critical. 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"hardSkills" : [ { "name" : "Electrical systems design", "level" : "intermediate" }, { "name" : "Electrical sub-assemblies design", "level" : "intermediate" }, { "name" : "Fabrication and test", "level" : "intermediate" }, { "name" : "System-level integration", "level" : "intermediate" }, { "name" : "Hardware testing", "level" : "intermediate" }, { "name" : "Instrumentation", "level" : "intermediate" }, { "name" : "Performance verification", "level" : "intermediate" }, { "name" : "CV analysis", "level" : "intermediate" }, { "name" : "IV analysis", "level" : "intermediate" }, { "name" : "Dit analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Ownership-driven mindset" }, { "name" : "Influence without authority" } ], "majorSkills" : "Electrical systems design, System architecture, System integration, Technical leadership", "majorSkillsList" : [ "Electrical systems design", "System architecture", "System integration", "Technical leadership" ], "coreResponsibilities" : "Lead design and development of electrical systems, Lead development of electrical sub-assemblies, Set technical direction, Ensure alignment with product architecture, Lead fabrication of electrical test structures, Lead test of electrical test structures, Own system-level integration, Ensure electrical elements work cohesively, Ensure mechanical elements work cohesively, Ensure control elements work cohesively, Define digital I/O architectures, Validate digital I/O architectures, Define analog I/O architectures, Validate analog I/O architectures, Drive technical decision-making, Review engineering changes, Approve engineering changes, Ensure technical integrity, Mitigate risk, Adhere to timelines, Contribute in design reviews, Provide expert guidance, Ensure readiness for production release, Define system validation strategies, Oversee system validation strategies, Oversee hardware testing, Oversee instrumentation, Oversee performance verification, Analyze electrical test data, Understand electrical test data, Interpret electrical test data, Guide process development, Guide integration of ASM's products, Evaluate feasibility of new concepts, Evaluate feasibility of new technologies, Solve complex system-level challenges, Influence global cross-functional teams, Collaborate with global cross-functional teams, Act as electrical domain expert, Mentor junior engineers, Guide junior engineers, Elevate technical capability, Drive high-quality technical documentation, Drive reporting standards, Drive stakeholder alignment", "teamCollaboration" : "Global cross-functional teams; International engineering teams", "projectManagementSkills" : [ "New product development", "Capital projects" ], "domainKnowledge" : "Semiconductor equipment; Semiconductor logic; Memory applications; ALD films", "domainList" : [ "semiconductor-equipment", "semiconductor-logic", "memory-applications", "ald-films" ], "domainSpecificKnowledge" : [ "Semiconductor equipment", "Semiconductor logic", "Memory applications", "ALD films" ], "toolProficiency" : [ "AutoCAD", "JMP" ], "communicationSkills" : "Technical discussions", "documentationSkills" : "Technical documentation", "innovationCreativity" : "Innovative approach", "problemSolvingSkills" : "Technical problem-solving; System-level challenges", "qualificationsBasic" : "Master's or PhD in Electrical and Electronics Engineering, Minimum 5 years of experience in system engineering, Expertise in electrical hardware design, Expertise in system architecture, Expertise in integration, Proficiency in AutoCAD, Proficiency in data analysis tools, Hands-on experience in hardware testing, Hands-on experience in instrumentation, Hands-on experience in system validation, Communication skills in English", "qualificationsPreferred" : "Experience as technical lead, Experience as subject matter expert, Understanding of semiconductor processes, Understanding of equipment architecture, Experience defining system validation strategies, Experience improving system validation strategies, Experience defining test methodologies, Experience improving test methodologies, Familiarity with data analysis tools, Familiarity with scripting tools, Proven track record of driving cost reduction, Proven track record of reliability improvements, Proven track record of product innovation, Experience working across regions, Experience working with international engineering teams", "workSiteFlexibility" : "Onsite", "rawDescription" : "Step into a career with ASM, where cutting edge technology meets collaborative culture. For over 55 years ASM has been ahead of what’s next, at the forefront of innovation and what’s technologically possible. With more than 4,500 ASMers representing 70 nationalities, our people and our advanced semiconductor devices are playing a crucial role in trends such as 5G, cloud computing, AI, and autonomous driving.  But we’re more than just a tech company. We value diversity, inclusion and sustainability as we strive to make a positive impact on the world. Our development programs help support your growth, shaping your future and pushing the boundaries of innovation to unleash potential. Job's mission As a Principal Engineer, Electrical Engineering at ASM, you will act as a technical lead for electrical systems within advanced semiconductor equipment. You will drive system-level design decisions, ensuring robust architecture, seamless integration, and high-performance delivery. By combining deep technical expertise with strong ownership, you will guide the development of complex systems from concept through production while influencing cross-functional engineering outcomes. What you will be working on Lead the design and development of electrical systems and sub-assemblies, setting technical direction and ensuring alignment with product architecture Lead fabrication and test of electrical test structures (ex. MOS capacitors, MIM capacitors, FETs) for semiconductor logic and memory applications Own system-level integration, ensuring electrical, mechanical, and control elements work cohesively to meet performance, safety, and reliability targets Define and validate digital and analog I/O architectures, enabling flexible, customer-specific configurations Drive technical decision-making across new product development, capital projects, and system improvements Review and approve engineering changes, ensuring technical integrity, risk mitigation, and adherence to timelines Act as a key contributor in design reviews, providing expert guidance and ensuring readiness for production release Define and oversee system validation strategies, including hardware testing, instrumentation, and performance verification Analyze, understand and interpret electrical test data (ex. CV, IV, Dit) to guide process development and integration of ASM's products such as ALD films Evaluate feasibility of new concepts and technologies, solving complex system-level challenges with a structured and innovative approach Influence and collaborate with global cross-functional teams, acting as the electrical domain expert Mentor and guide junior engineers, elevating technical capability within the team Drive high-quality technical documentation, reporting standards, and stakeholder alignment What we are looking for Master’s or PhD in Electrical and Electronics Engineering Minimum 5 years of experience in system engineering within semiconductor equipment manufacturing Strong expertise in electrical hardware design, system architecture, and integration (e.g., reactors, plasma sources, or similar systems) Proven ability to lead technical problem-solving and make system-level design decisions Proficiency in AutoCAD and data analysis tools such as JMP Hands-on experience in hardware testing, instrumentation, and system validation Ability to operate effectively in a fast-paced, global engineering environment Strong communication skills in English, with the ability to influence technical discussions What sets you apart Experience acting as a technical lead or subject matter expert on complex engineering projects Strong understanding of semiconductor processes and equipment architecture Experience defining or improving system validation strategies and test methodologies Familiarity with data analysis or scripting tools (e.g., Python) Proven track record of driving cost reduction, reliability improvements, or product innovation Experience working across regions or with international engineering teams Proactive, ownership-driven mindset with the ability to influence without formal authority Apply today to be part of what’s next. We make the tech that enables the chips in devices which improve lives around the world. We do this with an eye to the future, pushing the boundaries of what’s possible through cutting-edge innovation, and driving the next wave of technological breakthroughs that shape how we live, work, and connect. To learn more about ASM, find us at asm.com and on LinkedIn, Facebook, Instagram, X and YouTube. ASM is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, age, nationality, social or ethnic origin, sexual orientation, gender, gender identify or expression, marital status, pregnancy, political affiliation, disability, genetic information, veteran status, or any other characteristic protected by law.", "summaryDescription" : "Principal Engineer, Electrical Engineering at ASM. Skills: Electrical systems design, System architecture, System integration, Technical leadership. Lead design and development of electrical systems. Lead development of electrical sub-assemblies", "postedDate" : "2026-06-11T20:33:10.119", "createdAt" : "2026-06-11T20:33:10.119", "lastUpdated" : "2026-06-14T21:56:58.590", "ingestTimestamp" : "2026-06-11T20:33:10.119", "mongoId" : "6a2aa61574d8ee00a06b786a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Electrical systems design", "Electrical sub-assemblies design", "Fabrication and test", "System-level integration", "Hardware testing", "Instrumentation", "Performance verification", "CV analysis", "IV analysis", "Dit analysis", "Ownership-driven mindset", "Influence without authority", "System architecture", "System integration", "Technical leadership", "System engineering", "Cross-functional collaboration", "Technical decision-making", "Risk mitigation", "Process development", "Stakeholder alignment", "Cost reduction", "Reliability improvements", "Product innovation", "New product development", "Capital projects", "Semiconductor equipment", "Semiconductor logic", "Memory applications", "ALD films", "AutoCAD", "JMP" ], "skillCount" : 32, "jobCategory" : "engineering", "jobSubcategory" : "su3.platform-common-engineering", "dataQualityScore" : 0.8888889, "_score" : 645.8567, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Semiconductor Equipment Manufacturing" }, { "id" : "6a2adaa174d8ee00a071c4df", "title" : "Principal Engineer", "company" : "Wells Fargo", "salary" : { "min" : 6000000.0, "max" : 9000000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Principal Engineer in Bengaluru, India, adjusted for executive seniority in the banking industry." }, "location" : "Bengaluru, India", "locations" : [ "Bengaluru, India" ], "certifications" : [ "AWS Solutions Architect", "Azure Architect Expert", "GCP Professional Cloud Architect" ], "timestamp" : "2026-06-14T23:33:46.643", "fingerprint" : "df74639f5d5ea1e67953b050edda4fc48c80dbedda8e062a6f76d99deb67cc38", "source" : "workday", "language" : "en", "applyUrl" : "https://wd1.myworkdaysite.com/recruiting/wf/WellsFargoJobs/job/Bengaluru-India/Principal-Engineer_R-552269", "externalId" : "R-552269", "locationPoint" : "12.97194,77.59369", "structuredLocations" : [ { "city" : "Bengaluru", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, India", "employmentType" : "FULL_TIME", "experienceMinYears" : 7, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "OpenShift, Kubernetes, Docker, Terraform, Ansible, CloudFormation, Jenkins, ArgoCD, GitHub Actions, Python, Go, Java, Node.js, Istio, Linkerd", "professionalSkills" : [ "System design", "API integration", "Technical documentation", "Cloud security", "Cloud networking", "Cloud monitoring", "Cost management", "DevSecOps", "FinOps", "Cloud governance" ], "hardSkillsList" : [ "Infrastructure as Code", "CI/CD pipelines", "GitOps practices", "Microservices", "Distributed systems", "Event-driven architectures" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Infrastructure as Code", "level" : "intermediate" }, { "name" : "CI/CD pipelines", "level" : "intermediate" }, { "name" : "GitOps practices", "level" : "intermediate" }, { "name" : "Microservices", "level" : "intermediate" }, { "name" : "Distributed systems", "level" : "intermediate" }, { "name" : "Event-driven architectures", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Cloud engineering, Software engineering, Architecture, DevOps", "majorSkillsList" : [ "Cloud engineering", "Software engineering", "Architecture", "DevOps" ], "coreResponsibilities" : "Act as advisor to leadership, Develop applications, Influence applications, Develop network technologies, Influence network technologies, Develop information security technologies, Influence information security technologies, Develop database technologies, Influence database technologies, Develop operating systems technologies, Influence operating systems technologies, Develop web technologies, Influence web technologies, Lead strategy resolution, Resolve complex challenges, Evaluate across multiple areas, Deliver long-term solutions, Deliver large-scale solutions, Translate experience into solutions, Translate business objectives into solutions, Translate technological environment into solutions, Translate organization structure into solutions, Translate technological opportunities into solutions, Provide vision to leadership, Provide direction to leadership, Provide expertise to leadership, Implement innovative business solutions, Implement significant business solutions, Maintain knowledge of industry best practices, Maintain knowledge of new technologies, Recommend innovations, Enhance operations, Provide competitive advantage, Strategically engage with professionals, Strategically engage with managers, Serve as expert advisor to leadership, Lead design of cloud-native solutions, Lead architecture of cloud-native solutions, Guide engineering team technically, Set best practices, Mentor senior engineers, Collaborate with Cloud Architects, Collaborate with DevOps Engineers, Collaborate with Application teams, Design cloud infrastructure, Implement cloud infrastructure, Define CI/CD pipelines, Implement CI/CD pipelines, Define automation strategies, Implement automation strategies, Define monitoring solutions, Implement monitoring solutions, Own end-to-end delivery, Provision cloud components, Deploy cloud components, Scale cloud components, Ensure resilience of cloud components, Drive technical evaluations, Propose adoption strategies, Ensure adherence to security standards, Ensure adherence to compliance standards, Ensure adherence to cost optimization standards, Act as technical SME, Continuously improve system performance, Continuously improve system reliability, Continuously improve developer productivity", "teamCollaboration" : "Cross-functional teams; Cloud Architects; DevOps Engineers; Application teams", "projectManagementSkills" : [ "Agile", "DevOps" ], "domainKnowledge" : "Cloud-native architecture; Microservices; Distributed systems; Event-driven architectures; Cloud security; Cloud networking; Cloud monitoring; Cost management; DevSecOps; FinOps; Cloud governance", "domainList" : [ "cloud-native-architecture", "microservices", "distributed-systems", "event-driven-architectures", "cloud-security", "cloud-networking", "cloud-monitoring", "cost-management", "devsecops", "finops", "cloud-governance" ], "domainSpecificKnowledge" : [ "Cloud-native architecture", "Microservices", "Distributed systems", "Event-driven architectures", "Cloud security", "Cloud networking", "Cloud monitoring", "Cost management", "DevSecOps", "FinOps", "Cloud governance" ], "toolProficiency" : [ "Red Hat OpenShift", "Kubernetes", "Docker", "Terraform", "Ansible", "CloudFormation", "Jenkins", "ArgoCD", "GitHub Actions" ], "communicationSkills" : "Technical documentation", "documentationSkills" : "Technical documentation", "innovationCreativity" : "Innovation; Creativity", "problemSolvingSkills" : "Advanced analytical thinking; Inductive thinking; Problem-solving", "qualificationsBasic" : "7+ years of Engineering experience", "qualificationsPreferred" : "7+ years progressive software engineering experience, 5+ years cloud engineering roles, Architecting and designing solutions on AWS, Azure, or GCP, Experience with Red Hat OpenShift, Kubernetes experience, Docker experience, Container lifecycle management experience, Proficiency in Infrastructure as Code, Terraform proficiency, Ansible proficiency, CloudFormation proficiency, Solid understanding of CI/CD pipelines, GitOps practices understanding, DevOps toolchains understanding, Proficiency in Python, Proficiency in Go, Proficiency in Java, Proficiency in Node.js, Grasp of microservices, Grasp of distributed systems, Grasp of event-driven architectures, Excellent system design skills, Excellent API integration skills, Excellent technical documentation skills, Knowledge of cloud security, Knowledge of cloud networking, Knowledge of cloud monitoring, Knowledge of cloud cost management, Certifications such as AWS Solutions Architect, Certifications such as Azure Architect Expert, Certifications such as GCP Professional Cloud Architect, Experience with DevSecOps, Experience with FinOps, Experience with cloud governance frameworks, Experience leading modernization initiatives, Experience leading cloud migration initiatives, Exposure to service mesh, Exposure to serverless architecture, Exposure to edge computing", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "**About this role:** Wells Fargo is seeking a Principal engineer for Architecture and Engineering team. ****In this role, you will:**** * Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups * Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking * Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions * Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions * Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization * Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership ****Required Qualifications:**** * 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education ****Desired Qualifications:**** * 7+ years of progressive experience in software engineering, with at least 5+ years in cloud engineering roles. * Proven experience in architecting and designing solutions on at least one major cloud platform – AWS, Azure, or GCP. * Strong experience with Red Hat OpenShift, Kubernetes, Docker, and container lifecycle management. * Proficiency in Infrastructure as Code using Terraform, Ansible, or CloudFormation. * Solid understanding of CI/CD pipelines, GitOps practices, and DevOps toolchains (Jenkins, ArgoCD, GitHub Actions, etc.). * Proficiency in at least one programming language – Python, Go, Java, or Node.js. * Strong grasp of microservices, distributed systems, and event-driven architectures. * Excellent skills in system design, API integration, and technical documentation. * Knowledge of cloud security, networking, monitoring, and cost management best practices. * Strong problem-solving, leadership, and communication skills. * Certifications such as AWS Solutions Architect, Azure Architect Expert, or GCP Professional Cloud Architect. * Experience with DevSecOps, FinOps, and cloud governance frameworks. * Prior experience in leading modernization or cloud migration initiatives. * Exposure to service mesh (Istio/Linkerd), serverless architecture, and edge computing is a plus. ****Job Expectations:**** * Lead the design and architecture of enterprise-scale cloud-native solutions with a focus on scalability, security, and performance. * Guide the engineering team technically, setting best practices and mentoring senior engineers. * Collaborate closely with Cloud Architects, DevOps Engineers, and Application teams to design and implement cloud infrastructure using Infrastructure as Code (IaC). * Define and implement CI/CD pipelines, automation strategies, and monitoring solutions aligned with DevOps best practices. * Own end-to-end delivery of cloud components including provisioning, deployment, scaling, and resilience. * Drive technical evaluations of cloud services and tools, proposing appropriate adoption strategies. * Ensure adherence to security, compliance, and cost optimization standards in all cloud implementations. * Act as a technical SME in OpenShift container platform and other Kubernetes-based orchestration systems. * Continuously improve system performance, reliability, and developer productivity. **Posting End Date:** 17 Jun 2026 _***Job posting may come down early due to volume of applicants.**_ **We Value Equal Opportunity** Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic. Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements. Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process. **Applicants with Disabilities** To request a medical accommodation during the application or interview process, visit [Disability Inclusion at Wells Fargo](https://www.wellsfargojobs.com/en/diversity/disability-inclusion/). **Drug and Alcohol Policy** **** Wells Fargo maintains a drug free workplace. Please see our [Drug and Alcohol Policy](https://www.wellsfargojobs.com/en/wells-fargo-drug-and-alcohol-policy) to learn more. **Wells Fargo Recruitment and Hiring Requirements:** a. Third-Party recordings are prohibited unless authorized by Wells Fargo. b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.", "summaryDescription" : "Principal Engineer at Wells Fargo. Skills: Cloud engineering, Software engineering, Architecture, DevOps. Act as advisor to leadership. 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