{ "count" : 36318, "data" : [ { "id" : "6a2ca5bd74d8ee00a09b7ee9", "title" : "Consultant, AI/ML", "company" : "Intellishore", "industry" : "Consulting", "salary" : { "min" : 95000.0, "max" : 125000.0, "currency" : "CHF", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior AI/ML Consultant in Zurich, Switzerland, adjusted for the healthcare industry and entry-level experience." }, "location" : "Zurich", "locations" : [ "Zurich" ], "timestamp" : "2026-06-16T00:54:45.403", "fingerprint" : "f6d4433cb3988df7a732e0d8185a8e876545af564b44ed2a350a0c29089dacd4", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/intellishoredk/jobs/7741425003", "externalId" : "7741425003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Zürich", "country" : "Switzerland", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "47.3744489,8.5410422" } ], "locationText" : "Zürich, Switzerland", "employmentType" : "FULL_TIME", "experienceMinYears" : 1, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "Machine learning, Generative AI, AI, Data engineering, Data science, Python, XGBoost, PyTorch, TensorFlow, LLMs, Vector databases, RAG techniques, AWS, Azure, GCP", "professionalSkills" : [ "Solution design", "Technology implementation", "Business solutions" ], "hardSkillsList" : [ "Machine learning engineering", "Statistics", "Data processing", "Software engineering practices" ], "hardSkills" : [ { "name" : "Machine learning engineering", "level" : "intermediate" }, { "name" : "Statistics", "level" : "intermediate" }, { "name" : "Data processing", "level" : "intermediate" }, { "name" : "Software engineering practices", "level" : "intermediate" } ], "majorSkills" : "AI, Machine learning, Generative AI", "majorSkillsList" : [ "AI", "Machine learning", "Generative AI" ], "coreResponsibilities" : "Develop machine learning solutions, Implement machine learning solutions, Develop generative AI solutions, Implement generative AI solutions, Build scalable data pipelines, Integrate AI models into production, Implement natural language processing, Implement retrieval-augmented generation, Create proofs-of-concept, Demonstrate AI capabilities, Collaborate with cross-functional teams, Support client engagements, Communicate technical concepts", "teamCollaboration" : "Cross-functional teams; Dedicated Intellishore project team", "domainKnowledge" : "Healthcare; Life sciences; Pharmaceutical companies", "domainList" : [ "healthcare", "life-sciences", "pharmaceutical-companies" ], "domainSpecificKnowledge" : [ "Healthcare", "Life sciences", "Pharmaceutical companies" ], "communicationSkills" : "Communicate technical concepts", "problemSolvingSkills" : "Problem-solving", "specialRequirements" : "Availability for on-site presence, Applications from Switzerland", "qualificationsBasic" : "1+ years of experience in machine learning and AI engineering, Solid grasp of statistics foundations, Python programming skills, Experience with ML frameworks, Knowledge of cloud platforms, Understanding of data processing techniques, Understanding of best software engineering practices, Problem-solving skills, Ability to learn quickly, Effective communication skills, Effective collaboration skills, Fluency in English", "qualificationsPreferred" : "Hands-on exposure to healthcare/life sciences industries use cases, Familiarity with LLMs, Familiarity with vector databases, Familiarity with RAG techniques, Fluency in German, Fluency in French", "workSiteFlexibility" : "Onsite", "rawDescription" : "We are looking for ambitious and passionate AI/ML Consultants to join our fast-growing Zürich office and help develop AI-driven solutions. You will work on building machine learning models, generative AI applications, and automation tools to address key challenges in direct tandem with our healthcare & life sciences clients. About the job Do you want to be part of an exciting journey where you will get plenty of responsibility and influence? Then you need to read on! Being an AI/ML Consultant at Intellishore, you will get to shape and implement technology as well as business solutions to deliver value at our new Intellishore office in Zürich. You will have the opportunity to immerse yourself in some of the most exciting technologies while gaining an in-depth understanding of specific business challenges through close collaboration with your dedicated Intellishore project team and clients. Additionally, by joining Intellishore in Zürich, you will have a unique opportunity to influence and shape the development and commercial growth of Intellishore CH within a highly entrepreneurial and flexible setup, while benefiting from the backing of a family of over 80 Intellishorians in Denmark. Who is Intellishore? Intellishore is an advanced analytics, AI, and strategy consultancy founded in 2013 to provide healthcare & life sciences clients with a seamless combination of strategic and technical expertise. Today, we are more than 80 skilled, entrepreneurial, and passionate employees from many different backgrounds: data engineering, economics, business, marketing, and data science. Intellishore CH is our new entity in Zürich, focused on empowering pharmaceutical companies to realize their AI aspirations. We deliver solutions across the value chain - no project is the same, and the energy is high. What are we looking for in an AI/ML Consultant? We are looking for an AI/ML Consultant at the beginning of their career who is curious and eager to develop real-life solutions for interesting clients. Perhaps you have recently completed your education or have a few years of full-time experience in AI and Data Science, possibly from a consultancy. At Intellishore, we are what you might call ‘agnostic,’ meaning we act as an objective technology partner, implementing only tailored and best-fit solutions for our clients. Therefore, you should be open-minded and curious to learn new technologies. Ideally, you match all or most of the following attributes: 1+ years of experience in machine learning and AI engineering (hands-on exposure to healthcare/life sciences industries use cases is a plus). Solid grasp of statistics foundations. Strong Python programming skills. Experience with ML frameworks (XGBoost, PyTorch, TensorFlow, etc.). Highly motivated to join Intellishore and its mission to revolutionize AI adoption in healthcare/life sciences, as demonstrated in the cover letter. Familiarity with LLMs, vector databases, and RAG techniques would be a plus, but deep knowledge of \"traditional\" AI/ML is a must. Knowledge of cloud platforms (AWS, Azure, or GCP). Understanding of data processing techniques and best software engineering practices. Strong problem-solving skills and the ability to learn quickly. Effective communication and collaboration skills. Fluency in English, German, or French, in addition, would be a plus. Availability for on-site presence in Zürich. And do not worry about whether you have too much or too little experience. We are always looking for curious and passionate people to join our family, and your title will match your level of seniority and expertise. What will be your key responsibilities? Intellishore is a cross-functional consultancy where you will represent the back-end area in the technical track. Here you will be responsible for (among other things): Develop and implement machine learning and generative AI solutions. Build scalable data pipelines and integrate AI models into production environments. Implement natural language processing (NLP) and retrieval-augmented generation (RAG) techniques. Create proofs-of-concept to demonstrate AI capabilities. Collaborate with cross-functional teams on solution design and development. Support client engagements and communicate technical concepts effectively. What can we offer you? 1 | Challenging projects Exciting and challenging project roles in strategic & technical AI projects 2 | Entrepreneurial work environment A highly entrepreneurial work environment with ambitious and innovative colleagues focused on rapidly growing the Intellishore CH business 3 | Influence Unique opportunity for influencing and directing Intellishore CH's market position, commercial growth, and strategic journey 4 | Strategic seminars A yearly strategic seminar where all Intellishorians across locations spend time strategizing and team-building (in previous years, we've been to South Africa, Japan, India, China, Dubai, Iceland, and Germany) 5 | Sustainable consulting A consulting career with high levels of flexibility, allowing for work-life balance 6 | Exciting growth journey We are on a mission to redefine the world of AI consulting, and we are constantly expanding our reach \"At Intellishore, we work with a principle of always choosing the best person for the job - disregarding seniority and titles. In practice, this means that you will have a major influence on what you'll be doing on a day-to-day basis as well as the level of responsibility you will have.\" Mikkel Møller Andersen Managing Director, Intellishore CH Apply now If you are interested in applying for this position, fill out the application form. Please attach a short motivational letter customized for this opportunity (generic letter might be overlooked). Applicants will be invited to interviews on a rolling basis. At the moment, we are only accepting applications from applicants in Switzerland.", "summaryDescription" : "Consultant, AI/ML at Intellishore. Skills: AI, Machine learning, Generative AI. Develop machine learning solutions. 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We’re on the frontier of an entirely new category: Agentic AI. We enable enterprises to build high-performing hybrid workforces made up of both humans and AI agents. These AI agents aren’t generic copilots. They’re fully trained digital teammates that learn from your best people, your content, and your business strategy—ready to get to work from day one. Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. Whether you're launching a product globally, onboarding new hires, translating learning content, or aligning legal teams across regions, Smartcat turns knowledge into action and action into scale. Over 1,000 companies, including 20% of the Fortune 500, rely on Smartcat to bring their business to the world—instantly, accurately, and in every language. As a Series C company with consistently high year-over-year growth, we’re scaling fast and investing in people who want to shape the future of work with us. Join us in unlocking global potential, one human and agent team at a time. Mission As a Senior Backend Engineer, you'll be at the forefront of enhancing our platform's capabilities. You'll design and implement scalable, high-performance backend services that power critical features for our growing client base. Outcomes Design, develop, and deploy backend services and APIs that solve real-world customer challenges Optimize application performance, scalability, and security Collaborate with product managers, frontend engineers, and DevOps to ensure seamless integration of services Troubleshoot and resolve production issues efficiently Actively participate in code reviews, knowledge sharing, and continuous learning Requirements 8+ years of proven professional experience as a Software Engineer, with at least 3 years in .NET and C# 2+ years of experience in product companies (SaaS) Passion and strong skill for writing clean, maintainable, and testable code and well-documented C# code Experience with writing and maintaining Unit tests and E2E tests Advanced experience with MongoDB Upper-intermediate or higher English proficiency (written and spoken) Strong problem-solving skills and a growth mindset Readiness to thrive in a fast-paced startup environment with extreme focus, a strong sense of ownership, and determination Openness to constructive feedback and value the ideas and opinions of others Our technologies Backend: .NET Core (C#), Python Frontend: Vue.js 2/3, Nuxt 3, Typescript Databases: MongoDB, PostgreSQL, Elasticsearch Messaging Queue: Kafka Cloud Provider: Amazon AWS Monitoring & Logging: ELK (EFK), Prometheus, Grafana Why joining Smartcat might be your best move so far A global, connected team We’re a team of 200+ people across 30+ countries, working together through a hub-and-spoke model anchored in eight key locations: New York, London, Lisbon, Costa Rica, Serbia, Armenia, Georgia, and Spain. Most of our roles are remote-friendly, giving you the flexibility to do your best work from where you thrive. For customer-facing teams, we prioritize proximity to our customers, ensuring we stay deeply connected to their needs and deliver an exceptional experience. No matter where you’re based, you’ll be part of a highly collaborative, globally-distributed team that values ownership, speed, and meaningful impact. Be part of an AI Native Organization We are highly innovative, using AI across all areas of the organization to accelerate decision-making and free people to focus on strategy and high-impact work. We embrace new ideas and encourage all Smartcaters, regardless of level or department, to manage their own AI Agents. At Smartcat you’ll shape how AI transforms the workplace and play an integral role in ensuring Smartcat remains a leader in AI innovation. Innovating a $100 Billion industry Smartcat is reshaping the $100B multilingual content industry with an AI-powered platform that makes it easy for companies to create, translate, and localize global content at scale. Our platform enables enterprise teams to move away from slow, traditional outsourcing methods, and achieve fast, high-quality results, at a fraction of the cost. Join the rocketship to scale-up 10x and beyond together We are looking for someone to become an integral part of our team and play a crucial role in the most exciting part of our journey: transitioning from a post-Series C startup to a company exceeding $100M in ARR and $1B in valuation. Our journey isn’t for the faint of heart. We are growing at 130% YoY, thanks to our strong product-market fit and high-performing team, and plan to accelerate from here. 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We’re on the frontier of an entirely new category: Agentic AI. We enable enterprises to build high-performing hybrid workforces made up of both humans and AI agents. These AI agents aren’t generic copilots. They’re fully trained digital teammates that learn from your best people, your content, and your business strategy—ready to get to work from day one. Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. Whether you're launching a product globally, onboarding new hires, translating learning content, or aligning legal teams across regions, Smartcat turns knowledge into action and action into scale. Over 1,000 companies, including 20% of the Fortune 500, rely on Smartcat to bring their business to the world—instantly, accurately, and in every language. As a Series C company with consistently high year-over-year growth, we’re scaling fast and investing in people who want to shape the future of work with us. Join us in unlocking global potential, one human and agent team at a time. Smartcat was founded in 2016 to help global enterprises create and manage their multilingual content. Today, Smartcat is the essential language AI platform for the global enterprise. Our client-tailored language AI turns content in any format into any language, from documents to videos to complex websites and software, making global operations simple for any corporate team. It also allows any user to create new content by tapping into a multilingual enterprise library. More than 1,000 global companies including 25% of the Fortune 500 trust Smartcat to communicate their innovations and ideas all over the world. Smartcat’s vision is to realise a world where there is equal access to innovations and ideas. Smartcat is backed by Matrix Partners, FJ Labs, and other leading VC firms focusing on SaaS, marketplaces and AI. You might recognize names like HubSpot, Zendesk, Uber, Stripe, RigUp, and Quora in their portfolios. Despite the economic recession, Smartcat is growing at 150% YoY. It's well-funded and capital efficient, providing a unique combination of a hyper-growth environment with downside protection and the ability to think and plan long-term. Senior Backend Developer Mission: Your mission will be to maintain and improve existing functionality and develop new application parts. This position will be remote-based in Europe. Ideal locations include: Serbia, Armenia, Bulgaria, Georgia and Romania. Outcomes Deliver value for our customers Improve the stability and observability of our product Develop parts of the application: design, refactoring, fixing bugs, and writing tests to maintain the quality and functionality of the product and libraries Review code and share knowledge with the team Requirements 5+ years of experience in .NET development and test coverage Knowledge of OOP principles and design patterns Experience with Database concurrency Upper-Intermediate English: both written and spoken A data-driven approach. Ability to justify decisions using concrete metrics Integrity and full commitment Growth mindset Readiness to work in an intense startup environment requiring extreme focus, a strong sense of ownership, and determination to break through Openness to constructive feedback and the opinions and ideas of others Our technologies PL: .NET Core DB: MongoDB, PostgreSQL Hosting in the AWS Elasticsearch cluster, indexes for several billion documents ELK (EFK) for logging, VM, Prometheus and Grafana for metrics and monitoring Why joining Smartcat might be your best move so far Fully remote team We are a global team of 200+ enthusiastic people spread across 30 countries. We have been fully remote since 2020, with some locations populated with more Smartcatters than others, such as Boston, NYC, SF, the Bay Area, London, Lisbon, and Yerevan. Innovating the $50 Billion-old industry Smartcat’s innovative business model taps into this $50B language translation industry with a platform allowing enterprise end users to stop using traditional outsourcing and enjoy easy-to-use AI-powered SaaS that delivers immediate high-quality results at a fraction of the cost. High impact role enabling innovation and inclusion in organizations You will enjoy building with us. You will drive changes in how an old-fashioned global language industry operates while improving how hundreds of thousands of people work and millions of people exchange knowledge and ideas worldwide. Join the rocketship to scale-up 10x and beyond together We are looking for someone to become an integral part of our team and play a crucial role in the most exciting part of our journey: transitioning from a post-Series B startup to a company exceeding $100M in ARR and $1B in valuation. Our journey isn’t for the faint of heart. We are growing at 150% YoY, thanks to our strong product-market fit and high-performing team. Smartcat Culture: Where Diversity Meets High Performance At Smartcat, we are committed to building a culture that highlights respect and appreciation for each individual's unique background and perspective, while maintaining a strong focus on results and clear, honest and direct communication. We believe in welcoming everyone and fostering an inclusive environment where team members can be their authentic selves at work. Our commitment to diversity and inclusion is steadfast, and we stand firmly against discrimination and harassment. Why joining Smartcat might be your best move so far A global, connected team We’re a team of 200+ people across 30+ countries, working together through a hub-and-spoke model anchored in eight key locations: New York, London, Lisbon, Costa Rica, Serbia, Armenia, Georgia, and Spain. Most of our roles are remote-friendly, giving you the flexibility to do your best work from where you thrive. For customer-facing teams, we prioritize proximity to our customers, ensuring we stay deeply connected to their needs and deliver an exceptional experience. No matter where you’re based, you’ll be part of a highly collaborative, globally-distributed team that values ownership, speed, and meaningful impact. Be part of an AI Native Organization We are highly innovative, using AI across all areas of the organization to accelerate decision-making and free people to focus on strategy and high-impact work. We embrace new ideas and encourage all Smartcaters, regardless of level or department, to manage their own AI Agents. At Smartcat you’ll shape how AI transforms the workplace and play an integral role in ensuring Smartcat remains a leader in AI innovation. Innovating a $100 Billion industry Smartcat is reshaping the $100B multilingual content industry with an AI-powered platform that makes it easy for companies to create, translate, and localize global content at scale. Our platform enables enterprise teams to move away from slow, traditional outsourcing methods, and achieve fast, high-quality results, at a fraction of the cost. Join the rocketship to scale-up 10x and beyond together We are looking for someone to become an integral part of our team and play a crucial role in the most exciting part of our journey: transitioning from a post-Series C startup to a company exceeding $100M in ARR and $1B in valuation. Our journey isn’t for the faint of heart. We are growing at 130% YoY, thanks to our strong product-market fit and high-performing team, and plan to accelerate from here. Smartcat Culture Code: Where Diversity Meets High Performance At Smartcat, we are committed to building a culture that highlights respect and appreciation for each individual's unique background and perspective, while maintaining a strong focus on results and engagement. We believe in welcoming everyone and fostering an inclusive environment where team members can be their authentic selves at work. Our commitment to inclusion is steadfast, and we stand firmly against discrimination and harassment.", "summaryDescription" : "AI First Developer at Smartcat. Skills: NET Core, Database concurrency, System design. Maintain existing functionality. Improve existing functionality", "postedDate" : "2026-06-16T01:18:55.555", "createdAt" : "2026-06-16T01:18:55.555", "lastUpdated" : "2026-06-16T11:00:41.431", "ingestTimestamp" : "2026-06-16T01:18:55.555", "mongoId" : "6a307648f292fd229c017e05", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Database concurrency", "Test coverage", "Determination", "NET Core", "System design", "Code review", "Startup environment", "Agentic AI", "Enterprise Skill Graph", "Generative AI", "Human-in-the-loop workflows", "Multilingual content", "Language AI platform", "MongoDB", "PostgreSQL", "AWS", "Elasticsearch", "ELK", "Prometheus", "Grafana" ], "skillCount" : 20, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 1221.1903, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3089caf292fd229c094d7d", "title" : "Python ML/AI Engineer", "company" : "DOTSOFT SA", "industry" : "Information Technology And Services", "salary" : { "min" : 38000.0, "max" : 55000.0, "currency" : "EUR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Mid-level Python ML/AI Engineer in the Technology industry in Pilea, Greece, adjusted for seniority and full-time employment." }, "location" : "Pilea, GR", "locations" : [ "Pilea", "GR" ], "timestamp" : "2026-06-16T11:35:00.625", "fingerprint" : "b46faa998ac8e53208bea2181d35324dfce027d92143157e84b9e2d5f20135a2", "source" : "smartrecruiters", "language" : "el", "applyUrl" : "https://jobs.smartrecruiters.com/DOTSOFTSA/744000132218589-python-ml-ai-engineer", "externalId" : "744000132218589", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Pilea", "state" : "Thessaloniki", "country" : "Greece", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "40.5850904,23.0356579" } ], "locationText" : "Pilea, Thessaloniki, Greece", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "technicalSkills" : "Python, Machine Learning, Deep Learning, AI, Generative AI, Large Language Models, Retrieval-Augmented Generation, Vector databases, Embeddings, Semantic search, MLOps, Scikit-learn, Pandas, NumPy, PyTorch, TensorFlow, SQL, APIs, Docker, Cloud platforms, OpenAI, Anthropic, Llama, Mistral, LangChain, LlamaIndex, Qdrant, Weaviate, Pinecone, Pgvector", "professionalSkills" : [ "Data processing", "System design", "Technology strategy" ], "hardSkillsList" : [ "Machine Learning", "Deep Learning", "Data pipelines", "Model evaluation", "AI Services", "Generative AI", "Large Language Models", "Retrieval-Augmented Generation", "Vector databases", "Embeddings", "Semantic search", "MLOps", "Deployment", "Monitoring", "API development" ], "hardSkills" : [ { "name" : "Machine Learning", "level" : "intermediate" }, { "name" : "Deep Learning", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "Model evaluation", "level" : "intermediate" }, { "name" : "AI Services", "level" : "intermediate" }, { "name" : "Generative AI", "level" : "intermediate" }, { "name" : "Large Language Models", "level" : "intermediate" }, { "name" : "Retrieval-Augmented Generation", "level" : "intermediate" }, { "name" : "Vector databases", "level" : "intermediate" }, { "name" : "Embeddings", "level" : "intermediate" }, { "name" : "Semantic search", "level" : "intermediate" }, { "name" : "MLOps", "level" : "intermediate" }, { "name" : "Deployment", "level" : "intermediate" }, { "name" : "Monitoring", "level" : "intermediate" }, { "name" : "API development", "level" : "intermediate" } ], "majorSkills" : "Machine Learning, AI, Python, Generative AI", "majorSkillsList" : [ "Machine Learning", "AI", "Python", "Generative AI" ], "coreResponsibilities" : "Develop ML models, Optimize ML models, Maintain ML models, Design data pipelines, Implement data pipelines, Develop AI services, Maintain AI services, Design Generative AI solutions, Develop Generative AI solutions, Integrate Generative AI solutions, Develop RAG applications, Utilize vector databases, Utilize embeddings, Utilize semantic search, Transition solutions to production, Monitor model performance, Optimize model performance, Deploy models, Monitor models, Ensure solution quality, Ensure solution reliability, Ensure solution scalability, Evaluate new technologies, Evaluate new tools, Evaluate new methodologies, Participate in technical design, Formulate technology strategy", "teamCollaboration" : "Data Science teams; Software Engineering teams; R&D teams", "domainKnowledge" : "Artificial Intelligence; Machine Learning; Data Analytics; Cloud Computing; Generative AI; Large Language Models; MLOps", "domainList" : [ "artificial-intelligence", "machine-learning", "data-analytics", "cloud-computing", "generative-ai", "large-language-models", "mlops" ], "domainSpecificKnowledge" : [ "Artificial Intelligence", "Machine Learning", "Data Analytics", "Cloud Computing", "Generative AI", "Large Language Models", "MLOps" ], "toolProficiency" : [ "Scikit-learn", "Pandas", "NumPy", "PyTorch", "TensorFlow", "Docker", "Qdrant", "Weaviate", "Pinecone", "Pgvector", "OpenAI", "Anthropic", "Llama", "Mistral", "LangChain", "LlamaIndex" ], "continuousLearning" : "Professional development; Continuous education", "innovationCreativity" : "Innovative digital solutions; Advanced AI solutions; Cutting-edge projects", "qualificationsBasic" : "3+ years experience ML/AI, Proficient in Python, Experience with Scikit-learn, Experience with Pandas, Experience with NumPy, Experience with PyTorch, Experience with TensorFlow, Experience ML model development, Experience ML model evaluation, Knowledge of SQL, Data management knowledge, Experience developing APIs, Ability to collaborate", "qualificationsPreferred" : "MSc in AI/ML, Experience with LLMs, Experience with LangChain, Experience with LlamaIndex, Experience with vector databases, Knowledge of MLOps tools, Knowledge of MLOps practices, Experience with Docker, Experience with cloud platforms, Participation in AI research projects, Participation in European AI projects", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Η DOTSOFT αναπτύσσει καινοτόμες ψηφιακές λύσεις αξιοποιώντας τεχνολογίες Τεχνητής Νοημοσύνης, Data Analytics και Cloud Computing. Στο πλαίσιο της συνεχούς ανάπτυξής της, αναζητά έναν Python ML/AI Engineer για την υλοποίηση προηγμένων λύσεων AI και Machine Learning σε έργα εθνικής και ευρωπαϊκής εμβέλειας. * Ανάπτυξη, βελτιστοποίηση και συντήρηση μοντέλων Machine Learning και Deep Learning για την κάλυψη επιχειρησιακών και ερευνητικών αναγκών. * Σχεδιασμός και υλοποίηση pipelines επεξεργασίας δεδομένων, εκπαίδευσης, αξιολόγησης και παραγωγικής λειτουργίας μοντέλων. * Ανάπτυξη και συντήρηση υπηρεσιών Τεχνητής Νοημοσύνης (AI Services) με χρήση Python και σύγχρονων frameworks. * Σχεδιασμός, ανάπτυξη και ενσωμάτωση λύσεων Generative AI και Large Language Models (LLMs) σε παραγωγικά πληροφοριακά συστήματα. * Ανάπτυξη εφαρμογών Retrieval-Augmented Generation (RAG) με αξιοποίηση vector databases, embeddings και τεχνικών semantic search. * Συνεργασία με ομάδες Data Science, Software Engineering και Έρευνας & Ανάπτυξης για τη μετάβαση λύσεων από στάδιο proof-of-concept σε παραγωγική λειτουργία. * Παρακολούθηση, αξιολόγηση και βελτιστοποίηση της απόδοσης μοντέλων μέσω διαδικασιών MLOps, deployment και monitoring. * Διασφάλιση της ποιότητας, αξιοπιστίας και επεκτασιμότητας των λύσεων Τεχνητής Νοημοσύνης. * Αξιολόγηση νέων τεχνολογιών, εργαλείων και μεθοδολογιών στον τομέα της Τεχνητής Νοημοσύνης και της Μηχανικής Μάθησης. * Συμμετοχή στον τεχνικό σχεδιασμό λύσεων και στη διαμόρφωση της τεχνολογικής στρατηγικής της ομάδας και της εταιρείας. ## Qualifications Προσόντα * Πτυχίο ΑΕΙ/ΤΕΙ στην Πληροφορική, Μηχανική Υπολογιστών, Data Science ή συναφή τομέα. * MSc σε Artificial Intelligence, Machine Learning ή σχετικό αντικείμενο θα θεωρηθεί επιπλέον προσόν. * 3+ χρόνια εμπειρίας σε ανάπτυξη λύσεων Machine Learning ή AI. * Πολύ καλή γνώση Python. * Εμπειρία με βιβλιοθήκες όπως Scikit-learn, Pandas, NumPy και PyTorch ή TensorFlow. * Εμπειρία στην ανάπτυξη και αξιολόγηση ML μοντέλων. * Γνώση SQL και διαχείρισης δεδομένων. * Εμπειρία στην ανάπτυξη APIs για AI υπηρεσίες. * Ικανότητα συνεργασίας σε διεπιστημονικές ομάδες. Επιθυμητά προσόντα * Εμπειρία με LLMs (OpenAI, Anthropic, Llama, Mistral κ.ά.). * Γνώση LangChain, LlamaIndex ή παρόμοιων frameworks. * Εμπειρία με vector databases (Qdrant, Weaviate, Pinecone, pgvector). * Γνώση MLOps εργαλείων και πρακτικών. * Εμπειρία με Docker και cloud πλατφόρμες. * Συμμετοχή σε ερευνητικά ή ευρωπαϊκά έργα AI. ## Additional Information Προσφέρεται * Ανταγωνιστικό πακέτο αποδοχών * Εργασία σε φιλικό & δυναμικό περιβάλλον * Συνεχής εκπαίδευση & δυνατότητα επαγγελματικής ανάπτυξης * Συμμετοχή σε καινοτόμα και υψηλής τεχνολογίας projects", "summaryDescription" : "Python ML/AI Engineer at DOTSOFT SA. Skills: Machine Learning, AI, Python, Generative AI. Develop ML models. Optimize ML models", "postedDate" : "2026-06-15T14:30:06.000", "createdAt" : "2026-06-16T01:43:02.724", "lastUpdated" : "2026-06-16T11:35:00.625", "ingestTimestamp" : "2026-06-16T01:43:02.724", "mongoId" : "6a3089caf292fd229c094d7d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "Machine Learning", "Deep Learning", "Data pipelines", "Model evaluation", "AI Services", "Generative AI", "Large Language Models", "Retrieval-Augmented Generation", "Vector databases", "Embeddings", "Semantic search", "MLOps", "Deployment", "Monitoring", "API development", "AI", "Python", "Data processing", "System design", "Technology strategy", "Artificial Intelligence", "Data Analytics", "Cloud Computing", "Scikit-learn", "Pandas", "NumPy", "PyTorch", "TensorFlow", "Docker", "Qdrant", "Weaviate", "Pinecone", "Pgvector", "OpenAI", "Anthropic", "Llama", "Mistral", "LangChain", "LlamaIndex" ], "skillCount" : 39, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "_score" : 1221.1143, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a307648f292fd229c017e06", "title" : "AI First Developer", "company" : "Smartcat", "industry" : "SaaS", "salary" : { "min" : 7000000.0, "max" : 1.2E7, "currency" : "AMD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level AI First Developer in Armenia, adjusted for the technology industry and remote work." }, "location" : "Armenia - Remote", "locations" : [ "Armenia - Remote", "Costa Rica - Remote", "Georgia - Remote", "Portugal - Remote", "Serbia - Remote" ], "timestamp" : "2026-06-16T13:50:15.316", "fingerprint" : "2a2a7ab55e9eddc89c43352ac964c42f8c65fc71742c5763c1b065cbfaf4a514", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.smartcat.com/career/?gh_jid=6000304004", "externalId" : "6000304004", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Armenia", "continent" : "as", "workMode" : "remote" } ], "locationText" : "Armenia", "technicalSkills" : "NET Core, MongoDB, PostgreSQL, AWS, Elasticsearch, ELK, EFK, VM, Prometheus, Grafana", "professionalSkills" : [ "Data-driven approach" ], "hardSkillsList" : [ "Application development", "Refactoring", "Bug fixing", "Writing tests", "Code review" ], "softSkillsList" : [ "Commitment", "Determination", "Feedback" ], "hardSkills" : [ { "name" : "Application development", "level" : "intermediate" }, { "name" : "Refactoring", "level" : "intermediate" }, { "name" : "Bug fixing", "level" : "intermediate" }, { "name" : "Writing tests", "level" : "intermediate" }, { "name" : "Code review", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Commitment" }, { "name" : "Determination" }, { "name" : "Feedback" } ], "majorSkills" : "NET Core, AWS, Databases", "majorSkillsList" : [ "NET Core", "AWS", "Databases" ], "coreResponsibilities" : "Maintain functionality, Improve functionality, Develop application parts, Design application parts, Refactor application parts, Fix bugs, Write tests, Review code, Share knowledge", "teamCollaboration" : "Global team; Fully remote team", "domainKnowledge" : "Agentic AI; Enterprise Skill Graph; Generative AI; Human-in-the-loop workflows; Multilingual content; Language AI platform", "domainList" : [ "agentic-ai", "enterprise-skill-graph", "generative-ai", "human-in-the-loop-workflows", "multilingual-content", "language-ai-platform" ], "domainSpecificKnowledge" : [ "Agentic AI", "Enterprise Skill Graph", "Generative AI", "Human-in-the-loop workflows", "Multilingual content", "Language AI platform" ], "toolProficiency" : [ "AWS", "Elasticsearch", "ELK", "EFK", "Prometheus", "Grafana" ], "innovationCreativity" : "AI innovation", "specialRequirements" : "Intense startup environment", "outcomesObjectives" : "Deliver value for customers; Improve stability; Improve observability", "qualificationsBasic" : "NET development experience, Test coverage experience, OOP principles knowledge, Design patterns knowledge, Database concurrency experience, Upper-Intermediate English", "qualificationsPreferred" : "AWS hosting experience, Elasticsearch cluster experience, ELK (EFK) experience, Prometheus and Grafana experience", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Smartcat Smartcat is building the future of work, where human expertise meets digital teammates to drive 10x to 1000x productivity gains for the world’s leading enterprises. We’re on the frontier of an entirely new category: Agentic AI. We enable enterprises to build high-performing hybrid workforces made up of both humans and AI agents. These AI agents aren’t generic copilots. They’re fully trained digital teammates that learn from your best people, your content, and your business strategy—ready to get to work from day one. Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. Whether you're launching a product globally, onboarding new hires, translating learning content, or aligning legal teams across regions, Smartcat turns knowledge into action and action into scale. Over 1,000 companies, including 20% of the Fortune 500, rely on Smartcat to bring their business to the world—instantly, accurately, and in every language. As a Series C company with consistently high year-over-year growth, we’re scaling fast and investing in people who want to shape the future of work with us. Join us in unlocking global potential, one human and agent team at a time. Smartcat was founded in 2016 to help global enterprises create and manage their multilingual content. Today, Smartcat is the essential language AI platform for the global enterprise. Our client-tailored language AI turns content in any format into any language, from documents to videos to complex websites and software, making global operations simple for any corporate team. It also allows any user to create new content by tapping into a multilingual enterprise library. More than 1,000 global companies including 25% of the Fortune 500 trust Smartcat to communicate their innovations and ideas all over the world. Smartcat’s vision is to realise a world where there is equal access to innovations and ideas. Smartcat is backed by Matrix Partners, FJ Labs, and other leading VC firms focusing on SaaS, marketplaces and AI. You might recognize names like HubSpot, Zendesk, Uber, Stripe, RigUp, and Quora in their portfolios. Despite the economic recession, Smartcat is growing at 150% YoY. It's well-funded and capital efficient, providing a unique combination of a hyper-growth environment with downside protection and the ability to think and plan long-term. Mission Your mission will be to maintain and improve existing functionality and develop new application parts. This position will be remote-based in Europe. Ideal locations include: Serbia, Armenia, Bulgaria, Georgia and Romania. Outcomes Deliver value for our customers Improve the stability and observability of our product Develop parts of the application: design, refactoring, fixing bugs, and writing tests to maintain the quality and functionality of the product and libraries Review code and share knowledge with the team Requirements Experience in .NET development and test coverage Knowledge of OOP principles and design patterns Experience with Database concurrency Upper-Intermediate English: both written and spoken A data-driven approach. Ability to justify decisions using concrete metrics Integrity and full commitment Growth mindset Readiness to work in an intense startup environment requiring extreme focus, a strong sense of ownership, and determination to break through Openness to constructive feedback and the opinions and ideas of others Our technologies PL: .NET Core DB: MongoDB, PostgreSQL Hosting in the AWS Elasticsearch cluster, indexes for several billion documents ELK (EFK) for logging, VM, Prometheus and Grafana for metrics and monitoring Why joining Smartcat might be your best move so far Fully remote team We are a global team of 200+ enthusiastic people spread across 30 countries. We have been fully remote since 2020, with some locations populated with more Smartcatters than others, such as Boston, NYC, SF, the Bay Area, London, Lisbon, and Yerevan. Innovating the $50 Billion-old industry Smartcat’s innovative business model taps into this $50B language translation industry with a platform allowing enterprise end users to stop using traditional outsourcing and enjoy easy-to-use AI-powered SaaS that delivers immediate high-quality results at a fraction of the cost. High impact role enabling innovation and inclusion in organizations You will enjoy building with us. You will drive changes in how an old-fashioned global language industry operates while improving how hundreds of thousands of people work and millions of people exchange knowledge and ideas worldwide. Join the rocketship to scale-up 10x and beyond together We are looking for someone to become an integral part of our team and play a crucial role in the most exciting part of our journey: transitioning from a post-Series B startup to a company exceeding $100M in ARR and $1B in valuation. Our journey isn’t for the faint of heart. We are growing at 150% YoY, thanks to our strong product-market fit and high-performing team. Smartcat Culture: Where Diversity Meets High Performance At Smartcat, we are committed to building a culture that highlights respect and appreciation for each individual's unique background and perspective, while maintaining a strong focus on results and clear, honest and direct communication. We believe in welcoming everyone and fostering an inclusive environment where team members can be their authentic selves at work. Our commitment to diversity and inclusion is steadfast, and we stand firmly against discrimination and harassment. Why joining Smartcat might be your best move so far A global, connected team We’re a team of 200+ people across 30+ countries, working together through a hub-and-spoke model anchored in eight key locations: New York, London, Lisbon, Costa Rica, Serbia, Armenia, Georgia, and Spain. Most of our roles are remote-friendly, giving you the flexibility to do your best work from where you thrive. For customer-facing teams, we prioritize proximity to our customers, ensuring we stay deeply connected to their needs and deliver an exceptional experience. No matter where you’re based, you’ll be part of a highly collaborative, globally-distributed team that values ownership, speed, and meaningful impact. Be part of an AI Native Organization We are highly innovative, using AI across all areas of the organization to accelerate decision-making and free people to focus on strategy and high-impact work. We embrace new ideas and encourage all Smartcaters, regardless of level or department, to manage their own AI Agents. At Smartcat you’ll shape how AI transforms the workplace and play an integral role in ensuring Smartcat remains a leader in AI innovation. Innovating a $100 Billion industry Smartcat is reshaping the $100B multilingual content industry with an AI-powered platform that makes it easy for companies to create, translate, and localize global content at scale. Our platform enables enterprise teams to move away from slow, traditional outsourcing methods, and achieve fast, high-quality results, at a fraction of the cost. Join the rocketship to scale-up 10x and beyond together We are looking for someone to become an integral part of our team and play a crucial role in the most exciting part of our journey: transitioning from a post-Series C startup to a company exceeding $100M in ARR and $1B in valuation. Our journey isn’t for the faint of heart. We are growing at 130% YoY, thanks to our strong product-market fit and high-performing team, and plan to accelerate from here. Smartcat Culture Code: Where Diversity Meets High Performance At Smartcat, we are committed to building a culture that highlights respect and appreciation for each individual's unique background and perspective, while maintaining a strong focus on results and engagement. We believe in welcoming everyone and fostering an inclusive environment where team members can be their authentic selves at work. Our commitment to inclusion is steadfast, and we stand firmly against discrimination and harassment.", "summaryDescription" : "AI First Developer at Smartcat. Skills: NET Core, AWS, Databases. Maintain functionality. Improve functionality", "postedDate" : "2026-06-16T01:19:33.805", "createdAt" : "2026-06-16T01:19:33.805", "lastUpdated" : "2026-06-16T13:50:15.316", "ingestTimestamp" : "2026-06-16T01:19:33.805", "mongoId" : "6a307648f292fd229c017e06", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Application development", "Refactoring", "Bug fixing", "Writing tests", "Code review", "Commitment", "Determination", "Feedback", "NET Core", "AWS", "Databases", "Data-driven approach", "Agentic AI", "Enterprise Skill Graph", "Generative AI", "Human-in-the-loop workflows", "Multilingual content", "Language AI platform", "Elasticsearch", "ELK", "EFK", "Prometheus", "Grafana" ], "skillCount" : 23, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 1220.9452, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "69ce5df99bc74574cb671a54", "title" : "AI Developer", "company" : "Texas Workforce Commission", "industry" : "Government", "salary" : { "min" : 145000.0, "max" : 210000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior AI Developer in Austin, TX, adjusted for government industry and full-time employment." }, "location" : "826631", "locations" : [ "826631", "
Austin:1411 Brazos (320TX-4000)
1411 Brazos St
Austin, 78701

" ], "timestamp" : "2026-06-15T22:56:59.191", "fingerprint" : "5f75133ba24aec7e4d1dcc96a85e398ff28a2d14c7101e16845098edb3ae68b8", "source" : "taleo", "language" : "en", "applyUrl" : "https://aa270.taleo.net/careersection/ex/jobdetail.ftl?job=33531", "externalId" : "33531", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Austin", "state" : "Texas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "30.2711286,-97.7436995" } ], "locationText" : "Austin, Texas, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Java, Python, REST APIs, Gen AI SDKs, AWS, Google, Microsoft, Oracle", "professionalSkills" : [ "Software development", "Programming projects", "Software solutions", "Data processing", "Systems analysis" ], "hardSkillsList" : [ "AI-driven applications", "AI-powered tools", "AI models" ], "softSkillsList" : [ "Curious" ], "hardSkills" : [ { "name" : "AI-driven applications", "level" : "intermediate" }, { "name" : "AI-powered tools", "level" : "intermediate" }, { "name" : "AI models", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Curious" } ], "majorSkills" : "AI/ML, Java development, Software development", "majorSkillsList" : [ "AI/ML", "Java development", "Software development" ], "coreResponsibilities" : "Perform skilled software development work, Partner with AI Strategists to design AI tools, Develop in-house AI tools, Integrate in-house AI tools, Write clean code, Write maintainable code, Write efficient code in Java, Write efficient code in other languages, Develop REST APIs, Connect with REST APIs, Develop data pipelines, Connect with data pipelines, Develop enterprise systems, Connect with enterprise systems, Learn Gen AI SDKs, Utilize Gen AI SDKs, Learn cloud provider services, Utilize cloud provider services, Build solutions with Gen AI, Implement AI models, Fine-tune AI models, Ensure solutions adhere to agency policies, Ensure solutions adhere to data governance, Ensure solutions adhere to accessibility standards, Ensure solutions adhere to security standards, Contribute to software development lifecycle, Oversee programming projects, Analyze proposed applications, Design software solutions", "teamCollaboration" : "Partner with AI Strategists; Work as part of a team", "projectManagementSkills" : [ "Agile methodologies", "DevOps practices" ], "domainKnowledge" : "AI/ML space; Gen AI", "domainList" : [ "ai-ml-space", "gen-ai" ], "domainSpecificKnowledge" : [ "AI/ML space", "Gen AI" ], "toolProficiency" : [ "Gen AI SDKs" ], "communicationSkills" : "Communicate effectively", "continuousLearning" : "Training and development opportunities", "innovationCreativity" : "Innovative ideas", "problemSolvingSkills" : "Problem-solving skills", "specialRequirements" : "Must be a Texas resident, Requires sponsorship for employment visa", "outcomesObjectives" : "Build next generation of AI-powered tools", "qualificationsBasic" : "Four years of full-time experience in data processing, computer science, computer programming, systems analysis, and/or related field, Five years of full-time experience in data processing, computer science, computer programming, systems analysis, and/or related field, Three or more years of full-time experience in software development, Background in Java development, Proficiency and hands-on professional experience in Java, Proficiency and hands-on professional experience in Python development, Experience with building and consuming REST APIs, Experience working with data pipelines, Proficiency in Gen AI prompting, Understanding prompt management techniques, Knowledge of Agile methodologies, Knowledge of DevOps practices, Texas resident or willing to relocate to Texas", "qualificationsPreferred" : "Bachelor’s degree in computer science, engineering, or a related field, Desire to learn about AI/ML technologies, Apply AI/ML to real-world problems, Exposure to cloud AI platforms like AWS, Azure, GCP, or OCI, Experience working in or with public sector or government agencies", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "WHO WE ARE: Texas Workforce Commission connects people with careers across the state. While we are based in Austin on the north lawn of the Texas State Capitol, we have offices statewide. We're a Family Friendly Certified Workplace with great work-life balance, competitive salaries, extensive opportunities for training and development, and fantastic benefits. This position is based at 1411 Brazos Street, Austin in the Information Technology Division. TWC is not considering applications from individuals who require sponsorship for an employment visa, including those currently on student or postgraduate visas. You must be a Texas resident to work for the Texas Workforce Commission or willing to relocate to Texas. WHO YOU ARE: A curious and collaborative developer with a strong foundation in Java development. You are excited by the opportunity to learn new technologies and apply your skills to build the next generation of AI-powered tools for public service. You communicate effectively and enjoy working as part of a team to bring innovative ideas to life. WHAT YOU WILL DO: In this role, you will partner closely with our AI Strategists to design, build, and implement new AI-driven applications and services. The ideal candidate is a strong developer eager to expand their skills into the AI/ML space. The AI Developer (Programmer IV-V) perform advanced to highly advanced (senior-level) computer programming work. Work involves overseeing programming projects, analyzing proposed applications and designing software solutions. This work is performed under minimal supervision, with opportunities for considerable latitude for the use of initiative and independent judgment while learning and growing in the role. YOU WILL BE TRUSTED TO: - Performs skilled software development work. - Partner with two AI Strategists to design, develop, and integrate in-house AI tools and solutions. - Write clean, maintainable, and efficient code in Java and other languages as needed. - Develop and connect with REST APIs, data pipelines, and enterprise systems. - Learn and utilize Gen AI SDKs and services from cloud providers (e.g., AWS, Google, Microsoft, Oracle) to build solutions. - Implement and fine-tune AI models developed in collaboration with the strategy team. - Ensure all solutions adhere to agency policies, data governance, accessibility and security standards. - Contribute to the full software development lifecycle, from initial concept to deployment and maintenance. YOU ARE A GREAT FIT WITH: - Bachelor’s degree in computer science, engineering, or a related field. - Three or more years of full-time experience in software development, with a strong background in Java. - Proficiency and hands-on professional experience in Java and Python development. - Experience with building and consuming REST APIs and working with data pipelines. - A strong desire to learn about AI/ML technologies and apply them to real-world problems. - Proficiency in Gen AI prompting and understanding prompt management techniques for improved outcomes. - Excellent problem-solving skills and the ability to work collaboratively in a team environment. - Knowledge of Agile methodologies and DevOps practices. - Any exposure to cloud AI platforms like AWS, Azure, GCP, or OCI. - Experience working in or with public sector or government agencies. YOU QUALIFY WITH: -Programmer IV: Four years of full-time experience in data processing, computer science, computer programming, systems analysis, and/or related field. -Programmer V: Five years of full-time experience in data processing, computer science, computer programming, systems analysis, and/or related field. -Both Levels: Relevant academic credits may be applied toward experience qualifications for this position. YOU GAIN: - A Family Friendly Certified Workplace - An opportunity to help shape the future of AI in public service - Work on impactful projects that improve services for millions of Texans - Competitive starting salary: $7,000.00 - $9,500.00/month - Defined Retirement Benefit Plan - Optional 401(k) and 457 accounts - Medical Insurance - Paid time off, including time for vacation, sick and family care leave - Additional benefits for active employees can be found at https://www.ers.texas.gov/Active-Employees/Health-Benefits VETERANS: Use your military skills to qualify for this position or other jobs! Go to www.texasskillstowork.com to translate your military work experience and training courses into civilian job terms, qualifications, and skill sets. Also, you can compare this position to military occupations (MOS) at the Texas State Auditor's Office by pasting this link into your browser: https://hr.sao.texas.gov/Compensation/MilitaryCrosswalk/MOSC_InformationTechnology.pdf. HOW TO APPLY: To be considered, please complete a State of Texas Application for Employment and apply online at www.workintexas.com or on Taleo ( Job Search ). TWC is not considering applications from individuals who require sponsorship for an employment visa, including those currently on student or postgraduate visas. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire. A position utilizing this classification will be designated as security sensitive according to the Texas Labor Code, Section 301.042. United States-Texas-Austin", "summaryDescription" : "AI Developer at Texas Workforce Commission. Skills: AI/ML, Java development, Software development. Perform skilled software development work. Partner with AI Strategists to design AI tools", "createdAt" : "2026-06-14T19:53:51.923", "lastUpdated" : "2026-06-15T22:56:59.191", "ingestTimestamp" : "2026-06-14T19:53:51.923", "mongoId" : "69ce5df99bc74574cb671a54", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 145000, "salaryAnnualMax" : 210000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "AI-driven applications", "AI-powered tools", "AI models", "Curious", "AI/ML", "Java development", "Software development", "Programming projects", "Software solutions", "Data processing", "Systems analysis", "Agile methodologies", "DevOps practices", "AI/ML space", "Gen AI", "Gen AI SDKs" ], "skillCount" : 16, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 1213.1432, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Government", "llmIndustryConfidence" : 0.95 }, { "id" : "6a30623cf292fd229cf99656", "title" : "Python Engineer (AI/ML)", "company" : "EVERSANA", "industry" : "Pharmaceuticals", "salary" : { "min" : 1500000.0, "max" : 2500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Python Engineer (AI/ML) in Pune, India, adjusted for the healthcare industry and company size." }, "location" : "Pune, MH, IN", "locations" : [ "Pune", "MH", "IN" ], "timestamp" : "2026-06-16T10:15:09.669", "fingerprint" : "ce5b26b0f8600157b3f0169dbdcfca8721a24bd40420dbc850e285dc30c2a071", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/EVERSANA1/744000132221719-python-engineer-ai-ml-", "externalId" : "744000132221719", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Pune", "state" : "Maharashtra", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "18.5213738,73.8545071" } ], "locationText" : "Pune, Maharashtra, India", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "technicalSkills" : "Python, Cloud platforms, Distributed systems, Machine learning, Deep learning, Large language models, MLOps", "professionalSkills" : [ "System design", "Algorithm design" ], "hardSkillsList" : [ "Algorithm design", "System design" ], "hardSkills" : [ { "name" : "Algorithm design", "level" : "intermediate" }, { "name" : "System design", "level" : "intermediate" } ], "majorSkills" : "AI, Machine Learning, Python", "majorSkillsList" : [ "AI", "Machine Learning", "Python" ], "coreResponsibilities" : "Design and implement AI/ML models, Develop and deploy machine learning solutions, Build and maintain scalable AI infrastructure, Collaborate with cross-functional teams, Research and apply cutting-edge AI techniques, Optimize model performance, Ensure responsible AI development practices", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Artificial intelligence; Machine learning; Large language models; Deep learning", "domainList" : [ "artificial-intelligence", "machine-learning", "large-language-models", "deep-learning" ], "domainSpecificKnowledge" : [ "Artificial intelligence", "Machine learning", "Large language models", "Deep learning" ], "documentationSkills" : "Technical documentation", "continuousLearning" : "Stay current with AI research", "innovationCreativity" : "Research and apply cutting-edge AI techniques", "problemSolvingSkills" : "Troubleshoot model issues; Optimize model performance", "qualificationsBasic" : "5+ years of experience, Bachelor's degree in Computer Science, Experience with Python, Experience with cloud platforms, Experience with distributed systems", "qualificationsPreferred" : "Master's degree or PhD, Experience with large language models, Experience with deep learning frameworks, Experience with MLOps", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "At EVERSANA, we are proud to be certified as a Great Place to Work across the globe. We’re fueled by our vision to create a healthier world. How? Our global team of more than 7,000 employees is committed to creating and delivering next-generation commercialization services to the life sciences industry. We are grounded in our cultural beliefs and serve more than 650 clients ranging from innovative biotech start-ups to established pharmaceutical companies. Our products, services and solutions help bring innovative therapies to market and support the patients who depend on them. Our jobs, skills and talents are unique, but together we make an impact every day. Join us! Across our growing organization, we embrace diversity in backgrounds and experiences. Improving patient lives around the world is a priority, and we need people from all backgrounds and swaths of life to help build the future of the healthcare and the life sciences industry. We believe our people make all the difference in cultivating an inclusive culture that embraces our cultural beliefs. We are deliberate and self-reflective about the kind of team and culture we are building. We look for team members that are not only strong in their own aptitudes but also who care deeply about EVERSANA, our people, clients and most importantly, the patients we serve. We are EVERSANA. We are looking for a Python AI/ML Engineer with hands-on experience in Machine Learning, Large Language Models (LLMs), and backend integration. The ideal candidate will work on building intelligent systems such as chatbots, AI assistants, data-driven APIs, and automation solutions using modern AI/ML frameworks and LLM technologies. Key Responsibilities * Design, develop, and maintain Python-based AI/ML applications * Build and integrate LLM-powered solutions (chatbots, document Q&A, summarization, intent detection) * Implement ML pipelines: data preprocessing, training, evaluation, and inference * Develop and optimize REST APIs using Fast API / Flask * Integrate AI solutions with SQL databases * Work with vector databases (FAISS, Chroma, Pinecone) * Optimize model performance, latency, and cost * Handle prompt engineering and RAG pipelines * Write clean, testable, and well-documented code ## Qualifications Required Skills Programming & Backend * Strong proficiency in Python * Experience with Fast API / Flask * SQL and SQL Alchemy AI / ML * Machine Learning fundamentals * Hands-on experience with LLMs (OpenAI, Azure OpenAI, Hugging Face) * NLP tasks: embeddings, classification, similarity search * Prompt engineering experience Good to Have * RAG architecture experience * Model deployment on CPU/GPU * Docker and cloud basics * On-prem AI deployment experience * LLM fine-tuning knowledge Soft Skills * Problem-solving mindset * Good communication skills * Ability to learn new technologies quickly * Team collaboration skills ## Additional Information OUR CULTURAL BELIEFS: Patient Minded I act with the patient’s best interest in mind. Client Delight I own every client experience and its impact on results. Take Action I am empowered and empower others to act now. Grow Talent I own my development and invest in the development of others. Win Together I passionately connect with anyone, anywhere, anytime to achieve results. Communication Matters I speak up to create transparent, thoughtful and timely dialogue. Embrace Diversity I create an environment of awareness and respect. Always Innovate I am bold and creative in everything I do. Our team is aware of recent fraudulent job offers in the market, misrepresenting EVERSANA. Recruitment fraud is a sophisticated scam commonly perpetrated through online services using fake websites, unsolicited e-mails, or even text messages claiming to be a legitimate company. Some of these scams request personal information and even payment for training or job application fees. Please know EVERSANA would never require personal information nor payment of any kind during the employment process. We respect the personal rights of all candidates looking to explore careers at EVERSANA. From EVERSANA’s inception, Diversity, Equity & Inclusion have always been key to our success. We are an Equal Opportunity Employer, and our employees are people with different strengths, experiences, and backgrounds who share a passion for improving the lives of patients and leading innovation within the healthcare industry. Diversity not only includes race and gender identity, but also age, disability status, veteran status, sexual orientation, religion, and many other parts of one’s identity. All of our employees’ points of view are key to our success, and inclusion is everyone's responsibility. Follow us on [LinkedIn](https://www.linkedin.com/company/eversana/) | [Twitter](https://twitter.com/EVERSANAcompany)", "summaryDescription" : "Python Engineer (AI/ML) at EVERSANA. Skills: AI, Machine Learning, Python. Design and implement AI/ML models. Develop and deploy machine learning solutions", "postedDate" : "2026-06-15T14:39:56.000", "createdAt" : "2026-06-16T00:16:28.703", "lastUpdated" : "2026-06-16T10:15:09.669", "ingestTimestamp" : "2026-06-16T00:16:28.703", "mongoId" : "6a30623cf292fd229cf99656", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Algorithm design", "System design", "AI", "Machine Learning", "Python", "Artificial intelligence", "Machine learning", "Large language models", "Deep learning" ], "skillCount" : 9, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "_score" : 1212.6163, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3071f3f292fd229cffb659", "title" : "Python Engineer (AI/ML)", "company" : "EVERSANA", "industry" : "Pharmaceuticals", "salary" : { "min" : 1500000.0, "max" : 2500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Python Engineer (AI/ML) in Pune, India, adjusted for the healthcare industry and company size." }, "location" : "Pune, MH, IN", "locations" : [ "Pune", "MH", "IN" ], "timestamp" : "2026-06-16T12:34:28.851", "fingerprint" : "893344570b4e50f55fcccb866dc65d3ca352d7d2e67d5a03780d52081b9deff5", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/EVERSANA1/744000132221719-python-engineer-ai-ml-", "externalId" : "744000132221719", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Pune", "state" : "Maharashtra", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "18.5213738,73.8545071" } ], "locationText" : "Pune, Maharashtra, India", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "technicalSkills" : "Python, C++, Java, Go, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Large Language Models, PyTorch, TensorFlow, JAX, Distributed training, GPU computing, Cloud platforms, Kubernetes, Docker, CI/CD, Data pipelines", "professionalSkills" : [ "System design", "Algorithm design" ], "hardSkillsList" : [ "Distributed systems", "Large-scale systems" ], "hardSkills" : [ { "name" : "Distributed systems", "level" : "intermediate" }, { "name" : "Large-scale systems", "level" : "intermediate" } ], "majorSkills" : "Machine Learning, Deep Learning, Large Language Models", "majorSkillsList" : [ "Machine Learning", "Deep Learning", "Large Language Models" ], "coreResponsibilities" : "Design and implement machine learning models, Develop and deploy deep learning systems, Build and maintain large-scale AI infrastructure, Research and apply state-of-the-art AI techniques, Collaborate with cross-functional teams, Contribute to the development of AI products, Optimize AI models for performance and scalability, Stay up-to-date with AI research and trends", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Distributed systems; Large-scale systems; Machine learning; Deep learning; Natural language processing; Computer vision; Reinforcement learning; Large language models", "domainList" : [ "distributed-systems", "large-scale-systems", "machine-learning", "deep-learning", "natural-language-processing", "computer-vision", "reinforcement-learning", "large-language-models" ], "domainSpecificKnowledge" : [ "Distributed systems", "Large-scale systems", "Machine learning", "Deep learning", "Natural language processing", "Computer vision", "Reinforcement learning", "Large language models" ], "toolProficiency" : [ "PyTorch", "TensorFlow", "JAX", "Kubernetes", "Docker" ], "problemSolvingSkills" : "Problem-solving", "qualificationsBasic" : "5+ years of experience, Bachelor's degree in Computer Science, Master's degree in Computer Science, PhD in Computer Science, Experience with Python, Experience with C++, Experience with Java, Experience with Go, Experience with distributed systems, Experience with large-scale systems", "qualificationsPreferred" : "Experience with machine learning, Experience with deep learning, Experience with natural language processing, Experience with computer vision, Experience with reinforcement learning, Experience with large language models, Experience with PyTorch, Experience with TensorFlow, Experience with JAX, Experience with distributed training, Experience with GPU computing, Experience with cloud platforms, Experience with Kubernetes, Experience with Docker, Experience with CI/CD, Experience with data pipelines, Experience with large datasets", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "At EVERSANA, we are proud to be certified as a Great Place to Work across the globe. We’re fueled by our vision to create a healthier world. How? Our global team of more than 7,000 employees is committed to creating and delivering next-generation commercialization services to the life sciences industry. We are grounded in our cultural beliefs and serve more than 650 clients ranging from innovative biotech start-ups to established pharmaceutical companies. Our products, services and solutions help bring innovative therapies to market and support the patients who depend on them. Our jobs, skills and talents are unique, but together we make an impact every day. Join us! Across our growing organization, we embrace diversity in backgrounds and experiences. Improving patient lives around the world is a priority, and we need people from all backgrounds and swaths of life to help build the future of the healthcare and the life sciences industry. We believe our people make all the difference in cultivating an inclusive culture that embraces our cultural beliefs. We are deliberate and self-reflective about the kind of team and culture we are building. We look for team members that are not only strong in their own aptitudes but also who care deeply about EVERSANA, our people, clients and most importantly, the patients we serve. We are EVERSANA. We are looking for a Python AI/ML Engineer with hands-on experience in Machine Learning, Large Language Models (LLMs), and backend integration. The ideal candidate will work on building intelligent systems such as chatbots, AI assistants, data-driven APIs, and automation solutions using modern AI/ML frameworks and LLM technologies. Key Responsibilities * Design, develop, and maintain Python-based AI/ML applications * Build and integrate LLM-powered solutions (chatbots, document Q&A, summarization, intent detection) * Implement ML pipelines: data preprocessing, training, evaluation, and inference * Develop and optimize REST APIs using Fast API / Flask * Integrate AI solutions with SQL databases * Work with vector databases (FAISS, Chroma, Pinecone) * Optimize model performance, latency, and cost * Handle prompt engineering and RAG pipelines * Write clean, testable, and well-documented code ## Qualifications Required Skills Programming & Backend * Strong proficiency in Python * Experience with Fast API / Flask * SQL and SQL Alchemy AI / ML * Machine Learning fundamentals * Hands-on experience with LLMs (OpenAI, Azure OpenAI, Hugging Face) * NLP tasks: embeddings, classification, similarity search * Prompt engineering experience Good to Have * RAG architecture experience * Model deployment on CPU/GPU * Docker and cloud basics * On-prem AI deployment experience * LLM fine-tuning knowledge Soft Skills * Problem-solving mindset * Good communication skills * Ability to learn new technologies quickly * Team collaboration skills ## Additional Information OUR CULTURAL BELIEFS: Patient Minded I act with the patient’s best interest in mind. Client Delight I own every client experience and its impact on results. Take Action I am empowered and empower others to act now. Grow Talent I own my development and invest in the development of others. Win Together I passionately connect with anyone, anywhere, anytime to achieve results. Communication Matters I speak up to create transparent, thoughtful and timely dialogue. Embrace Diversity I create an environment of awareness and respect. Always Innovate I am bold and creative in everything I do. Our team is aware of recent fraudulent job offers in the market, misrepresenting EVERSANA. Recruitment fraud is a sophisticated scam commonly perpetrated through online services using fake websites, unsolicited e-mails, or even text messages claiming to be a legitimate company. Some of these scams request personal information and even payment for training or job application fees. Please know EVERSANA would never require personal information nor payment of any kind during the employment process. We respect the personal rights of all candidates looking to explore careers at EVERSANA. From EVERSANA’s inception, Diversity, Equity & Inclusion have always been key to our success. We are an Equal Opportunity Employer, and our employees are people with different strengths, experiences, and backgrounds who share a passion for improving the lives of patients and leading innovation within the healthcare industry. Diversity not only includes race and gender identity, but also age, disability status, veteran status, sexual orientation, religion, and many other parts of one’s identity. All of our employees’ points of view are key to our success, and inclusion is everyone's responsibility. Follow us on [LinkedIn](https://www.linkedin.com/company/eversana/) | [Twitter](https://twitter.com/EVERSANAcompany)", "summaryDescription" : "Python Engineer (AI/ML) at EVERSANA. Skills: Machine Learning, Deep Learning, Large Language Models. Design and implement machine learning models. Develop and deploy deep learning systems", "postedDate" : "2026-06-15T14:39:56.000", "createdAt" : "2026-06-16T01:39:41.034", "lastUpdated" : "2026-06-16T12:34:28.851", "ingestTimestamp" : "2026-06-16T01:39:41.034", "mongoId" : "6a3071f3f292fd229cffb659", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Distributed systems", "Large-scale systems", "Machine Learning", "Deep Learning", "Large Language Models", "System design", "Algorithm design", "Machine learning", "Deep learning", "Natural language processing", "Computer vision", "Reinforcement learning", "Large language models", "PyTorch", "TensorFlow", "JAX", "Kubernetes", "Docker" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "_score" : 1174.8832, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c92ed74d8ee00a0986e08", "title" : "AI/ML Engineer", "company" : "Xebia", "industry" : "Consulting", "salary" : { "min" : 160000.0, "max" : 240000.0, "currency" : "PLN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for an AI/ML Engineer in Poland, adjusted for mid-level seniority and the technology industry." }, "location" : "Poland", "locations" : [ "Poland" ], "timestamp" : "2026-06-15T04:50:14.996", "fingerprint" : "27ab0b0f18a1b422f8dd60c258eb2ea10494c2d8f8692b7c8c53a64ddaaa5092", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/xebiacee/jobs/5996777004", "externalId" : "5996777004", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Poland", "continent" : "eu", "workMode" : "onsite" } ], "locationText" : "Poland", "experienceMinYears" : 3, "experienceMaxYears" : 6, "experienceLevel" : "Mid", "technicalSkills" : "Python, Scikit-learn, TensorFlow, PyTorch, NLP, LLM, RAG architectures, Prompt engineering, Fine-tuning, MLOps, AWS SageMaker, Azure ML, GCP Vertex AI, Time-series analysis, Anomaly detection", "professionalSkills" : [ "AI agent design", "AI agent development", "ML model development", "Confidence scoring", "Audit trails", "Workflow integration", "Effectiveness measurement", "Effectiveness reporting" ], "hardSkillsList" : [ "ML engineering", "Applied AI", "Model deployment", "Model monitoring", "Model versioning", "CI/CD for ML", "Observability data", "Metrics", "Logs", "Traces", "Events" ], "hardSkills" : [ { "name" : "ML engineering", "level" : "intermediate" }, { "name" : "Applied AI", "level" : "intermediate" }, { "name" : "Model deployment", "level" : "intermediate" }, { "name" : "Model monitoring", "level" : "intermediate" }, { "name" : "Model versioning", "level" : "intermediate" }, { "name" : "CI/CD for ML", "level" : "intermediate" }, { "name" : "Observability data", "level" : "intermediate" }, { "name" : "Metrics", "level" : "intermediate" }, { "name" : "Logs", "level" : "intermediate" }, { "name" : "Traces", "level" : "intermediate" }, { "name" : "Events", "level" : "intermediate" } ], "majorSkills" : "AI/ML Engineering, AIOps, Applied AI, MLOps", "majorSkillsList" : [ "AI/ML Engineering", "AIOps", "Applied AI", "MLOps" ], "coreResponsibilities" : "Design AI agents for operations, Develop AI agents for operations, Build AI KT Agent, Deploy AI KT Agent, Implement Agent Maturity Gate framework, Develop ML models for alert correlation, Develop ML models for anomaly detection, Develop ML models for root-cause prediction, Train models on operational data, Build confidence scoring systems, Deploy agents using Xebia ACE, Maintain audit trails, Collaborate with SRE teams, Collaborate with Automation teams, Integrate agents into workflows, Measure agent effectiveness, Report agent effectiveness", "teamCollaboration" : "SRE teams; Automation teams; Cross-functional teams", "domainKnowledge" : "AI agents; AIOps; MLOps; IT operations; SRE; Incident workflows; Dependency mapping; Change risk prediction; Automated testing", "domainList" : [ "ai-agents", "aiops", "mlops", "it-operations", "sre", "incident-workflows", "dependency-mapping", "change-risk-prediction", "automated-testing" ], "domainSpecificKnowledge" : [ "AI agents", "AIOps", "MLOps", "IT operations", "SRE", "Incident workflows", "Dependency mapping", "Change risk prediction", "Automated testing" ], "toolProficiency" : [ "LangChain", "AutoGen", "Anthropic Claude", "OpenAI APIs", "Xebia ACE" ], "communicationSkills" : "English communication", "problemSolvingSkills" : "Dependency Analysis; Root-cause prediction", "specialRequirements" : "Work permit, Work from EU", "outcomesObjectives" : "Accuracy reporting; False positive rates reporting; Human override frequency reporting", "qualificationsBasic" : "3-6 years of experience, Python skills, ML frameworks experience, NLP/LLM integration experience, MLOps understanding, Cloud ML services experience, Observability data structures knowledge, Time-series analysis familiarity, Anomaly detection familiarity, English communication skills", "qualificationsPreferred" : "LLM-based agent architectures experience, Anthropic Claude or OpenAI APIs familiarity, IT operations or SRE background, Graph-based dependency mapping experience, Change risk prediction knowledge, Automated testing frameworks knowledge", "remoteFriendly" : true, "rawDescription" : "Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture. In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. You will be: designing and developing AI agents for operations: Incident Triage, Dependency Analysis, Runbook Interpreter, Change Risk, building and deploying the AI KT Agent that ingests codebase snapshots, IaC, and 12 months of incident history, implementing the Agent Maturity Gate framework: OBSERVE, RECOMMEND, CONTROLLED EXECUTE, LIMITED AUTONOMY, developing ML models for alert correlation, anomaly detection, and root-cause prediction, training models on operational data within client own repositories (full IP portability), building confidence scoring systems: agents only advance maturity gates when data-validated, deploying agents using Xebia ACE (Anthropic Claude Enterprise) platform across 4 regional instances, maintaining full audit trails for all agent decisions and recommendations, collaborating with SRE and Automation teams to integrate agents into operational workflows, measuring and reporting agent effectiveness: accuracy, false positive rates, human override frequency. Your profile: 3-6 years of experience in ML engineering, AIOps, or applied AI, strong Python skills with ML frameworks (scikit-learn, TensorFlow, PyTorch), experience with NLP and/or LLM integration (RAG architectures, prompt engineering, fine-tuning), understanding of MLOps: model deployment, monitoring, versioning, CI/CD for ML, experience with cloud ML services (AWS SageMaker, Azure ML, GCP Vertex AI), knowledge of observability data structures: metrics, logs, traces, events Familiarity with time-series analysis and anomaly detection techniques, strong English communication skills for cross-functional collaboration. Work from the European Union region and a work permit are required. Nice to have: experience with LLM-based agent architectures (LangChain, AutoGen, or similar), familiarity with Anthropic Claude or OpenAI APIs, background in IT operations or SRE (understanding of incident workflows), experience with graph-based dependency mapping, knowledge of change risk prediction and automated testing frameworks. Recruitment Process: CV review – HR call – Interview – Client Interview – Decision", "summaryDescription" : "AI/ML Engineer at Xebia. Skills: AI/ML Engineering, AIOps, Applied AI, MLOps. Design AI agents for operations. Develop AI agents for operations", "postedDate" : "2026-06-14T03:23:36.788", "createdAt" : "2026-06-14T03:23:36.788", "lastUpdated" : "2026-06-15T04:50:14.996", "ingestTimestamp" : "2026-06-14T03:23:36.788", "mongoId" : "6a2c92ed74d8ee00a0986e08", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "ML engineering", "Applied AI", "Model deployment", "Model monitoring", "Model versioning", "CI/CD for ML", "Observability data", "Metrics", "Logs", "Traces", "Events", "AI/ML Engineering", "AIOps", "MLOps", "AI agent design", "AI agent development", "ML model development", "Confidence scoring", "Audit trails", "Workflow integration", "Effectiveness measurement", "Effectiveness reporting", "AI agents", "IT operations", "SRE", "Incident workflows", "Dependency mapping", "Change risk prediction", "Automated testing", "LangChain", "AutoGen", "Anthropic Claude", "OpenAI APIs", "Xebia ACE" ], "skillCount" : 34, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 1153.1968, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca47a74d8ee00a09b216c", "title" : "AI/ML Engineer", "company" : "Closure Technologies", "industry" : "Government", "salary" : { "min" : 155000.0, "max" : 210000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "The estimated salary is based on 2024-2025 market data for a Senior AI/ML Engineer in Chantilly, United States, with adjustments for industry and company size." }, "location" : "Chantilly, Virginia, United States", "locations" : [ "Chantilly", "Virginia", "United States" ], "timestamp" : "2026-06-15T08:33:32.720", "fingerprint" : "13c0f0400ade2dd0cbce583c18cf4dca775921bd73b71161e1cbf9a6f3716b7f", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/closure-tech/jobs/4255026009", "externalId" : "4255026009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Chantilly", "state" : "Virginia", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "38.8852190,-77.4486772" } ], "locationText" : "Chantilly, Virginia, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 6, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, AI/ML, LLM, RAG, API, Postgres", "professionalSkills" : [ "Technical research", "Problem-solving", "Data organization", "Query performance", "System integration" ], "hardSkillsList" : [ "Retrieval-Augmented Generation", "Large Language Models", "API development", "Data storage optimization", "Postgres schema refinement", "Document processing", "Embedding generation", "Prompt assembly", "REST API interactions", "Data retrieval" ], "hardSkills" : [ { "name" : "Retrieval-Augmented Generation", "level" : "intermediate" }, { "name" : "Large Language Models", "level" : "intermediate" }, { "name" : "API development", "level" : "intermediate" }, { "name" : "Data storage optimization", "level" : "intermediate" }, { "name" : "Postgres schema refinement", "level" : "intermediate" }, { "name" : "Document processing", "level" : "intermediate" }, { "name" : "Embedding generation", "level" : "intermediate" }, { "name" : "Prompt assembly", "level" : "intermediate" }, { "name" : "REST API interactions", "level" : "intermediate" }, { "name" : "Data retrieval", "level" : "intermediate" } ], "majorSkills" : "AI/ML, RAG, LLM integration", "majorSkillsList" : [ "AI/ML", "RAG", "LLM integration" ], "coreResponsibilities" : "Implement RAG pipelines, Maintain RAG pipelines, Process documents, Generate embeddings, Configure retrieval, Assemble prompts, Integrate LLMs into applications, Develop REST API interactions, Maintain REST API interactions, Design Postgres schemas, Refine Postgres schemas", "domainKnowledge" : "Retrieval-Augmented Generation; Large Language Models; Generative AI; Deep learning; Natural language processing; Reinforcement learning; Computer vision; Cloud-native architecture", "domainList" : [ "retrieval-augmented-generation", "large-language-models", "generative-ai", "deep-learning", "natural-language-processing", "reinforcement-learning", "computer-vision", "cloud-native-architecture" ], "domainSpecificKnowledge" : [ "Retrieval-Augmented Generation", "Large Language Models", "Generative AI", "Deep learning", "Natural language processing", "Reinforcement learning", "Computer vision", "Cloud-native architecture" ], "toolProficiency" : [ "Python", "Postgres", "Docker", "AWS" ], "continuousLearning" : "Learn new AI/ML methodologies; Learn new tools; Learn new frameworks", "innovationCreativity" : "Independent technical research; Evaluate emerging AI/ML approaches; Experimental development", "problemSolvingSkills" : "Advanced analytical problem-solving", "specialRequirements" : "TS/SCI with Polygraph, Work onsite full time, US citizenship", "qualificationsBasic" : "Demonstrated ability to conduct independent technical research, Ability to rapidly learn and apply new AI/ML methodologies, Experience developing AI/ML applications, Proficiency in Python, Active/current TS/SCI with required polygraph, US citizenship required, Minimum 8 years of experience with a Bachelor’s, Minimum 7 years of experience with a Masters, Minimum 6 years of experience with a Doctorate", "qualificationsPreferred" : "Advanced research experience in machine learning, Deep learning experience, Natural language processing experience, Generative AI experience, Reinforcement learning experience, Computer vision experience, Experience publishing research, Contributing to open-source AI/ML initiatives, Leading experimental and prototype development efforts, Familiarity with model evaluation frameworks, Familiarity with fine-tuning workflows, Familiarity with inference optimization, Familiarity with AI observability/monitoring tools, Experience with vector databases, Experience with AWS/cloud environments, Experience with Docker, Experience with containerized AI/ML development workflows, Experience designing and integrating REST APIs, Experience with scalable data architectures", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into applications, supported by API development and optimizing data storage through Postgres schema refinement. Clearance Requirement: TS/SCI with Polygraph Key Responsibilities: Implement and maintain RAG pipelines, including document processing, embedding generation, retrieval configuration, and prompt assembly. Integrate LLMs into applications using available APIs and frameworks. Develop and maintain REST API interactions to support data retrieval and system integration. Design or refine Postgres schemas to improve data organization and query performance. Required Qualifications: Demonstrated ability to conduct independent technical research, evaluate emerging AI/ML approaches, and apply advanced analytical problem-solving comparable to PhD-level research environments. Ability to rapidly learn and apply new AI/ML methodologies, tools, and frameworks in support of evolving mission requirements. Experience developing AI/ML applications focused on Retrieval-Augmented Generation (RAG), semantic retrieval, LLM integration, or related AI workflows. Strong proficiency in Python and modern AI/ML libraries, frameworks, and API integrations. Active/current TS/SCI with required polygraph. Willingness to work onsite full time. US citizenship required. Senior Labor Category: Minimum 8 years of experience with a Bachelor’s degree; or 7 years of experience with a Masters degree; or 6 years of experience with a Doctorate Preferred Qualifications: Advanced research experience in machine learning, deep learning, natural language processing, generative AI, reinforcement learning, computer vision, or related disciplines. Experience publishing research, contributing to open-source AI/ML initiatives, or leading experimental and prototype development efforts. Familiarity with model evaluation frameworks, fine-tuning workflows, inference optimization, and AI observability/monitoring tools. Experience with vector databases, AWS/cloud environments, Docker, and containerized AI/ML development workflows. Experience designing and integrating REST APIs and scalable data architectures.", "summaryDescription" : "AI/ML Engineer at Closure Technologies. Skills: AI/ML, RAG, LLM integration. Implement RAG pipelines. Maintain RAG pipelines", "postedDate" : "2026-06-14T03:39:32.277", "createdAt" : "2026-06-14T03:39:32.277", "lastUpdated" : "2026-06-15T08:33:32.720", "ingestTimestamp" : "2026-06-14T03:39:32.277", "mongoId" : "6a2ca47a74d8ee00a09b216c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 155000, "salaryAnnualMax" : 210000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Retrieval-Augmented Generation", "Large Language Models", "API development", "Data storage optimization", "Postgres schema refinement", "Document processing", "Embedding generation", "Prompt assembly", "REST API interactions", "Data retrieval", "AI/ML", "RAG", "LLM integration", "Technical research", "Problem-solving", "Data organization", "Query performance", "System integration", "Generative AI", "Deep learning", "Natural language processing", "Reinforcement learning", "Computer vision", "Cloud-native architecture", "Python", "Postgres", "Docker", "AWS" ], 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"timestamp" : "2026-06-16T10:53:42.065", "fingerprint" : "40208ce92f0fe7dd6698cc73b50928525490fe34327ad198dea430677a4dd475", "source" : "google", "language" : "en", "externalId" : "136390105332884166", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Hyderabad", "state" : "Telangana", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "17.3605890,78.4740613" } ], "locationText" : "Hyderabad, Telangana, India", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "summaryDescription" : "Senior Software Engineer, AI/ML, AI Garage", "postedDate" : "2026-06-16T01:50:32.527", "createdAt" : "2026-06-16T01:50:32.527", "lastUpdated" : "2026-06-16T10:53:42.065", "ingestTimestamp" : "2026-06-16T01:50:32.527", "mongoId" : "6a210e7b74d8ee00a0af7c74", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.5555556, "_score" : 1126.9462, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca5bd74d8ee00a09b7eea", "title" : "Senior Consultant, AI/ML", "company" : "Intellishore", "industry" : "Consulting", "salary" : { "min" : 135000.0, "max" : 175000.0, "currency" : "CHF", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior Consultant, AI/ML in Zurich, Switzerland, adjusted for seniority and industry." }, "location" : "Zurich", "locations" : [ "Zurich" ], "timestamp" : "2026-06-16T06:38:11.666", "fingerprint" : "e88ec4b504f3e32d4af852582f75a4665f2459c7d1ccbe386d27fd8f9c6023b0", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/intellishoredk/jobs/7724694003", "externalId" : "7724694003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Zürich", "country" : "Switzerland", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "47.3744489,8.5410422" } ], "locationText" : "Zürich, Switzerland", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, TensorFlow, PyTorch, Scikit-learn, Pandas, Azure, AWS, GCP, Databricks, LLMs, Vector databases, RAG techniques", "professionalSkills" : [ "Consulting capabilities", "Business solutions", "Technology solutions" ], "hardSkillsList" : [ "Statistics foundations", "Data ingestion", "Model development", "Model training", "Model deployment", "Model monitoring", "Model retraining", "Model governance", "CI/CD", "Automation", "Monitoring strategies", "Retraining strategies" ], "hardSkills" : [ { "name" : "Statistics foundations", "level" : "intermediate" }, { "name" : "Data ingestion", "level" : "intermediate" }, { "name" : "Model development", "level" : "intermediate" }, { "name" : "Model training", "level" : "intermediate" }, { "name" : "Model deployment", "level" : "intermediate" }, { "name" : "Model monitoring", "level" : "intermediate" }, { "name" : "Model retraining", "level" : "intermediate" }, { "name" : "Model governance", "level" : "intermediate" }, { "name" : "CI/CD", "level" : "intermediate" }, { "name" : "Automation", "level" : "intermediate" }, { "name" : "Monitoring strategies", "level" : "intermediate" }, { "name" : "Retraining strategies", "level" : "intermediate" } ], "majorSkills" : "AI/ML, Machine learning models, Generative AI, Automation tools, Data science, MLOps", "majorSkillsList" : [ "AI/ML", "Machine learning models", "Generative AI", "Automation tools", "Data science", "MLOps" ], "coreResponsibilities" : "Develop AI-driven solutions, Build machine learning models, Build generative AI applications, Build automation tools, Shape technology solutions, Implement technology solutions, Shape business solutions, Implement business solutions, Drive design of AI solutions, Drive development of AI solutions, Drive deployment of AI solutions, Guide teams, Support teams, Deliver innovative solutions, Drive business value, Represent data science competencies, Drive projects, Partner with stakeholders, Identify business opportunities, Define best practices, Implement data drift detection, Implement model drift detection, Establish automated retraining triggers, Establish best practices for monitoring, Establish best practices for alerting, Establish best practices for continuous improvement, Stay ahead of industry trends, Drive adoption of emerging technologies, Enhance model accuracy, Enhance model speed, Enhance business applicability, Cultivate culture of innovation, Cultivate culture of continuous learning", "teamCollaboration" : "Cross-functional team; Dedicated Intellishore project team; Small cross-functional team", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "Healthcare; Life sciences; HCP engagement; Clinical development; Real-world evidence; Patient outcomes; Commercial analytics", "domainList" : [ "healthcare", "life-sciences", "hcp-engagement", "clinical-development", "real-world-evidence", "patient-outcomes", "commercial-analytics" ], "domainSpecificKnowledge" : [ "Healthcare", "Life sciences", "HCP engagement", "Clinical development", "Real-world evidence", "Patient outcomes", "Commercial analytics" ], "communicationSkills" : "Stakeholder management", "continuousLearning" : "Continuous learning", "innovationCreativity" : "Innovation; Emerging technologies", "problemSolvingSkills" : "Analytical skills", "specialRequirements" : "On-site presence in Zürich", "outcomesObjectives" : "Deliver measurable impact", "qualificationsBasic" : "3+ years data science experience, 3+ years machine learning experience, 3+ years AI solution delivery experience, Proficiency in Python, Proficiency in data science frameworks, Proficiency in ML frameworks, Hands-on cloud platforms experience, Experience implementing ML solutions at scale, Experience with full ML lifecycle, Excellent communication skills, Excellent stakeholder management skills, Excellent strategic understanding, Availability for on-site presence", "qualificationsPreferred" : "Experience in pharmaceutical industry, Experience in life sciences industry, Hands-on MLOps experience, Experience launching AI/ML solutions to production, Experience using cloud technologies, Fluency in German, Fluency in French, Experience in healthcare industry, Experience in clinical use cases, Experience in medical use cases, Experience in commercial use cases, Experience in supply chain use cases", "workSiteFlexibility" : "Onsite", "rawDescription" : "We are looking for ambitious and passionate AI/ML Senior Consultants to join our fast-growing Zürich office and help develop AI-driven solutions. You will work on building machine learning models, generative AI applications, and automation tools to address key challenges in direct tandem with our healthcare & life sciences clients. About the job Do you want to be part of an exciting journey where you will get plenty of responsibility and influence? Then you need to read on! Being an AI/ML Consultant at Intellishore, you will get to shape and implement technology as well as business solutions to deliver value at our new Intellishore office in Zürich. You will have the opportunity to immerse yourself in some of the most exciting technologies while gaining an in-depth understanding of specific business challenges through close collaboration with your dedicated Intellishore project team and clients. Additionally, by joining Intellishore in Zürich, you will have a unique opportunity to influence and shape the development and commercial growth of Intellishore CH within a highly entrepreneurial and flexible setup, while benefiting from the backing of a family of over 80 Intellishorians in Denmark. Who is Intellishore? Intellishore is an advanced analytics, AI, and strategy consultancy founded in 2013 to provide healthcare & life sciences clients with a seamless combination of strategic and technical expertise. Today, we are more than 80 skilled, entrepreneurial, and passionate employees from many different backgrounds: data engineering, economics, business, marketing, and data science. Intellishore CH is our new entity in Zürich, focused on empowering pharmaceutical companies to realize their AI aspirations. We deliver solutions across the value chain - no project is the same, and the energy is high. What are we looking for in an AI/ML Senior Consultant? We are seeking a highly skilled and experienced AI Consultant to drive the design, development, and deployment of data science, machine learning, and AI solutions at scale. The ideal candidate will bring technical expertise and proven consulting capabilities to guide and support teams in delivering innovative solutions that drive business value. Experience in the pharmaceutical or life sciences industry is a strong plus, as many of our use cases involve HCP engagement, clinical development process optimization, real-world evidence, patient outcomes, and commercial analytics. Also, hands-on experience with MLOps and the launch of AI/ML solutions to production in real-world environments using cloud technologies is a big plus. At Intellishore, we are what you might call ‘agnostic,’ meaning we act as an objective technology partner, implementing only tailored and best-fit solutions for our clients. Therefore, you should be open-minded and curious to learn new technologies. Ideally, you match all or most of the following attributes: Educational background within Computer Science, Data Science, AI/ML, or related field. Solid grasp of statistics foundations. 3+ years of experience in data science, machine learning, or AI solution delivery - preferably from consulting. Proficiency in Python and associated data science/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Pandas). Hands-on experience with cloud platforms (Azure, AWS, GCP, Databricks) for building and deploying AI solutions. Experience in implementing ML solutions at scale in the cloud, covering the full lifecycle: data ingestion, model development, training, deployment, monitoring, retraining, and governance. Knowledge of MLOps practices, including CI/CD, automation, monitoring, and retraining strategies. Excellent communication, stakeholder management, and strategic understanding. Familiarity with LLMs, vector databases, and RAG techniques. Fluency in English, German, or French in addition would be a plus. Availability for on-site presence in Zürich. But do not worry about whether you have too much or too little experience. We are always looking for curious and passionate individuals to join our team, and your title will reflect your level of seniority and expertise. Preferred Qualifications Experience working in or with the pharmaceutical/healthcare industry (clinical, medical, commercial, or supply chain use cases). What will be your key responsibilities? Intellishore is a cross-functional consultancy where you will represent the data science competencies. Here you will be responsible for (among other things): Project Delivery & Strategy Drive projects with a small cross-functional team (data scientists, ML engineers, and strategy consultants) Partner with stakeholders to identify business opportunities where advanced analytics and AI can deliver measurable impact. Define best practices for delivering scalable AI solutions across the entire lifecycle, from experimentation to production. Solution Development & Deployment Design and implement machine learning and AI models using Python and modern ML libraries. Oversee deployment of solutions in cloud environments (Azure, AWS, GCP, or Databricks) with a focus on scalability and reliability. Ensure solutions are production-ready, secure, and compliant with industry standards. MLOps & Lifecycle Management Build and maintain end-to-end MLOps pipelines including CI/CD automation, model versioning, performance monitoring, and retraining workflows. Implement data and model drift detection strategies, along with automated retraining triggers. Establish best practices for monitoring, alerting, and continuous improvement of production ML systems. Innovation & Upskilling Stay ahead of industry trends in AI/ML, cloud platforms, and automation frameworks. Drive adoption of emerging technologies to enhance model accuracy, speed, and business applicability. Cultivate a culture of innovation and continuous learning within the AI team. What can we offer you? 1 | Challenging projects Exciting and challenging project roles in strategic & technical AI projects 2 | Entrepreneurial work environment A highly entrepreneurial work environment with ambitious and innovative colleagues focused on rapidly growing the Intellishore CH business 3 | Influence Unique opportunity for influencing and directing Intellishore CH's market position, commercial growth, and strategic journey 4 | Strategic seminars A yearly strategic seminar where all Intellishorians across locations spend time strategizing and team-building (in previous years, we've been to South Africa, Japan, India, China, Dubai, Iceland, Germany, and Italy) 5 | Sustainable consulting A consulting career with high levels of flexibility, allowing for work-life balance 6 | Exciting growth journey We are on a mission to redefine the world of AI consulting, and we are constantly expanding our reach \"At Intellishore, we work with a principle of always choosing the best person for the job - disregarding seniority and titles. In practice, this means that you will have a major influence on what you'll be doing on a day-to-day basis as well as the level of responsibility you will have.\" Mikkel Møller Andersen Managing Director, Intellishore CH Apply now If you are interested in applying for this position, fill out the application form. Please attach a short, customized motivational letter for this opportunity (generic letters may be overlooked). Applicants will be invited to interviews on a rolling basis. At the moment, we are only accepting applications from applicants in Switzerland", "summaryDescription" : "Senior Consultant, AI/ML at Intellishore. Skills: AI/ML, Machine learning models, Generative AI, Automation tools, Data science, MLOps. Develop AI-driven solutions. Build machine learning models", "postedDate" : "2026-06-14T21:49:14.418", "createdAt" : "2026-06-14T21:49:14.418", "lastUpdated" : "2026-06-16T06:38:11.666", "ingestTimestamp" : "2026-06-14T21:49:14.418", "mongoId" : "6a2ca5bd74d8ee00a09b7eea", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "Statistics foundations", "Data ingestion", "Model development", "Model training", "Model deployment", "Model monitoring", "Model retraining", "Model governance", "CI/CD", "Automation", "Monitoring strategies", "Retraining strategies", "AI/ML", "Machine learning models", "Generative AI", "Automation tools", "Data science", "MLOps", "Consulting capabilities", "Business solutions", "Technology solutions", "Agile", "Healthcare", "Life sciences", "HCP engagement", "Clinical development", "Real-world evidence", "Patient outcomes", "Commercial analytics" ], "skillCount" : 29, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 1126.4437, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Consulting", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c749d74d8ee00a09350b0", "title" : "AI/ML Engineer", "company" : "Kallikor", "industry" : "Kallikor", "salary" : { "min" : 95000.0, "max" : 140000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for Senior AI/ML Engineers in London, UK, adjusted for the logistics industry and company size." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-15T09:22:39.435", "fingerprint" : "9c179b77dca7690d159ebb45e12d041c12a4dcf95924d1e979314b09884f3570", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/kallikor/13d4cf35-0aa4-4b7d-808c-bfe32808b6ed/application", "externalId" : "13d4cf35-0aa4-4b7d-808c-bfe32808b6ed", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, FastAPI, PydanticAI, FastMCP, Memgraph, Postgres, PyTorch, Unsloth, Axolotl, VLLM, Weights & Biases, AWS, Docker, Kubernetes, Qwen 2.5, Llama 3.1, GPT-4, Claude", "professionalSkills" : [ "System design", "Production engineering", "MLOps", "Data pipelines", "Inference endpoints", "Monitoring", "Observability", "Performance optimization", "Incremental learning", "Code review", "Pair programming", "Code quality", "Testing practices", "Production practices" ], "hardSkillsList" : [ "Async/await", "Generators", "Lists", "Performance profiling", "Model fine-tuning", "Model training", "Model evaluation", "Model debugging", "Failure design", "Instrumentation", "Edge case consideration", "Monitoring", "Logging", "Alerting", "Graceful degradation", "Transformer architecture", "Attention mechanisms", "Training dynamics", "Heuristic development", "Code refactoring", "Test writing", "Trade-off communication" ], "hardSkills" : [ { "name" : "Async/await", "level" : "intermediate" }, { "name" : "Generators", "level" : "intermediate" }, { "name" : "Lists", "level" : "intermediate" }, { "name" : "Performance profiling", "level" : "intermediate" }, { "name" : "Model fine-tuning", "level" : "intermediate" }, { "name" : "Model training", "level" : "intermediate" }, { "name" : "Model evaluation", "level" : "intermediate" }, { "name" : "Model debugging", "level" : "intermediate" }, { "name" : "Failure design", "level" : "intermediate" }, { "name" : "Instrumentation", "level" : "intermediate" }, { "name" : "Edge case consideration", "level" : "intermediate" }, { "name" : "Monitoring", "level" : "intermediate" }, { "name" : "Logging", "level" : "intermediate" }, { "name" : "Alerting", "level" : "intermediate" }, { "name" : "Graceful degradation", "level" : "intermediate" }, { "name" : "Transformer architecture", "level" : "intermediate" }, { "name" : "Attention mechanisms", "level" : "intermediate" }, { "name" : "Training dynamics", "level" : "intermediate" }, { "name" : "Heuristic development", "level" : "intermediate" }, { "name" : "Code refactoring", "level" : "intermediate" }, { "name" : "Test writing", "level" : "intermediate" }, { "name" : "Trade-off communication", "level" : "intermediate" } ], "majorSkills" : "AI/ML, LLMs, Production systems, Python engineering", "majorSkillsList" : [ "AI/ML", "LLMs", "Production systems", "Python engineering" ], "coreResponsibilities" : "Build production AI systems, Design full stack, Implement FastAPI endpoints, Create training pipelines, Deploy inference services, Own architecture, Train DSLM, Fine-tune models, Build infrastructure, Create data pipelines, Build evaluation frameworks, Build deployment systems, Integrate ML into backend, Extend systems with ML, Ensure clean abstractions, Ensure proper error handling, Ensure observability, Own inference performance, Optimize model speed, Hit latency targets, Shape Project Genome foundation, Architect data ingestion, Process supply chain data, Synthesize supply chain knowledge, Raise code quality bar, Raise testing bar, Raise production practices bar, Teach engineers ML systems", "teamCollaboration" : "Principal Engineer; Mid Data/ML Engineer; Junior AI Engineer; Cross-functional teams", "projectManagementSkills" : [ "Agile", "Scrum", "JIRA" ], "domainKnowledge" : "Supply chain intelligence; Digital twins; Supply chains; Warehouses; Distribution networks; Global logistics; Domain-specific language model; Project Genome; Supply chain knowledge; Actionable intelligence; Production engineering; ML/LLMs; Transformer architecture; Attention mechanisms; Training dynamics; Prompt engineering; Context management; Rate limits; Retries; Model fine-tuning; Model training; Model evaluation; Model debugging; Systems design; Data pipelines; Graph databases; Incremental learning; LoRA; Full fine-tuning; QLoRA; DeepSpeed; FSDP; Memgraph; Neo4j; Agent frameworks; Qwen 2.5; Llama 3.1; GPT-4; Claude; AWS; Docker; Kubernetes; vLLM; Weights & Biases", "domainList" : [ "supply-chain-intelligence", "digital-twins", "supply-chains", "warehouses", "distribution-networks", "global-logistics", "domain-specific-language-model", "project-genome", "supply-chain-knowledge", "actionable-intelligence", "production-engineering", "ml-llms", "transformer-architecture", "attention-mechanisms", "training-dynamics", "prompt-engineering", "context-management", "rate-limits", "retries", "model-fine-tuning", "model-training", "model-evaluation", "model-debugging", "systems-design", "data-pipelines", "graph-databases", "incremental-learning", "lora", "full-fine-tuning", "qlora", "deepspeed", "fsdp", "memgraph", "neo4j", "agent-frameworks", "qwen-2-5", "llama-3-1", "gpt-4", "claude", "aws", "docker", "kubernetes", "vllm", "weights-biases" ], "domainSpecificKnowledge" : [ "Supply chain intelligence", "Digital twins", "Supply chains", "Warehouses", "Distribution networks", "Global logistics", "Domain-specific language model", "Project Genome", "Supply chain knowledge", "Actionable intelligence", "Production engineering", "ML/LLMs", "Transformer architecture", "Attention mechanisms", "Training dynamics", "Prompt engineering", "Context management", "Rate limits", "Retries", "Model fine-tuning", "Model training", "Model evaluation", "Model debugging", "Systems design", "Data pipelines", "Graph databases", "Incremental learning", "LoRA", "Full fine-tuning", "QLoRA", "DeepSpeed", "FSDP", "Memgraph", "Neo4j", "Agent frameworks", "Qwen 2.5", "Llama 3.1", "GPT-4", "Claude", "AWS", "Docker", "Kubernetes", "vLLM", "Weights & Biases" ], "toolProficiency" : [ "FastAPI", "PydanticAI", "FastMCP", "Memgraph", "Unsloth", "Axolotl", "VLLM", "Weights & Biases", "Docker", "Kubernetes", "AWS", "Git", "JIRA" ], "communicationSkills" : "Communicate trade-offs", "problemSolvingSkills" : "Debug complex systems; Debug model learning; Troubleshooting", "outcomesObjectives" : "Hit <200ms latency targets", "qualificationsBasic" : "Production Python engineer, Built FastAPI services, Built with LLMs, Handled streaming responses, Dealt with rate limits, Dealt with retries, Cached intelligently, Prompt engineering, Context management, Error handling, Cost control, Trained or fine-tuned models, Dealt with training data, Dealt with evaluation metrics, Dealt with overfitting, Debugged model learning, Systems engineer mindset, Designed for failure, Added instrumentation, Considered edge cases, Cared about monitoring, Cared about logging, Cared about alerting, Cared about degradation, Understood transformers, Understood attention mechanisms, Understood training dynamics, Balanced velocity with quality, Proactively refactored, Wrote tests that matter, Communicated trade-offs clearly", "qualificationsPreferred" : "Fine-tuning experience, Distributed training basics, Graph databases experience, Supply chain domain knowledge, Logistics domain knowledge, Agent frameworks experience", "remoteFriendly" : true, "rawDescription" : "At Kallikor, we're building the future of supply chain intelligence through AI-powered simulation digital twins. We create living digital representations of real-world operations (warehouses, distribution networks, global logistics) that help organisations make better decisions faster. We're at an inflection point: moving from AI-assisted tools to domain-specific AI that understands supply chains as deeply as our best engineers do. You'll be instrumental in building our first domain-specific language model (DSLM) and the foundation for Project Genome, an ambitious initiative to capture and synthesise the world's supply chain knowledge into actionable intelligence. This is a production engineering role first. You'll build robust Python systems that happen to train and serve LLMs, not the other way around. We need someone who writes production-quality code, debugs complex distributed systems, and thinks about reliability, who has learned ML/LLMs as powerful tools in their engineering arsenal. You'll work across our entire AI stack: building FastAPI services that serve models, creating training pipelines that process production data, deploying inference endpoints with proper monitoring, and integrating all of this into our existing Python backend. The ML is important, but the engineering discipline is what makes it production-ready. Learn more at kallikor.ai http://kallikor.ai. YOUR OPPORTUNITY - Build production AI systems: Design and implement the full stack, from FastAPI endpoints that handle requests, to training pipelines that process data, to inference services that serve predictions. You'll own the architecture, not just the model weights. - Train and deploy our DSLM: Fine-tune models using Unsloth/Axolotl, but more importantly, build the robust infrastructure around it - data pipelines that feed training, evaluation frameworks that catch regressions, deployment systems that handle failover. Make it production-grade. - Integrate ML into our backend: We use FastAPI, PydanticAI, FastMCP, Memgraph. You'll extend these systems with ML capabilities, not as a separate \"ML service\" but as a natural part of our backend architecture. Clean abstractions, proper error handling, observability. - Own inference performance: Get models running fast, whether that's vLLM deployment, quantization strategies, batching optimizations, or caching. Hit our <200ms latency targets through engineering, not just throwing bigger GPUs at it. - Shape Project Genome's foundation: Work with our Principal Engineer to architect how we ingest, process, and learn from global supply chain data. This is systems design as much as ML with data pipelines, graph databases, incremental learning strategies being just as important. - Mentor through code review and pairing: Raise the bar on code quality, testing, and production practices across the team. Teach mid and junior engineers how to build ML systems that don't fall over. WHY YOU'RE MADE FOR THIS - You're a strong production Python engineer: You write clean, maintainable, tested code. You understand async/await, know when to use generators vs lists, can profile performance bottlenecks. You've built FastAPI services (or similar) that handle production traffic. Your code passes review without drama. - You've built with LLMs in production: You've integrated GPT-4/Claude into real applications, handled streaming responses, dealt with rate limits and retries, cached intelligently. You know the practical challenges: prompt engineering, context management, error handling, cost control. - You've trained or fine-tuned models: Whether it's fine-tuning LLMs, training classifiers, or running experiments, you understand the workflow. You've dealt with training data quality, evaluation metrics, and overfitting. You can debug why a model isn't learning what you expected. - You think like a systems engineer: You design for failure, add instrumentation, consider edge cases. You know that \"the model works on my laptop\" isn't shipping. You care about monitoring, logging, alerting, and graceful degradation. - You can navigate the ML landscape pragmatically: You know enough about transformers, attention mechanisms, and training dynamics to make informed decisions. But you're not precious about it. If a simple heuristic beats a complex model, you ship the heuristic. - You balance velocity with quality: You ship incrementally and iterate based on production data. But you don't accumulate tech debt, you refactor proactively, write tests that matter, and leave the codebase better than you found it. - You communicate trade-offs clearly: You can explain to the team why we're choosing LoRA over full fine-tuning, why we're deploying on Fireworks instead of self-hosting, or why a 7B model might beat a 70B model. You help everyone make informed decisions. WHAT WE'RE LOOKING FOR SPECIFICALLY Must have: - 5+ years building production Python systems (backend services, APIs, data processing) - Strong software engineering fundamentals: design patterns, testing, debugging, profiling - Experience integrating LLMs into applications (OpenAI/Anthropic APIs, prompt engineering, streaming, PydanticAI) - Understanding of ML training workflows (even if you're not an expert. You need to know enough to build the infrastructure) - Docker, CI/CD, production deployment experience - Can read and understand PyTorch code (you don't need to write novel architectures) Nice to have: - Fine-tuning experience (LoRA, full fine-tuning, QLoRA) - Distributed training basics (DeepSpeed, FSDP) - Graph databases (Memgraph, Neo4j) - Supply chain or logistics domain knowledge - Experience with agent frameworks (LangChain, PydanticAI, etc.) WHAT YOU'LL WORK WITH - Backend Stack: Python, FastAPI, PydanticAI, FastMCP, Memgraph, Postgres - ML Stack: PyTorch, Unsloth/Axolotl for training, vLLM for inference, Weights & Biases - Models: Qwen 2.5, Llama 3.1, GPT-4, Claude (for now) - Infrastructure: AWS (flexible), Docker, Kubernetes, GPUs when needed - Team: Principal Engineer (your partner on architecture), Mid Data/ML Engineer (your data pipeline partner), Junior AI Engineer (your mentee) EXAMPLE PROJECTS YOU'LL OWN - Build a FastAPI service that handles streaming LLM responses with correct error handling and retry logic - Create a training pipeline that processes production logs, validates data quality, and triggers fine-tuning runs - Deploy a fine-tuned 7B model with vLLM that beats GPT-4 latency while maintaining quality on our domain - Design the data ingestion architecture for Project Genome, how we process papers, documentation, and operational data at scale - Implement evaluation frameworks that catch model regressions before they reach production About Us Kallikor is determined to foster an environment where people can do their best work and feel like they belong. We believe a healthy culture, strong values and contribution from a diverse range of individuals will help us to achieve success. We do not discriminate based on race, ethnicity, gender, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran status, genetic information, marital status or any other legally protected status.", "summaryDescription" : "AI/ML Engineer at Kallikor. Skills: AI/ML, LLMs, Production systems, Python engineering. Build production AI systems. Design full stack", "createdAt" : "2026-06-14T06:34:57.632", "lastUpdated" : "2026-06-15T09:22:39.435", "ingestTimestamp" : "2026-06-14T06:34:57.632", "mongoId" : "6a2c749d74d8ee00a09350b0", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Async/await", "Generators", "Lists", "Performance profiling", "Model fine-tuning", "Model training", "Model evaluation", "Model debugging", "Failure design", "Instrumentation", "Edge case consideration", "Monitoring", "Logging", "Alerting", "Graceful degradation", "Transformer architecture", "Attention mechanisms", "Training dynamics", "Heuristic development", "Code refactoring", "Test writing", "Trade-off communication", "AI/ML", "LLMs", "Production systems", "Python engineering", "System design", "Production engineering", "MLOps", "Data pipelines", "Inference endpoints", "Observability", "Performance optimization", "Incremental learning", "Code review", "Pair programming", "Code quality", "Testing practices", "Production practices", "Agile", "Scrum", "JIRA", "Supply chain intelligence", "Digital twins", "Supply chains", "Warehouses", "Distribution networks", "Global logistics", "Domain-specific language model", "Project Genome", "Supply chain knowledge", "Actionable intelligence", "ML/LLMs", "Prompt engineering", "Context management", "Rate limits", "Retries", "Systems design", "Graph databases", "LoRA", "Full fine-tuning", "QLoRA", "DeepSpeed", "FSDP", "Memgraph", "Neo4j", "Agent frameworks", "Qwen 2.5", "Llama 3.1", "GPT-4", "Claude", "AWS", "Docker", "Kubernetes", "vLLM", "Weights & Biases", "FastAPI", "PydanticAI", "FastMCP", "Unsloth", "Axolotl", "VLLM", "Git" ], "skillCount" : 83, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.7777778, "_score" : 1118.1208, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Logistics", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2cd5f974d8ee00a0a3c9c4", "title" : "Staff Engineer AI/ML", "company" : "AnswersNow", "industry" : "Engineering", "salary" : { "min" : 150000.0, "max" : 215000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "Remote", "locations" : [ "Remote" ], "timestamp" : "2026-06-16T01:55:30.858", "fingerprint" : "6a4f60561be6179ed2e3bde1a7aa84a4c8eb5180ba8ba10a1fb49da27e82bf54", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/AnswersNow/77f6d0e2-adb8-47b8-98bd-d0bd2c5d23a2/application", "externalId" : "77f6d0e2-adb8-47b8-98bd-d0bd2c5d23a2", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Bulgaria", "continent" : "eu", "workMode" : "remote" } ], "locationText" : "Bulgaria", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "JavaScript, TypeScript, React, Node.js, Express, Postgres, AWS, ECS, RDS, S3, Lambda, ETL, AI, LLM, Event-driven architectures, Message queues, Streaming pipelines", "professionalSkills" : [ "System design", "Technical mentorship", "Architecture discussions", "Technical strategy", "Production support", "Incident response" ], "hardSkillsList" : [ "Full-stack development", "Data pipeline architecture", "ML/AI system architecture", "Model lifecycle management" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Full-stack development", "level" : "intermediate" }, { "name" : "Data pipeline architecture", "level" : "intermediate" }, { "name" : "ML/AI system architecture", "level" : "intermediate" }, { "name" : "Model lifecycle management", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "AI/ML, Full-stack development, Distributed systems, Data pipelines", "majorSkillsList" : [ "AI/ML", "Full-stack development", "Distributed systems", "Data pipelines" ], "coreResponsibilities" : "Own platform architecture, Evolve platform architecture, Drive JavaScript to TypeScript migration, Establish migration patterns, Establish migration tooling, Establish migration standards, Design ETL pipeline, Extend ETL pipeline, Design AI integration framework, Extend AI integration framework, Lead technical design reviews, Create architecture decision records, Ensure engineering decisions documented, Ensure engineering decisions defensible, Identify systemic technical debt, Resolve systemic technical debt, Define technical strategy for ML/AI integration, Execute technical strategy for ML/AI integration, Ensure scalability, Ensure performance, Ensure reliability, Mentor engineers, Pair engineers, Review code, Coach engineers, Grow team capability, Establish engineering standards, Maintain engineering standards, Serve as technical resource, Serve as thought partner, Help define engineering hiring bar, Participate in interview process, Partner with engineering leadership, Partner with product leadership, Scope technical initiatives, Sequence technical initiatives, De-risk technical initiatives, Lead by example on production support, Define runbooks, Own post-mortems, Drive systemic fixes from incidents, Work across UI layers, Work across API layers, Work across DB layers, Work across infrastructure layers", "teamCollaboration" : "Partner with CTO; Partner with product leadership; Partner with clinical stakeholders; Cross-functional teams", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Autism therapy; Virtual ABA therapy; Distributed systems; Data pipeline architectures; ETL pipelines; AI/LLM integration; Data-intensive systems; ML/AI systems; Model lifecycle management; Healthcare data environments; Regulated data environments; HIPAA compliance; PHI handling; Event-driven architectures; Message queues; Streaming pipelines", "domainList" : [ "autism-therapy", "virtual-aba-therapy", "distributed-systems", "data-pipeline-architectures", "etl-pipelines", "ai-llm-integration", "data-intensive-systems", "ml-ai-systems", "model-lifecycle-management", "healthcare-data-environments", "regulated-data-environments", "hipaa-compliance", "phi-handling", "event-driven-architectures", "message-queues", "streaming-pipelines" ], "domainSpecificKnowledge" : [ "Autism therapy", "Virtual ABA therapy", "Distributed systems", "Data pipeline architectures", "ETL pipelines", "AI/LLM integration", "Data-intensive systems", "ML/AI systems", "Model lifecycle management", "Healthcare data environments", "Regulated data environments", "HIPAA compliance", "PHI handling", "Event-driven architectures", "Message queues", "Streaming pipelines" ], "toolProficiency" : [ "Node.js/Express", "Postgres", "AWS ECS", "AWS RDS", "AWS S3", "AWS Lambda" ], "communicationSkills" : "Architecture docs; Design reviews; Brief executives", "documentationSkills" : "Architecture decision records", "problemSolvingSkills" : "Root cause analysis", "qualificationsBasic" : "8+ years software engineering experience, 3+ years senior/staff level role, Deep expertise in JavaScript, Deep expertise in TypeScript, Production full-stack environment experience, Command of React, Command of Node.js/Express, Command of Postgres, Experience designing distributed systems, Experience owning distributed systems, Experience designing data pipeline architectures, Experience owning data pipeline architectures, Track record of technical mentorship, Excellent written communication, Excellent verbal communication, Experience in growth-stage startup", "qualificationsPreferred" : "AWS ECS experience valued, AWS RDS experience valued, AWS S3 experience valued, AWS Lambda experience valued, Familiarity with ETL pipelines, Familiarity with AI/LLM integration patterns, Familiarity with data-intensive systems, Experience with healthcare environments, Experience with regulated data environments, HIPAA compliance experience, PHI handling experience, Familiarity with event-driven architectures, Familiarity with message queues, Familiarity with streaming pipelines, Prior experience as engineering manager, Contributions to open source, Engineering blog posts contributions, Conference talks contributions", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Staff Engineer AI/ML Remote, Anywhere in the US About AnswersNow At AnswersNow, we are trailblazing the future of autism therapy, making it more immediate, accessible, and effective for families everywhere. Our innovative virtual ABA therapy platform is thoughtfully designed by clinicians to recreate the focused, supportive environment of in-person therapy, complete with distraction-free features and interactive activities that enhance engagement and progress. Our team operates fully remote—meaning you’ll have the flexibility to work from the comfort of home. If you're ready to make a meaningful impact and join a team that's reshaping autism therapy, we’d love to hear from you! Why this role matters: We're looking for a Senior Engineering Manager who knows that great engineering leadership is about growing people, removing obstacles, and making the team better — not writing the most code. You've led teams before. You know how to hold a high bar for craft while keeping engineers energized and growing. You understand that a team of four highly effective engineers with strong habits will outperform a team of twelve with unclear expectations. You'll manage a team of Engineering Team Leads, each of whom runs a squad of full-stack engineers. You own the health of the engineering organization: hiring, performance, culture, delivery, and the processes that keep everything running. You partner closely with the CTO, product leadership, and clinical stakeholders to ensure engineering is building the right things, the right way. This is a player-coach role in spirit — you should be technically credible and able to engage meaningfully in architecture discussions — but your primary output is team output, not individual code. Job Details - W2 Employee - Full-Time - 100% Remote Job Requirements - 8+ years of professional software engineering experience, with at least 3 years in a senior or staff-level role - Deep expertise in JavaScript and TypeScript in a production full-stack environment - Strong command of React, Node.js/Express, and Postgres — you can reason about performance, reliability, and maintainability at each layer - Proven experience designing and owning distributed systems or data pipeline architectures on AWS (ECS, RDS, S3, Lambda experience valued) - Track record of technical mentorship — you've made engineers around you measurably better - Excellent written and verbal communication; you can write an architecture doc, run a design review, and brief a non-technical executive in the same day - Experience working in or leading engineering at a growth-stage startup — you understand the balance between velocity and sustainability - Familiarity with ETL pipelines, AI/LLM integration patterns, or data-intensive systems is a strong plus - Significant experience architecting and deploying production-grade ML/AI systems, including LLM integration and model lifecycle management. Nice to have: - Experience with healthcare or regulated data environments (HIPAA compliance, PHI handling) - Familiarity with event-driven architectures, message queues, or streaming pipelines - Prior experience as an engineering manager who returned to an IC track (player-coach background welcome) - Contributions to open source or engineering blog posts / conference talks What You’ll Do Technical Leadership - Own and evolve the architecture of our core platform: React frontend, Node.js/Express APIs, Postgres, and AWS ECS infrastructure - Drive our JavaScript → TypeScript migration, establishing patterns, tooling, and standards the team can follow - Design and extend our ETL pipeline and config-driven AI integration framework, enabling engineers to ship AI-powered features faster and more reliably - Lead technical design reviews, create architecture decision records (ADRs), and ensure engineering decisions are documented and defensible - Identify and resolve systemic technical debt — not just flagging it, but owning the plan to address it - Define and execute the technical strategy for integrating ML/AI models into our core platform, ensuring scalability, performance, and reliability. Engineering Culture & Mentorship - Mentor engineers across all levels — pair, review, coach, and grow the team's collective capability - Establish and maintain engineering standards: code quality, testing practices, observability, on-call runbooks, and incident response - Serve as a technical resource and thought partner for product, clinical, and business stakeholders - Help define the engineering hiring bar and participate in the interview process Delivery & Operations - Partner with engineering leadership and product to scope, sequence, and de-risk large technical initiatives - Lead by example on production support — define runbooks, own post-mortems, and drive systemic fixes from incidents - Work across UI, API, DB, and infrastructure layers with genuine depth in at least two What we Offer - $151,000- $178,500 annual salary - Fully remote – work from anywhere in the U.S. - Flexible hours with an async-friendly team culture More About AnswersNow AnswersNow welcomes applicants of all backgrounds, experiences, and abilities. We believe a diverse team is a strong team, and are committed to provide a fair and equitable experience for every candidate. If you require reasonable accommodations at any stage, we encourage you to reach out. We’re here to support! Learn more about us at getanswersnow.com http://getanswersnow.com.", "summaryDescription" : "Staff Engineer AI/ML at AnswersNow. Skills: AI/ML, Full-stack development, Distributed systems, Data pipelines. Own platform architecture. Evolve platform architecture", "createdAt" : "2026-06-14T18:40:37.087", "lastUpdated" : "2026-06-16T01:55:30.858", "ingestTimestamp" : "2026-06-14T18:40:37.087", "mongoId" : "6a2cd5f974d8ee00a0a3c9c4", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 150000, "salaryAnnualMax" : 215000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Full-stack development", "Data pipeline architecture", "ML/AI system architecture", "Model lifecycle management", "Leadership", "AI/ML", "Distributed systems", "Data pipelines", "System design", "Technical mentorship", "Architecture discussions", "Technical strategy", "Production support", "Incident response", "Roadmap planning", "Autism therapy", "Virtual ABA therapy", "Data pipeline architectures", "ETL pipelines", "AI/LLM integration", "Data-intensive systems", "ML/AI systems", "Healthcare data environments", "Regulated data environments", "HIPAA compliance", "PHI handling", "Event-driven architectures", "Message queues", "Streaming pipelines", "Node.js/Express", "Postgres", "AWS ECS", "AWS RDS", "AWS S3", "AWS Lambda" ], "skillCount" : 35, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "_score" : 1109.0681, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3057a0f292fd229cf3c3e9", "title" : "Quality Engineering Intern, AI/ML", "company" : "Rocket Lawyer", "industry" : "Legal", "salary" : { "min" : 40.0, "max" : 50.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Arizona ", "locations" : [ "Arizona", "California", "Colorado", "North Carolina", "Utah" ], "timestamp" : "2026-06-16T07:39:49.821", "fingerprint" : "d717137b205e7ef1ba98047f11de50336e2931c5e8b3311e4503f941be359937", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/rocketlawyer/jobs/5263173008", "externalId" : "5263173008", "industryFunction" : { }, "structuredLocations" : [ { "state" : "California", "country" : "United States", "continent" : "na", "workMode" : "remote" }, { "state" : "Arizona", "country" : "United States", "continent" : "na", "workMode" : "remote" }, { "state" : "Colorado", "country" : "United States", "continent" : "na", "workMode" : "remote" }, { "state" : "North Carolina", "country" : "United States", "continent" : "na", "workMode" : "remote" }, { "state" : "Utah", "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "California, United States; Arizona, United States; Colorado, United States; North Carolina, United States; Utah, United States", "employmentType" : "INTERNSHIP", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "remoteFriendly" : true, "rawDescription" : "About Rocket Lawyer We believe everyone deserves access to affordable and simple legal services. Founded in 2008, Rocket Lawyer is the largest and most widely used online legal service platform in the world. With offices in North America, South America, and Europe, Rocket Lawyer has helped over 30 million people create over 50 million legal documents, and get their legal questions answered. We are in a unique position to enhance and expand the Rocket Lawyer platform to a scale never seen before in the company’s history, to capture audiences worldwide. We are expanding our team to take on this challenge! About your role Join our team as a Quality Engineering Intern on the AI/ML team at Rocket Lawyer, where you'll have the exciting opportunity to contribute to the testing of applications for Rocket Copilot, our AI Product. This internship offers hands-on experience in the software development process, and you'll collaborate closely with a talented, diverse, and global test team. Your work will directly impact the quality of Rocket Lawyer’s products, all while gaining valuable insights into industry best practices for software development and test automation. In this role, you'll dive into various areas of test automation, including mobile, partnerships, web frontend, and performance testing. This internship provides a unique chance to apply your skills and learn innovative testing and automation techniques, all while receiving mentorship from experienced professionals in the field. If you're eager to contribute to real-world projects and grow your expertise, we would love to have you join us! How you will make a difference day to day Assist with the creation and execution of automated tests for mobile applications. Partnerships Test Automation: Develop automated test scripts for integrations with external partners. Contribute to the automation of testing for marketing sites and Google Tag Manager functionality. Help build and execute automated test cases for web frontend applications and authoring tools. Assist in identifying and measuring system performance to ensure optimal functionality under varying loads. Actively participate in daily scrum meetings, collaborating with team members and engineers to align on priorities and tasks. Support in the building, execution, and delivery of automated test scripts and results. What you’ll need Graduate Student, Recent Graduate, or in your Senior year: Pursuing a technical degree in computer science, engineering, mathematics, or a related field. Familiarity with Javascript/Typescript and Python. A strong desire to expand your knowledge, improve technical skills, and grow within a collaborative environment. We encourage applicants from all backgrounds and communities to apply. We believe that diverse perspectives strengthen our teams and enhance the quality of our work. Interview Process Recruiter Phone Screen Hiring Manager Interview Team Interview Rocket Lawyer is proudly committed to recruiting and retaining a diverse and inclusive workforce. As an Equal Opportunity Employer, we never discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, military or veteran status, status as an individual with a disability, or other applicable legally protected characteristics. We particularly welcome applications from veterans and military spouses. All your information will be kept confidential according to EEO guidelines. You may request reasonable accommodations by sending an email to hr@rocketlawyer.com. Location: Remote, but you must be located in CA, AZ, CO, NC, or UT during the internship. Compensation per hour by location: San Francisco Bay Area, CA: $50.00 California (outside of San Francisco Bay Area): $46.25 Colorado: $42.50 Utah, Arizona, and North Carolina: $40.00 Actual compensation packages are determined by various factors unique to each candidate, including but not limited to skill set, depth of experience, certifications, specific work location, and performance during the interview process. In addition to base salary, this role may include variable compensation and be eligible for an equity grant, depending on the position and level. Base salary range: $40—$50 USD By applying for this position, your data will be processed as per Rocket Lawyer Privacy Policy.", "summaryDescription" : "Quality Engineering Intern, AI/ML at Rocket Lawyer", "postedDate" : "2026-06-15T23:24:24.217", "createdAt" : "2026-06-15T23:24:24.217", "lastUpdated" : "2026-06-16T07:39:49.821", "ingestTimestamp" : "2026-06-15T23:24:24.217", "mongoId" : "6a3057a0f292fd229cf3c3e9", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 83200, "salaryAnnualMax" : 104000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "_score" : 1088.4834, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Legal", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c8c8374d8ee00a0975b4b", "title" : "Senior AI/ML Researcher (Foundation AI)", "company" : "WHOOP", "industry" : "Foundation AI", "salary" : { "min" : 190000.0, "max" : 230000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, MA", "locations" : [ "Boston, MA" ], "timestamp" : "2026-06-15T10:23:49.495", "fingerprint" : "f94b434fec5274b93a65a2c8db669cbf49d9627e4867298394efdd5d6cf9e3f2", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/whoop/85da87ff-c1a6-4fcd-8c7c-162e57b18281/application", "externalId" : "85da87ff-c1a6-4fcd-8c7c-162e57b18281", "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" : "Master's", "experienceMinYears" : 7, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, PyTorch, TensorFlow, Deep learning, Transformers, State space models, Representation learning, Self-supervised learning", "professionalSkills" : [ "Model optimization", "Applied research", "Scalable training", "Distributed training", "Production deployment", "Technical roadmap", "Architectural direction" ], "hardSkillsList" : [ "Multimodal model training", "Large-scale modeling", "Data parallelisms", "Model parallelisms", "Context parallelisms" ], "hardSkills" : [ { "name" : "Multimodal model training", "level" : "intermediate" }, { "name" : "Large-scale modeling", "level" : "intermediate" }, { "name" : "Data parallelisms", "level" : "intermediate" }, { "name" : "Model parallelisms", "level" : "intermediate" }, { "name" : "Context parallelisms", "level" : "intermediate" } ], "majorSkills" : "Foundation models, Deep learning, Multimodal models, Applied AI/ML", "majorSkillsList" : [ "Foundation models", "Deep learning", "Multimodal models", "Applied AI/ML" ], "coreResponsibilities" : "Design multimodal foundation models, Train multimodal foundation models, Optimize multimodal foundation models, Conduct applied research, Develop scalable training pipelines, Develop distributed training pipelines, Operationalize models for production, Ensure model robustness, Ensure model reproducibility, Ensure model observability, Translate model capabilities into features, Contribute to technical roadmap, Contribute to architectural direction, Ensure ethical AI standards, Ensure transparent AI standards, Ensure privacy-preserving AI standards", "teamCollaboration" : "Collaborate with data scientists; Collaborate with ML engineers; Collaborate with MLOps; Collaborate with data engineering; Collaborate with software engineering; Collaborate with product teams; Collaborate with research teams; Cross-functional partners", "domainKnowledge" : "Human physiology; Human behavior; Wearable sensors; Biomarkers; Clinical information", "domainList" : [ "human-physiology", "human-behavior", "wearable-sensors", "biomarkers", "clinical-information" ], "domainSpecificKnowledge" : [ "Human physiology", "Human behavior", "Wearable sensors", "Biomarkers", "Clinical information" ], "communicationSkills" : "Cross-functional communication", "specialRequirements" : "Prepared to relocate", "outcomesObjectives" : "Deliver measurable value; Deliver meaningful member value", "qualificationsBasic" : "Master's degree or equivalent experience, 7+ years applied ML/AI research, Expertise modern deep learning, Expertise multimodal model training, Proficiency in Python, Proficiency in deep learning frameworks, Familiarity mulit-node distributed compute, Familiarity multi-gpu distributed compute, Applied experience representation learning, Applied experience self-supervised methods, Applied experience post-training foundation models, Excellent communication skills, Ability to collaborate cross-functionally", "qualificationsPreferred" : "Ph. D. in related field, Experience reinforcement learning, Familiarity MLOps best practices, Passion for WHOOP's mission", "workSiteFlexibility" : "Onsite", "rawDescription" : "WHOOP is an advanced health and fitness wearable on a mission to unlock human performance and extend healthspan. By providing members with a deep understanding of their bodies, behaviors, and daily lives, WHOOP empowers healthier choices and peak performance. We are seeking a Senior AI Researcher to join our Foundation AI team. This team builds the multimodal foundation models that underpin WHOOP’s next generation of intelligent, personalized, and health-enhancing experiences. These models integrate data across wearable sensors, language, biomarkers, clinical information, and self-reported inputs to create scalable AI systems that understand human physiology and behavior. In this role, you’ll serve as a senior individual contributor driving the research, development, and deployment of large-scale multimodal models. You’ll collaborate closely with data scientists, ML engineers, and cross-functional partners to push the boundaries of deep learning and ensure our models deliver measurable value to WHOOP members. RESPONSIBILITIES: - - Design, train, and optimize large-scale multimodal foundation models that integrate wearable sensor data, text, biomarkers, and behavioral data. - Conduct applied research in self-supervised learning, representation learning, and downstream task fine tuning to advance WHOOP’s core model capabilities. - Develop scalable, distributed training pipelines for large models on high-performance compute environments. - Collaborate with MLOps, data engineering, and software engineering teams to operationalize models for production deployment, ensuring robustness, reproducibility, and observability. - Partner with product and research teams to translate foundation model capabilities into downstream features that deliver meaningful member value. - Contribute to the technical roadmap and architectural direction for foundation model development at WHOOP. - Ensure models adhere to WHOOP’s standards for ethical, transparent, and privacy-preserving AI. QUALIFICATIONS: - - Advanced degree (Master’s or Ph.D.) in Computer Science, Machine Learning, Electrical Engineering, or a related field, or equivalent professional experience. - 7+ years of experience in applied ML, AI research, or large-scale modeling, with a track record of delivering production systems. - Expertise in modern deep learning (e.g., transformers, state space models), multimodal model training. - Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow). - Familiarity with training models on mulit-node, multi-gpu distributed compute environments. - Familiarity with best practices for data, model, and context parallelisms. - Strong applied experience with representation learning, self-supervised methods, and post-training for downstream applications. - Experience with reinforcement learning for post-training foundation models (PPO, DPO, GRPO etc.). - Familiarity with MLOps best practices including model versioning, evaluation, CI/CD for ML, and cloud-based compute. - Excellent communication skills and ability to collaborate cross-functionally with engineers, researchers, and product teams. - Passion for WHOOP’s mission to improve human performance and extend healthspan through science and technology. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $190,000 - $230,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.", "summaryDescription" : "Senior AI/ML Researcher (Foundation AI) at WHOOP. Skills: Foundation models, Deep learning, Multimodal models, Applied AI/ML. Design multimodal foundation models. Train multimodal foundation models", "createdAt" : "2026-06-14T09:36:47.891", "lastUpdated" : "2026-06-15T10:23:49.495", "ingestTimestamp" : "2026-06-14T09:36:47.891", "mongoId" : "6a2c8c8374d8ee00a0975b4b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 190000, "salaryAnnualMax" : 230000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Multimodal model training", "Large-scale modeling", "Data parallelisms", "Model parallelisms", "Context parallelisms", "Foundation models", "Deep learning", "Multimodal models", "Applied AI/ML", "Model optimization", "Applied research", "Scalable training", "Distributed training", "Production deployment", "Technical roadmap", "Architectural direction", "Human physiology", "Human behavior", "Wearable sensors", "Biomarkers", "Clinical information" ], "skillCount" : 21, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 1086.968, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a307648f292fd229c017e07", "title" : "AI First Developer", "company" : "Smartcat", "industry" : "Technology", "salary" : { "min" : 7000000.0, "max" : 1.2E7, "currency" : "AMD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level AI First Developer in Armenia, adjusted for the technology industry and remote work." }, "location" : "Armenia - Remote", "locations" : [ "Armenia - Remote", "Costa Rica - Remote", "Georgia - Remote", "Portugal - Remote", "Serbia - Remote" ], "timestamp" : "2026-06-16T11:50:41.684", "fingerprint" : "ffd5a96f070e29b9bcc6a9a8677084fa71b587614ef7962478974572d31377ba", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://www.smartcat.com/career/?gh_jid=6000302004", "externalId" : "6000302004", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Armenia", "continent" : "as", "workMode" : "remote" } ], "locationText" : "Armenia", "employmentType" : "FULL_TIME", "technicalSkills" : "AWS, NET, Python, MongoDB, Generative AI, GPT APIs, LLMs", "professionalSkills" : [ "Delivery", "Ownership", "Execution" ], "hardSkillsList" : [ "AI-driven approach", "AI workflows" ], "hardSkills" : [ { "name" : "AI-driven approach", "level" : "intermediate" }, { "name" : "AI workflows", "level" : "intermediate" } ], "majorSkills" : "AI-First Engineering, Software Development, DevOps, Cloud", "majorSkillsList" : [ "AI-First Engineering", "Software Development", "DevOps", "Cloud" ], "coreResponsibilities" : "Deliver production-quality features, Apply AI across development lifecycle, Establish new engineering benchmark, Understand AWS tech stack, .NET tech stack understanding, Python tech stack understanding, MongoDB tech stack understanding, Ship real features using AI, Contribute to improving workflows, Own full lifecycle of feature delivery, Identify improvements in velocity, Identify improvements in automation, Identify improvements in team efficiency, Partner with Product Leads, Partner with Tech Leads, Accelerate time-to-market, Deliver features faster, Deliver features with higher quality, Mentor others on using AI, Drive AI-First engineering standard", "teamCollaboration" : "Cross-functional teams; Product and Tech Leads", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "Agentic AI; Enterprise Skill Graph; Hybrid workforces; AI agents; Multilingual content", "domainList" : [ "agentic-ai", "enterprise-skill-graph", "hybrid-workforces", "ai-agents", "multilingual-content" ], "domainSpecificKnowledge" : [ "Agentic AI", "Enterprise Skill Graph", "Hybrid workforces", "AI agents", "Multilingual content" ], "toolProficiency" : [ "Copilot", "Cursor", "WindSurf", "GPT APIs", "LLMs" ], "documentationSkills" : "Documentation", "innovationCreativity" : "AI innovation", "problemSolvingSkills" : "Root cause analysis", "outcomesObjectives" : "Deliver high-quality features faster; Build and optimize AI-first workflows; Raise the bar for speed; Raise the bar for quality; Raise the bar for ownership; Be a core contributor", "qualificationsBasic" : "Mastery in using AI tools, Technical foundation in AWS, NET technical foundation, Python technical foundation, MongoDB technical foundation, Obsessed with delivery", "qualificationsPreferred" : "Experience with Copilot, Experience with Cursor, Experience with WindSurf, Experience with GPT APIs, Experience with LLMs", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About Smartcat Smartcat is building the future of work, where human expertise meets digital teammates to drive 10x to 1000x productivity gains for the world’s leading enterprises. We’re on the frontier of an entirely new category: Agentic AI. We enable enterprises to build high-performing hybrid workforces made up of both humans and AI agents. These AI agents aren’t generic copilots. They’re fully trained digital teammates that learn from your best people, your content, and your business strategy—ready to get to work from day one. Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. Whether you're launching a product globally, onboarding new hires, translating learning content, or aligning legal teams across regions, Smartcat turns knowledge into action and action into scale. Over 1,000 companies, including 20% of the Fortune 500, rely on Smartcat to bring their business to the world—instantly, accurately, and in every language. As a Series C company with consistently high year-over-year growth, we’re scaling fast and investing in people who want to shape the future of work with us. Join us in unlocking global potential, one human and agent team at a time. WHY YOU SHOULD JOIN OUR TEAM We are building the future of software development — AI-First is the new standard. You won’t be “experimenting”; you’ll be delivering. Fast. Smart. Relentless. Join the core team that will prove AI-driven engineering is the only way forward. If you love challenges, own your outcomes, and are obsessed with delivery, you’ll thrive here. MISSION As an AI-First Engineer, your mission is to deliver production-quality features at a speed and scale that traditional teams cannot match. You will apply AI aggressively across every stage of the development lifecycle — from requirements and design to coding, testing, and release — and establish a new engineering benchmark for the company. OUTCOMES Consistently deliver high-quality, production-grade features faster than traditional teams. Build and optimize AI-first workflows that integrate AI across all development stages. Raise the bar for speed, quality, and ownership in product delivery. Be a core contributor to the new engineering culture built on AI-First principles. HOW YOU’LL RAMP By Day 30: Deeply understand our AWS, .NET, Python, MongoDB tech stack and delivery model. Start shipping real features using AI at every stage: coding, testing, documenting, releasing. Contribute to improving workflows for even faster delivery. By Day 60: Independently own the full lifecycle of feature delivery through AI-first methods. Identify and drive improvements in velocity, automation, and team efficiency. Partner with Product and Tech Leads to aggressively accelerate time-to-market. By Day 90: Deliver features faster and with higher quality than baseline teams. Actively mentor others on using AI as a multiplier across development. Become a key driver of the AI-First engineering standard inside the company. WHAT YOU’VE ACCOMPLISHED: Proven track record of delivering production-grade products using AI-driven approach. Mastery in using AI tools (Copilot/Cursor/WindSurf (etc, you choose), GPT APIs, LLMs) across the entire development lifecycle — design, code generation, testing, documentation, and release. Strong technical foundation in AWS, .NET, Python, and MongoDB. Obsessed with delivery: you ship, you improve, you own the outcome. Comfortable moving fast, taking ownership, and constantly pushing for better, faster, smarter execution. Why joining Smartcat might be your best move so far A global, connected team We’re a team of 200+ people across 30+ countries, working together through a hub-and-spoke model anchored in eight key locations: New York, London, Lisbon, Costa Rica, Serbia, Armenia, Georgia, and Spain. Most of our roles are remote-friendly, giving you the flexibility to do your best work from where you thrive. For customer-facing teams, we prioritize proximity to our customers, ensuring we stay deeply connected to their needs and deliver an exceptional experience. No matter where you’re based, you’ll be part of a highly collaborative, globally-distributed team that values ownership, speed, and meaningful impact. Be part of an AI Native Organization We are highly innovative, using AI across all areas of the organization to accelerate decision-making and free people to focus on strategy and high-impact work. We embrace new ideas and encourage all Smartcaters, regardless of level or department, to manage their own AI Agents. At Smartcat you’ll shape how AI transforms the workplace and play an integral role in ensuring Smartcat remains a leader in AI innovation. Innovating a $100 Billion industry Smartcat is reshaping the $100B multilingual content industry with an AI-powered platform that makes it easy for companies to create, translate, and localize global content at scale. Our platform enables enterprise teams to move away from slow, traditional outsourcing methods, and achieve fast, high-quality results, at a fraction of the cost. Join the rocketship to scale-up 10x and beyond together We are looking for someone to become an integral part of our team and play a crucial role in the most exciting part of our journey: transitioning from a post-Series C startup to a company exceeding $100M in ARR and $1B in valuation. Our journey isn’t for the faint of heart. We are growing at 130% YoY, thanks to our strong product-market fit and high-performing team, and plan to accelerate from here. Smartcat Culture Code: Where Diversity Meets High Performance At Smartcat, we are committed to building a culture that highlights respect and appreciation for each individual's unique background and perspective, while maintaining a strong focus on results and engagement. We believe in welcoming everyone and fostering an inclusive environment where team members can be their authentic selves at work. Our commitment to inclusion is steadfast, and we stand firmly against discrimination and harassment.", "summaryDescription" : "AI First Developer at Smartcat. Skills: AI-First Engineering, Software Development, DevOps, Cloud. Deliver production-quality features. 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This ideal candidate will leverage tools such as GitHub Copilot and Claude (Claude Code) to accelerate development, build intelligent applications, automate workflows, and create AI agents candidate will design, develop, and deploy AI-driven applications and services, integrating machine learning models into scalable enterprise solutions. Key Responsibilities * Design, develop, and deploy AI-powered applications using LLMs such as Claude, GPT, and other foundation models. * Utilize GitHub Copilot / Claude Code to accelerate software development, testing, debugging, and documentation. * Build AI agents, copilots, and workflow automation solutions. * Design and develop AI/ML-based solutions using modern frameworks and tools * Build and maintain backend services using .NET (C#, ASP.NET Core) * Deploy, manage, and optimize applications on Microsoft Azure * Integrate AI models into production systems and APIs * Work with structured data stored in Oracle DB, including performance tuning and query optimization * Collaborate with data scientists, product managers, and cross-functional teams * Implement data pipelines and workflows for AI model training and inference * Ensure scalability, reliability, and security of AI applications * Monitor model performance and continuously improve solutions Required Skills & Qualifications * Hands-on experience with Claude API, OpenAI API, or equivalent AI platforms. * Hands-on experience with Microsoft Azure services (Azure ML, App Services, Functions, Storage, etc.) * Strong experience in .NET / C# / ASP.NET Core * Solid experience with Oracle Database (PL/SQL, query optimization, schema design) * Knowledge of AI/ML concepts and frameworks (e.g., Python, TensorFlow, PyTorch, or ML.NET) * Experience in building and consuming REST APIs * Familiarity with microservices architecture * Understanding of DevOps practices and CI/CD pipelines * Good problem-solving and analytical skills ## Additional Information All your information will be kept confidential according to EEO guidelines.", "summaryDescription" : ". 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Preferred Qualifications: BSc in Computer Science, Software Engineering or equivalent MSc in Computer Science, Data Science, AI or equivalent Required Skills: Solid software engineering fundamentals (OOP, Git, concurrency, parallelism) Proficiency in Python Understanding of LLM system design (RAG, agents, etc.) Knowledge of ML system design (pipelines, training/inference techniques) Excellent English communication skills Nice to Have: Experience in non-academic projects (jobs, internships or similar) Previous LLM projects (academic or otherwise) Exposure to AI features in cloud platforms (Sagemaker, Bedrock, Vertex AI) Experience working in large codebases Why TensorOps? Fully remote (legal residence in Portugal required) Real-world projects, rapid feedback loops, and measurable impact Mentorship from engineers who have shipped ML systems at scale Competitive compensation and growth opportunities - your growth will be based on ownership and performance rather than periodic reviews (which we still do) Compensation & Perks: Yearly salary: €30,000-35,000 Travel expenses allowance Urban Sports Club membership Free Professional Certifications", "summaryDescription" : "Junior AI/ML Engineer at TensorOps. Skills: Machine Learning, AI, MLOps, Generative AI. Build AI products. 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"Entry", "domainKnowledge" : "AI/ML/LLM concepts; Prompting; Embeddings; Retrieval; Cloud platforms; DevOps practices", "domainList" : [ "ai-ml-llm-concepts", "prompting", "embeddings", "retrieval", "cloud-platforms", "devops-practices" ], "domainSpecificKnowledge" : [ "AI/ML/LLM concepts", "Prompting", "Embeddings", "Retrieval", "Cloud platforms", "DevOps practices" ], "problemSolvingSkills" : "Troubleshoot issues", "specialRequirements" : "Eligible to work in U.S", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Who We Are: Atlas Energy Solutions Inc. (NYSE: AESI) is a leading solutions provider to the energy industry. Atlas’ portfolio of offerings includes oilfield logistics, distributed power systems, and the largest proppant supply network in the Permian Basin. With a focus on leveraging technology, automation, and remote operations to enhance efficiencies, Atlas is centered around a core mission of improving human beings’ access to hydrocarbons that power our lives and, by doing so, maximizing value creation for our shareholders. How You Will Make an Impact: The AI Developer is a technical, entry-level role within the Atlas Technology team that builds and maintains AI solutions across the business. Responsibilities AI-powered features and applications such as conversational interfaces, workflow automations, MCP servers, and computer vision. Connect AI solutions with Atlas internal systems, Microsoft Graph, Azure services, third-party APIs, and operational data sources. Implement testing strategies for AI behavior including prompt evaluation, regression testing, output validation, and model performance. Apply authentication patterns, data protection controls, and audit logging. Ensure responsible and compliant AI usage by reinforcing approved tools, data handling, and governance guardrails; coordinate privacy/security reviews and escalate risks and exceptions as needed. Monitor deployed solutions for performance, reliability, and cost. Respond to incidents, troubleshoot issues, and drive continuous improvement through analytics and user feedback. Minimum qualifications Bachelor’s degree (in disciplines relevant to business process improvement or technology adoption) or equivalent practical experience/training. Programming: Foundational proficiency in one general purpose programming language (e. g. Python or C#) and one front end framework (e. g. React/JavaScript) Comfort with REST APIs, JSON, DBs and basic data structures Foundations: Understanding of AI/ML/LLM concepts (prompting, embeddings, retrieval) through coursework, personal projects, or internship AI/ML/LLM concepts or project experience Eligible to work in the U. S. without future sponsorship. Demonstrated experience through relevant personal projects with publicly shareable artifacts (e.g., GitHub repositories, demos, technical write-ups, or case studies). Preferred qualifications Experience building LLM-powered applications and automations Exposure to cloud platforms and DevOps practices (Azure Functions, CI/CD pipelines, Git/GitHub, containers). Familiarity with Microsoft tools such as Power Platform, Copilot Studio, Microsoft Foundry, Graph APIs and collaboration platforms (e.g., Teams and SharePoint) Completion of relevant AI-focused certifications and/or accredited boot camps. What You Will Love About Us Best People and Team. Great Place to Work , Hire Vets, Top Place to Work For – Austin American Statesman Your Well-Being is a Priority. 100% covered Medical, Dental, and Vision Invest in Your Future. 401K with company match, immediate vesting Relax and Recharge. Paid time off (non-rotational roles), 15+ company paid holidays Equal Opportunity Employer Statement: Atlas Energy Solutions is an equal opportunity employer and is committed to providing equal employment opportunity to all applicants and employees. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, pregnancy, gender identity or expression, sexual orientation, genetic information, citizenship status, veteran or military status, or any other characteristic protected by applicable federal, state, or local law. This commitment applies to all aspects of employment, including recruiting, hiring, training, promotion, compensation, benefits, and termination. Reasonable Accommodation Atlas Energy Solutions provides reasonable accommodations to qualified individuals with disabilities and those with pregnancy-related conditions in accordance with applicable law. 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Cross-functional teams", "projectManagementSkills" : [ "Lead projects" ], "domainKnowledge" : "AI benchmarking; AI capabilities; AI strategies; Emerging modalities; Emerging capabilities", "domainList" : [ "ai-benchmarking", "ai-capabilities", "ai-strategies", "emerging-modalities", "emerging-capabilities" ], "domainSpecificKnowledge" : [ "AI benchmarking", "AI capabilities", "AI strategies", "Emerging modalities", "Emerging capabilities" ], "toolProficiency" : [ "Pandas", "OpenAI" ], "communicationSkills" : "Presenting data; Actionable insights", "innovationCreativity" : "AI-native workflow; Cutting-edge AI tools", "problemSolvingSkills" : "Problem-solving skills; Distill complex concepts", "qualificationsBasic" : "3+ years software engineering, Proficiency Python libraries, Proficiency AI APIs, Familiarity cloud infrastructure, Familiarity orchestration tools, Familiarity monitoring tools, Experience visualizing data, Experience presenting data, Problem-solving skills, Distill complex concepts, Excellent communication skills, Excellent collaboration skills, Lead projects independently, Bachelor's or Master's", "qualificationsPreferred" : "Experience AI/ML frameworks, Experience PyTorch", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "ABOUT ARTIFICIAL ANALYSIS Artificial Analysis is the leading independent AI benchmarking company. We support labs, engineers and enterprises to understand AI capabilities and make critical decisions about their AI strategies. We are the go-to authority for understanding AI, from AI labs and enterprises to media, investors, and policymakers. Our benchmarks don't just measure the cutting edge of AI, they are actively shaping the frontier. Our benchmarks and analysis are trusted by hundreds of thousands of users and are the go-to reference for leading AI labs including OpenAI, Google, Meta, NVIDIA and Anthropic, and major publications including the Wall Street Journal, Bloomberg, the Financial Times and The Economist. We are a team of 35+, on track to triple by year end, backed by Nat Friedman (Github, Meta), Daniel Gross (SSI), Andrew Ng (Google Brain, DeepLearning.ai http://DeepLearning.ai, Amazon), Adam D'Angelo (Quora, Poe, OpenAI), Clem Delangue (Hugging Face) and other industry leaders. THE OPPORTUNITY We're looking for an Intermediate to Senior ML Engineer to join our team and lead projects in AI benchmarking and analysis. You'll work closely with our founders to build core parts of the software stack for our early stage start-up. The coming wave of AI scaling is going to change the world in ways we don't yet understand — and we're offering a front row seat. WHAT YOU’LL DO - Lead the development and optimization of aspects of our core benchmarking stack, focusing on data intensive backend systems and APIs, and driving projects from concept to shipped - Design and implement robust Python solutions for benchmarking, model evaluation and data analysis - Design and implement user interfaces and data visualizations that distill complex AI benchmarking data into intuitive, interactive experiences for thousands of daily users - Conduct custom analyses for enterprise customers, providing actionable insights to inform their AI strategies - Contribute to the evolution of our benchmarking methodologies, including development of evaluation methodology for emerging modalities and capabilities - Embrace an AI-native workflow, using cutting-edge AI tools to generate leverage in a fast-changing industry WHAT WE’RE LOOKING FOR - 3+ years of professional software engineering experience - Passion for AI and eagerness to work at the forefront of technological innovation - Proficiency with relevant Python libraries for data analysis (e.g. pandas) and key AI APIs (e.g. OpenAI) - Familiarity with cloud infrastructure, orchestration and monitoring tools - Experience with visualizing & presenting data - Strong problem-solving skills and ability to distill complex concepts into actionable insights in the face of uncertainty - Excellent communication and collaboration skills - Proven ability to lead projects independently in a fast-paced environment - Bachelor's or Master's in Computer Science, Engineering, or related field (e.g. Physics) Preferred but not essential: - Experience with AI/ML frameworks (e.g. PyTorch) - Creation of analytical reports WHY ARTIFICIAL ANALYSIS? - Shape how AI gets built: The leading AI labs track our benchmarks and use them to guide their development priorities. Your work will directly influence the direction of AI. - Become a world expert in AI: You will evaluate every major model, across every major capability, as they are released. Very few roles offer this breadth of exposure to frontier AI. - Work with the most important players in AI: You'll manage relationships with teams at the leading AI labs and major enterprises as a trusted, independent voice. - Join at a defining moment: We're 35+ people and fast growing, backed by some of the most connected investors in AI. The people who join now will shape the product, the team, and the strategy as we scale. - Competitive compensation including equity - Our team is split across San Francisco, Sydney, and Melbourne ", "summaryDescription" : "Senior AI / ML Engineer at Artificial Analysis. Skills: AI benchmarking, ML engineering, Data analysis, Backend systems. Lead development benchmarking stack. Optimize benchmarking stack", "createdAt" : "2026-06-14T04:13:21.048", "lastUpdated" : "2026-06-15T12:06:06.609", "ingestTimestamp" : "2026-06-14T04:13:21.048", "mongoId" : "6a2cafbd74d8ee00a09d7aaf", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "Backend systems", "APIs", "Python solutions", "Data intensive systems", "AI benchmarking", "Model evaluation", "Data analysis", "User interface design", "Data visualization", "Enterprise analysis", "Evaluation methodology", "Leadership", "ML engineering", "Benchmarking", "Enterprise customer analysis", "AI strategy", "Emerging modalities", "Emerging capabilities", "Lead projects", "AI capabilities", "AI strategies", "Pandas", "OpenAI" ], "skillCount" : 23, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 1043.6637, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca16774d8ee00a09a5619", "title" : "Staff Engineer AI/ML", "company" : "AnswersNow", "industry" : "Engineering", "salary" : { "min" : 150000.0, "max" : 215000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "Remote", "locations" : [ "Remote" ], "timestamp" : "2026-06-15T09:44:02.890", "fingerprint" : "451418a8e15fb2df1c649d3574479a929046fd566056c753cc1fd3b871df9568", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/answersnow/77f6d0e2-adb8-47b8-98bd-d0bd2c5d23a2/application", "externalId" : "77f6d0e2-adb8-47b8-98bd-d0bd2c5d23a2", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "JavaScript, TypeScript, React, Node.js, Express, Postgres, AWS, ECS, RDS, S3, Lambda, ETL, AI, LLM, Event-driven architectures, Message queues, Streaming pipelines", "professionalSkills" : [ "Technical leadership", "System design", "Architecture design", "Technical mentorship", "Performance analysis", "Reliability analysis", "Maintainability analysis", "Technical strategy", "Production support", "Incident response", "Root cause analysis" ], "hardSkillsList" : [ "Full-stack development", "Data pipeline architecture", "ML/AI system architecture", "Model lifecycle management" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Full-stack development", "level" : "intermediate" }, { "name" : "Data pipeline architecture", "level" : "intermediate" }, { "name" : "ML/AI system architecture", "level" : "intermediate" }, { "name" : "Model lifecycle management", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "AI/ML, Distributed systems, Data pipelines, Full-stack development", "majorSkillsList" : [ "AI/ML", "Distributed systems", "Data pipelines", "Full-stack development" ], "coreResponsibilities" : "Own and evolve platform architecture, Drive JavaScript to TypeScript migration, Establish migration patterns, tooling, standards, Design and extend ETL pipeline, Design config-driven AI integration framework, Enable engineers ship AI features, Lead technical design reviews, Create architecture decision records, Ensure engineering decisions documented, Identify and resolve technical debt, Define and execute technical strategy, Integrate ML/AI models, Ensure scalability, performance, reliability, Mentor engineers, Grow team capability, Establish engineering standards, Maintain code quality, Maintain testing practices, Maintain observability, Maintain on-call runbooks, Maintain incident response, Serve as technical resource, Partner with leadership to scope initiatives, Partner to sequence initiatives, Partner to de-risk initiatives, Lead by example production support, Define runbooks, Own post-mortems, Drive systemic fixes from incidents, Work across UI, API, DB, infrastructure", "teamCollaboration" : "Partner with CTO; Partner with product leadership; Partner with clinical stakeholders; Partner with engineering leadership; Cross-functional teams", "projectManagementSkills" : [ "Scoping", "Sequencing", "De-risking" ], "domainKnowledge" : "Autism therapy; Virtual ABA therapy; HIPAA compliance; PHI handling", "domainList" : [ "autism-therapy", "virtual-aba-therapy", "hipaa-compliance", "phi-handling" ], "domainSpecificKnowledge" : [ "Autism therapy", "Virtual ABA therapy", "HIPAA compliance", "PHI handling" ], "toolProficiency" : [ "Node.js/Express", "Postgres", "AWS ECS", "AWS RDS", "AWS S3", "AWS Lambda" ], "communicationSkills" : "Brief non-technical executives; Architecture documentation; Design reviews", "documentationSkills" : "Architecture decision records; On-call runbooks; Post-mortems", "innovationCreativity" : "AI-powered features", "problemSolvingSkills" : "Root cause analysis; Systemic fixes", "qualificationsBasic" : "8+ years software engineering, 3+ years senior/staff role, Deep expertise JavaScript/TypeScript, Command React, Node.js/Express, Postgres, Experience designing distributed systems, Experience owning data pipeline architectures, Track record technical mentorship, Excellent written and verbal communication, Experience growth-stage startup", "qualificationsPreferred" : "AWS ECS, RDS, S3, Lambda experience, Familiarity ETL pipelines, Familiarity AI/LLM integration patterns, Familiarity data-intensive systems, Experience healthcare regulated data, Familiarity event-driven architectures, Familiarity message queues, Familiarity streaming pipelines, Prior experience engineering manager, Contributions to open source, Engineering blog posts, Conference talks", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Staff Engineer AI/ML Remote, Anywhere in the US About AnswersNow At AnswersNow, we are trailblazing the future of autism therapy, making it more immediate, accessible, and effective for families everywhere. Our innovative virtual ABA therapy platform is thoughtfully designed by clinicians to recreate the focused, supportive environment of in-person therapy, complete with distraction-free features and interactive activities that enhance engagement and progress. Our team operates fully remote—meaning you’ll have the flexibility to work from the comfort of home. If you're ready to make a meaningful impact and join a team that's reshaping autism therapy, we’d love to hear from you! Why this role matters: We're looking for a Senior Engineering Manager who knows that great engineering leadership is about growing people, removing obstacles, and making the team better — not writing the most code. You've led teams before. You know how to hold a high bar for craft while keeping engineers energized and growing. You understand that a team of four highly effective engineers with strong habits will outperform a team of twelve with unclear expectations. You'll manage a team of Engineering Team Leads, each of whom runs a squad of full-stack engineers. You own the health of the engineering organization: hiring, performance, culture, delivery, and the processes that keep everything running. You partner closely with the CTO, product leadership, and clinical stakeholders to ensure engineering is building the right things, the right way. This is a player-coach role in spirit — you should be technically credible and able to engage meaningfully in architecture discussions — but your primary output is team output, not individual code. Job Details - W2 Employee - Full-Time - 100% Remote Job Requirements - 8+ years of professional software engineering experience, with at least 3 years in a senior or staff-level role - Deep expertise in JavaScript and TypeScript in a production full-stack environment - Strong command of React, Node.js/Express, and Postgres — you can reason about performance, reliability, and maintainability at each layer - Proven experience designing and owning distributed systems or data pipeline architectures on AWS (ECS, RDS, S3, Lambda experience valued) - Track record of technical mentorship — you've made engineers around you measurably better - Excellent written and verbal communication; you can write an architecture doc, run a design review, and brief a non-technical executive in the same day - Experience working in or leading engineering at a growth-stage startup — you understand the balance between velocity and sustainability - Familiarity with ETL pipelines, AI/LLM integration patterns, or data-intensive systems is a strong plus - Significant experience architecting and deploying production-grade ML/AI systems, including LLM integration and model lifecycle management. Nice to have: - Experience with healthcare or regulated data environments (HIPAA compliance, PHI handling) - Familiarity with event-driven architectures, message queues, or streaming pipelines - Prior experience as an engineering manager who returned to an IC track (player-coach background welcome) - Contributions to open source or engineering blog posts / conference talks What You’ll Do Technical Leadership - Own and evolve the architecture of our core platform: React frontend, Node.js/Express APIs, Postgres, and AWS ECS infrastructure - Drive our JavaScript → TypeScript migration, establishing patterns, tooling, and standards the team can follow - Design and extend our ETL pipeline and config-driven AI integration framework, enabling engineers to ship AI-powered features faster and more reliably - Lead technical design reviews, create architecture decision records (ADRs), and ensure engineering decisions are documented and defensible - Identify and resolve systemic technical debt — not just flagging it, but owning the plan to address it - Define and execute the technical strategy for integrating ML/AI models into our core platform, ensuring scalability, performance, and reliability. Engineering Culture & Mentorship - Mentor engineers across all levels — pair, review, coach, and grow the team's collective capability - Establish and maintain engineering standards: code quality, testing practices, observability, on-call runbooks, and incident response - Serve as a technical resource and thought partner for product, clinical, and business stakeholders - Help define the engineering hiring bar and participate in the interview process Delivery & Operations - Partner with engineering leadership and product to scope, sequence, and de-risk large technical initiatives - Lead by example on production support — define runbooks, own post-mortems, and drive systemic fixes from incidents - Work across UI, API, DB, and infrastructure layers with genuine depth in at least two What we Offer - $151,000- $178,500 annual salary - Fully remote – work from anywhere in the U.S. - Flexible hours with an async-friendly team culture More About AnswersNow AnswersNow welcomes applicants of all backgrounds, experiences, and abilities. We believe a diverse team is a strong team, and are committed to provide a fair and equitable experience for every candidate. If you require reasonable accommodations at any stage, we encourage you to reach out. We’re here to support! Learn more about us at getanswersnow.com http://getanswersnow.com.", "summaryDescription" : "Staff Engineer AI/ML at AnswersNow. Skills: AI/ML, Distributed systems, Data pipelines, Full-stack development. Own and evolve platform architecture. Drive JavaScript to TypeScript migration", "createdAt" : "2026-06-14T04:08:11.930", "lastUpdated" : "2026-06-15T09:44:02.890", "ingestTimestamp" : "2026-06-14T04:08:11.930", "mongoId" : "6a2ca16774d8ee00a09a5619", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 150000, "salaryAnnualMax" : 215000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Full-stack development", "Data pipeline architecture", "ML/AI system architecture", "Model lifecycle management", "Leadership", "Mentoring", "AI/ML", "Distributed systems", "Data pipelines", "Technical leadership", "System design", "Architecture design", "Technical mentorship", "Performance analysis", "Reliability analysis", "Maintainability analysis", "Technical strategy", "Production support", "Incident response", "Root cause analysis", "Scoping", "Sequencing", "De-risking", "Autism therapy", "Virtual ABA therapy", "HIPAA compliance", "PHI handling", "Node.js/Express", "Postgres", "AWS ECS", "AWS RDS", "AWS S3", "AWS Lambda" ], "skillCount" : 33, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "_score" : 1040.1404, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.95 }, { "id" : "6a307f6cf292fd229c05913c", "title" : "Customer Engineer, AI/ML, Startups, Google Cloud", "company" : "Google", "industry" : "Technology", "salary" : { "min" : 165000.0, "max" : 250000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Customer Engineer in Austin, TX, adjusted for Google's size and the Technology industry." }, "location" : "[Austin, TX, USA, [500 W 2nd St, Austin, TX 78701, USA], Austin, 78701, TX, US]", "locations" : [ "[Austin, TX, USA, [500 W 2nd St, Austin, TX 78701, USA], Austin, 78701, TX, US]" ], "timestamp" : "2026-06-16T13:22:28.417", "fingerprint" : "7abe34f71731e3872ca3b831cf69b74042f8f053d2e24b92933c5adbbfbefad4", "source" : "google", "language" : "en", "externalId" : "98617023310766790", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Austin", "state" : "Texas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "30.2711286,-97.7436995" } ], "locationText" : "Austin, Texas, United States", "technicalSkills" : "AI, ML, Google Cloud", "majorSkills" : "AI, ML", "majorSkillsList" : [ "AI", "ML" ], "domainKnowledge" : "Startups", "domainList" : [ "startups" ], "domainSpecificKnowledge" : [ "Startups" ], "summaryDescription" : "Customer Engineer, AI/ML, Startups, Google Cloud at Google. Skills: AI, ML", "postedDate" : "2026-06-16T01:49:21.646", "createdAt" : "2026-06-16T01:49:21.646", "lastUpdated" : "2026-06-16T13:22:28.417", "ingestTimestamp" : "2026-06-16T01:49:21.646", "mongoId" : "6a307f6cf292fd229c05913c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 165000, "salaryAnnualMax" : 250000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "AI", "ML", "Startups" ], "skillCount" : 3, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "_score" : 1031.0928, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305581f292fd229cf1fc6a", "title" : ". NET Developer", "company" : "GlobeMed Group", "industry" : "Insurance", "salary" : { "min" : 2.4E7, "max" : 4.2E7, "currency" : "LBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior .NET Developer in Beirut, Lebanon, adjusted for the healthcare industry and company size." }, "location" : "Beirut, LB", "locations" : [ "Beirut", "LB" ], "timestamp" : "2026-06-16T06:57:54.942", "fingerprint" : "e189dd264943291e75e10001683c1fa19fcd01d8a24df3ead1419bb729c2d1d7", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/GlobeMedGroup/744000132162479--net-developer", "externalId" : "744000132162479", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Beirut", "country" : "Lebanon", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "33.8892265,35.5025585" } ], "locationText" : "Beirut, Lebanon", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor Degree", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "mid", "coreResponsibilities" : "Understand functional requirements, Create technical documentation, Produce clean code, Upgrade existing software, Troubleshoot software, Debug software", "documentationSkills" : "Technical documentation", "problemSolvingSkills" : "Troubleshoot; Debug", "qualificationsBasic" : "1-5 years’ experience in software development, Ability to work under deadlines, Maintain a professional attitude, Ability to learn new languages and technologies", "qualificationsPreferred" : "Flexible and willing to accept a change in priorities, Attention to details, Fluent in English and Arabic, Organized and well structured", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "GlobeMed Group, the largest Healthcare Benefits Management company in the MENA region is looking for a .NET Developer to to use programming languages and source code to create software that meets the requirements. Duties & Responsibilities: * Work closely with the team leader or other more senior teammates to understand the functional requirements for the code that he/she will develop * Create technical documentation * Produce clean, efficient code based on technical specifications and development standards * Troubleshoot, debug and upgrade existing software * Participate in testing process through unit testing * Recommend improvements ## Qualifications Education: Bachelor Degree in Computer Science or related fields Experience/Knowledge: * 1-5 years’ experience in software development * Ability to work under deadlines and maintain a professional attitude * Ability to learn new languages and technologies Technical Skills/Competencies: * Flexible and willing to accept a change in priorities as necessary * Strong attention to details * Fluent in English and Arabic * Organized and well structured", "summaryDescription" : ". NET Developer at GlobeMed Group. Understand functional requirements. Create technical documentation", "postedDate" : "2026-06-15T10:08:17.000", "createdAt" : "2026-06-15T23:42:28.894", "lastUpdated" : "2026-06-16T06:57:54.942", "ingestTimestamp" : "2026-06-15T23:42:28.894", "mongoId" : "6a305581f292fd229cf1fc6a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Junior", "dataQualityScore" : 0.8888889, "_score" : 1029.0067, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c8c8274d8ee00a0975af7", "title" : "Staff AI/ML Researcher (Foundation AI)", "company" : "WHOOP", "industry" : "Foundation AI", "salary" : { "min" : 215000.0, "max" : 260000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, MA", "locations" : [ "Boston, MA" ], "timestamp" : "2026-06-15T08:17:47.758", "fingerprint" : "bed06dd2a5ae0063a3bdee6a36e166193d09fd165d7966a8576fee851e68916b", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/whoop/b9aa2724-75eb-4180-9cd3-aa0f3af43e76/application", "externalId" : "b9aa2724-75eb-4180-9cd3-aa0f3af43e76", "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" : "Master's", "experienceMinYears" : 7, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, Deep learning, Transformers, State space models, Multimodal model training, Self-supervised learning, Representation learning, Reinforcement learning, PPO, DPO, GRPO", "professionalSkills" : [ "Model optimization", "Technical roadmap", "Architectural direction" ], "hardSkillsList" : [ "Large-scale modeling", "Multimodal data integration", "Distributed training", "Model versioning", "Model evaluation", "CI/CD for ML" ], "softSkillsList" : [ "Mentoring" ], "hardSkills" : [ { "name" : "Large-scale modeling", "level" : "intermediate" }, { "name" : "Multimodal data integration", "level" : "intermediate" }, { "name" : "Distributed training", "level" : "intermediate" }, { "name" : "Model versioning", "level" : "intermediate" }, { "name" : "Model evaluation", "level" : "intermediate" }, { "name" : "CI/CD for ML", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "Foundation models, Deep learning, Multimodal models", "majorSkillsList" : [ "Foundation models", "Deep learning", "Multimodal models" ], "coreResponsibilities" : "Design foundation models, Train foundation models, Optimize foundation models, Conduct applied research, Develop training pipelines, Operationalize models for production, Partner with product teams, Contribute to technical roadmap, Serve as technical mentor, Ensure ethical AI standards", "teamCollaboration" : "Cross-functional partners; Data scientists; ML engineers; Product teams; MLOps teams; Data engineering teams; Software engineering teams", "domainKnowledge" : "Human physiology; Human behavior", "domainList" : [ "human-physiology", "human-behavior" ], "domainSpecificKnowledge" : [ "Human physiology", "Human behavior" ], "toolProficiency" : [ "PyTorch", "TensorFlow" ], "communicationSkills" : "Cross-functional collaboration", "outcomesObjectives" : "Deliver measurable value", "qualificationsBasic" : "Advanced degree in Computer Science, 7+ years applied ML experience, Expertise in modern deep learning, Proficiency in Python, Proficiency in deep learning frameworks, Experience scaling large datasets, Experience training large models, Experience with distributed compute environments, Excellent communication skills", "qualificationsPreferred" : "Ph. D. in Computer Science, Experience with reinforcement learning, Familiarity with MLOps best practices, Familiarity with data parallelisms, Familiarity with model parallelisms, Familiarity with context parallelisms, Familiarity with self-supervised learning, Familiarity with representation learning, Familiarity with downstream task fine tuning", "workSiteFlexibility" : "Onsite", "rawDescription" : "WHOOP is an advanced health and fitness wearable on a mission to unlock human performance and extend healthspan. By providing members with a deep understanding of their bodies, behaviors, and daily lives, WHOOP empowers healthier choices and peak performance. We are seeking a Staff AI/ML Researcher to join our Foundation AI team. This team builds the multimodal foundation models that underpin WHOOP’s next generation of intelligent, personalized, and health-enhancing experiences. These models integrate data across wearable sensors, language, biomarkers, clinical information, and self-reported inputs to create scalable AI systems that understand human physiology and behavior. In this role, you’ll serve as a staff individual contributor driving the research, development, and deployment of large-scale multimodal models. You’ll collaborate closely with data scientists, ML engineers, and cross-functional partners to push the boundaries of deep learning and ensure our models deliver measurable value to WHOOP members. RESPONSIBILITIES: - - Design, train, and optimize large-scale multimodal foundation models that integrate wearable sensor data, text, biomarkers, and behavioral data. - Conduct applied research in self-supervised learning, representation learning, and downstream task fine tuning to advance WHOOP’s core model capabilities. - Develop scalable, distributed training pipelines for large models on high-performance compute environments. - Collaborate with MLOps, data engineering, and software engineering teams to operationalize models for production deployment, ensuring robustness, reproducibility, and observability. - Partner with product and research teams to translate foundation model capabilities into downstream features that deliver meaningful member value. - Contribute to the technical roadmap and architectural direction for foundation model development at WHOOP. - Serve as a technical mentor for other data scientists, sharing best practices in deep learning, large-scale training, and multimodal data integration. - Ensure models adhere to WHOOP’s standards for ethical, transparent, and privacy-preserving AI. QUALIFICATIONS: - - Advanced degree (Master’s or Ph.D.) in Computer Science, Machine Learning, Electrical Engineering, or a related field, or equivalent professional experience. - 7+ years of experience in applied ML, AI research, or large-scale modeling, with a track record of delivering production systems. - Expertise in modern deep learning (e.g., transformers, state space models), multimodal model training. - Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow). - Experience building and scaling large datasets and training large models in mulit-node, multi-gpu distributed compute environments. - Familiarity with best practices for data, model, and context parallelisms. - Strong applied experience with representation learning, self-supervised methods, and post-training for downstream applications. - Experience with reinforcement learning for post-training foundation models (PPO, DPO, GRPO etc.). - Familiarity with MLOps best practices including model versioning, evaluation, CI/CD for ML, and cloud-based compute. - Excellent communication skills and ability to collaborate cross-functionally with engineers, researchers, and product teams. - Passion for WHOOP’s mission to improve human performance and extend healthspan through science and technology. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $215,000 - $260,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.", "summaryDescription" : "Staff AI/ML Researcher (Foundation AI) at WHOOP. Skills: Foundation models, Deep learning, Multimodal models. Design foundation models. 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ENVIRONMENT The project operates within a European financial institution, necessitating adherence to strict regulatory and compliance standards. The role is part of a collaborative team comprising senior data s", "summaryDescription" : "AI/ML Engineer (intermediate) at Cronos Europa. Strengthen the Cronos Europa team", "createdAt" : "2026-06-14T08:07:42.075", "lastUpdated" : "2026-06-15T09:57:54.112", "ingestTimestamp" : "2026-06-14T08:07:42.075", "mongoId" : "6a17383258b93c861ed2000e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Regulatory and compliance standards" ], "skillCount" : 1, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 1025.6108, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c944474d8ee00a098a010", "title" : "Senior. NET Developer", "company" : "Iris North America", "industry" : "Media", "salary" : { "min" : 130000.0, "max" : 150000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, Massachusetts, United States", "locations" : [ "Boston", "Massachusetts", "United States" ], "timestamp" : "2026-06-15T11:46:24.783", "fingerprint" : "9f05572b31ae7410eb51babc99294fefd54cc2ca545c70a078dd679ca9aaf31b", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/iris/jobs/7675538", "externalId" : "7675538", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "C# .NET, Azure, Cloud PaaS, AI, APIs, Data Integrity, System Architecture", "professionalSkills" : [ "Backend architecture", "Backend logic", "System design" ], "hardSkillsList" : [ "Backend development", "AI integration" ], "hardSkills" : [ { "name" : "Backend development", "level" : "intermediate" }, { "name" : "AI integration", "level" : "intermediate" } ], "majorSkills" : "Backend Development, AI Integration, Azure Cloud", "majorSkillsList" : [ "Backend Development", "AI Integration", "Azure Cloud" ], "coreResponsibilities" : "Develop backend architecture, Integrate AI features, Build APIs, Ensure data integrity, Design system architecture, Explain technical constraints", "teamCollaboration" : "Agile team; Frontend Developer", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "AI features; Client solutions", "domainList" : [ "ai-features", "client-solutions" ], "domainSpecificKnowledge" : [ "AI features", "Client solutions" ], "toolProficiency" : [ "Google Gemini", "Azure Foundry" ], "communicationSkills" : "Explain technical constraints", "innovationCreativity" : "Cutting-edge AI features", "specialRequirements" : "Authorized to work in US", "qualificationsBasic" : "5+ years C# .NET, Azure Cloud PaaS, Azure Foundry, Google Gemini", "qualificationsPreferred" : "Senior position available, Junior position available", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Purpose We are looking for a highly proficient Software Developer to join our agile team. You will focus on backend architecture and logic, leveraging Azure Cloud PaaS and C# .NET. This is not just a maintenance role; you will be instrumental in integrating cutting-edge AI features using Google Gemini and Azure Foundry into our existing client solutions. You will work alongside a dedicated, highly experienced Frontend Developer to build seamless user experiences, meaning your focus will be on robust APIs, data integrity, and system architecture. Responsibilities Develop able to explain technical constraints to non-technical stakeholders. Self-Starter: Self-motivated and able to manage tasks independently within a hybrid environment. About Iris Participate or perish. It’s not just our rallying cry – it’s a creative imperative. Iris is the global creative micro-network built for brands that refuse to blend in. With 650 people across 11 offices, we help clients like Samsung, adidas, Bentley, California Pizza Kitchen, Beiersdorf and Samsonite show up in culture with work that stands apart. Powered by Participation, and brought to life across paid, earned and owned media, our agency model is big enough to be dangerous, small enough to stay agile. Founded outside the ad establishment in 1999, Iris has always been defined by its outsider mindset – one that still drives our mission today. We are proud to be an equal opportunities employer and recruit on talent alone, regardless of age, gender identity, ethnicity, religion, education, class, sexual orientation or disability. We champion diversity and believe it not only benefits, but enhances our creativity, our company and the wider society at large. Salary Range Our estimated range for this role is $130,000-$150,000/year Compensation packages are based on the skill level and experience each candidate brings to their role. There may also be a more senior or junior position available that could be a better fit with your expertise. Each level has its own compensation range. We pride ourselves on competitive salaries, and ensuring pay equity exists across our organization. We benchmark each position against existing employee competencies and 4As compensation data which includes geographic and agency size benchmarks. We also meet with department leaders 3x/year to ensure we are supporting employees in living into their full potential. Our promotions are not limited to a specific time per year. Promotions are tied to performance. Right To Work In The US You must be authorized to work in the US for any employer. At this time, we are not sponsoring or providing assistance with obtaining work authorization. We are in the office Tuesday/Wednesday/Thursday on a hybrid schedule. We look forward to meeting you!", "summaryDescription" : "Senior. NET Developer at Iris North America. Skills: Backend Development, AI Integration, Azure Cloud. Develop backend architecture. Integrate AI features", "postedDate" : "2026-06-14T05:59:44.164", "createdAt" : "2026-06-14T05:59:44.164", "lastUpdated" : "2026-06-15T11:46:24.783", "ingestTimestamp" : "2026-06-14T05:59:44.164", "mongoId" : "6a2c944474d8ee00a098a010", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 130000, "salaryAnnualMax" : 150000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Backend development", "AI integration", "Backend Development", "AI Integration", "Azure Cloud", "Backend architecture", "Backend logic", "System design", "Agile", "AI features", "Client solutions", "Google Gemini", "Azure Foundry" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "_score" : 1019.2253, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Marketing", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c92ba74d8ee00a09866bb", "title" : "Staff Engineer, ML/AI Platform", "company" : "Attentive", "industry" : "Technology", "salary" : { "min" : 280000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "United States", "locations" : [ "United States" ], "timestamp" : "2026-06-16T05:34:12.579", "fingerprint" : "c366d37172e49cfa370ad31141b6afc99d969b23ea31c3188328f3f56648a0c9", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/attentive/jobs/4251570009", "externalId" : "4251570009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Staff", "remoteFriendly" : true, "rawDescription" : "Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights. Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers. With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in Deloitte’s Fast 500 (four years running!), LinkedIn’s Top Startups, Forbes’ Cloud 100 (five years running!), Inc.’s Best Workplaces, and the Human Rights Campaign Foundation's Corporate Equality Index! About the Role We’re seeking an accomplished Staff Software Engineer to join Attentive’s Machine Learning Platform team as a high-impact individual contributor focused on building the AI and ML infrastructure that powers our AI product suite. You’ll architect and build the foundational platform components that enable AI / ML engineers and data scientists to train, deploy, and serve models and agentic infrastructure with velocity, performance, and reliability at scale. As a Staff-level IC, you’ll operate as a technical force multiplier, setting the technical direction for AI and ML infrastructure across Attentive’s AI organization. You’ll lead through influence and technical excellence, advocating for long-term architectural progress while balancing immediate platform needs. Your work will span strategic initiatives measured in quarters and years, focusing on high-leverage decisions that enable entire teams to ship AI and ML capabilities faster and more reliably. Strategic Need Attentive is revolutionizing the digital shopping experience across every channel through our AI product suite for half a billion subscribers. We’re looking for a high impact individual to take our platform from v1 to vNext and beyond — supporting the full spectrum of AI and ML workloads at massive scale. We support traditional models and deep learning today, and we are growing into reinforcement learning and agentic infrastructure quickly. This is a ground-floor opportunity to drive and influence the architectural roadmap for Attentive’s entire AI and ML ecosystem toward self-service workflows, real-time inference at scale, agentic capabilities, and robust model lifecycle management. What You’ll Accomplish Setting Technical Direction - Architect ML platform strategy spanning data pipelines, training infrastructure, and serving layers using cutting-edge tooling like Ray, MLFlow, Metaflow, Argo, and Spark. Uplevel and Innovate Core AI & ML Stack - Build and operate production-grade, low-latency ML serving layers with robust model lifecycle systems including champion/challenger testing, automated rollouts, versioning, and rollback capabilities. Uplevel and Innovate Core AI & ML Stack - Define and drive Attentive’s agentic stack. Technical Leadership - Provide ML infrastructure perspective in high-level discussions about Attentive’s AI strategy spanning multiple quarters and teams. Technical Mentorship - Mentor platform and ML engineers, actively championing team members. Being the “Glue” - Build universal interfaces, architectures, and patterns—like data access layers and prediction serving APIs—that bridge platform capabilities with product needs to streamline high-priority ML work across the organization. Your Expertise You have the experience to know what works, what doesn’t, and why in AI and ML systems. 5+ years focused specifically on ML Platform/MLOps, with deep understanding of gold-standard practices and best-in-class tooling. Proven track record of owning and building core components of ML platforms using tools like Spark, Ray, MLFlow, Kubeflow, or Metaflow. You’ve built and operated a high-throughput agentic stack (MCP / data infrastructure, context store, orchestration, and prompt layer). Strong expertise in Python for both batch processing and online service frameworks. Experience designing and operating online and offline inference systems, understanding the critical differences and tradeoffs between them. Sample Projects Design and implement inference pipelines with champion/challenger shadow testing and automated model promotion. Lead and scale Attentive’s agentic stack from the ground up. Scale real-time feature streaming to handle low-latency, high-volume reinforcement learning workloads. Build a universal data access layer and prediction serving interface that powers ML capabilities across Attentive’s product suite. What We Use Our backend is Java / Kotlin / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Aurora, AirFlow, Postgres, and Redis, hosted via AWS Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS, using tooling like Istio, Datadog, Terraform, CloudFlare, and Helm Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright Our automation is driven by custom and open source machine learning models, industry-leading LLMs, lots of data and tech like Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work. For US based applicants: The US base salary range for this full-time position is $170,000 - $280,000 annually + equity + benefits Our salary ranges are determined by role, level and location #LI-EZ1 By applying for this position, your data will be processed as per Attentive's Privacy Policy. Attentive Company Values Default to Action - Move swiftly and with purpose Be One Unstoppable Team - Rally as each other’s champions Champion the Customer - Our success is defined by our customers' success Act Like an Owner - Take responsibility for Attentive’s success Learn more about AWAKE, Attentive’s collective of employee resource groups. If you do not meet all the requirements listed here, we still encourage you to apply! No job description is perfect, and we may also have another opportunity that closely matches your skills and experience. At Attentive, we know that our Company's strength lies in the diversity of our employees. Attentive is an Equal Opportunity Employer and we welcome applicants from all backgrounds. Our policy is to provide equal employment opportunities for all employees, applicants and covered individuals regardless of protected characteristics. We prioritize and maintain a fair, inclusive and equitable workplace free from discrimination, harassment, and retaliation. Attentive is also committed to providing reasonable accommodations for candidates with disabilities. If you need any assistance or reasonable accommodations, please let your recruiter know.", "summaryDescription" : "Staff Engineer, ML/AI Platform at Attentive", "postedDate" : "2026-06-14T20:04:11.427", "createdAt" : "2026-06-14T20:04:11.427", "lastUpdated" : "2026-06-16T05:34:12.579", "ingestTimestamp" : "2026-06-14T20:04:11.427", "mongoId" : "6a2c92ba74d8ee00a09866bb", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 280000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "_score" : 996.8046, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "68c2e42ff8b1b0376634c748", "title" : "Sr Delivery Consultant (AI/ML)", "company" : "AWS EMEA SARL (UK Branch)", "industry" : "Data Science, Professional Services, Cloud Computing", "salary" : { "min" : 95000.0, "max" : 145000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Delivery Consultant (AI/ML) in London, UK, adjusted for seniority and company size." }, "location" : "London, England, GBR", "locations" : [ "London, England, GBR" ], "timestamp" : "2026-06-16T01:13:27.449", "fingerprint" : "55243af44fa4e8d0465a46040b5beff1f73387ccbf867228eab3fd1d39d20efe", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3073396/apply", "externalId" : "a559a383-7975-42b3-9510-b5ec2ba31b98", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "remoteFriendly" : false, "workSiteFlexibility" : "onsite", "rawDescription" : "The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the project lifecycle. Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. Key job responsibilities As an experienced technology professional, you will be responsible for: - Design and develop robust and scalable AI solutions for business problems - Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem - Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs - Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes - Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts - Comfortable working in a fast paced, highly collaborative, dynamic work environment - Mentor and develop members on the team A day in the life Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Basic Qualifications: - - Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience. - - 8+ years of consulting experience working with Data and AI/ML solutions and 8 + years of experience in developing long-term strategies around product/ solution roadmap with execution programs to deliver on envisioned strategy. - - Recent and demonstrable hands-on experience with AI/ML workloads related to machine learning, deep learning, NLP, CV, GNN, or distributed training. - - Ability to create compelling customer proposals and executive-level presentation skills. Able to communicate effectively in English, within technical and business settings. Preferred Qualifications: - - AWS experience preferred, with proficiency in a wide range of AWS services (Amazon SageMaker, Amazon Bedrock, EMR, S3 and EC2). AWS Certification (Solution Architect Associate, Machine Learning Engineer Associate) - - Working knowledge of AI/ML, generative AI and hands on experience in prompt engineering, deploying and hosting Large Foundational Models. - - Experience with automation and scripting (e.g., Terraform, Python) and knowledge of security and compliance standards (e.g., HIPAA, GDPR). Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates. 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.", "summaryDescription" : "Sr Delivery Consultant (AI/ML) at AWS EMEA SARL (UK Branch)", "postedDate" : "2026-06-14T20:26:38.600", "createdAt" : "2026-06-14T20:26:38.600", "lastUpdated" : "2026-06-16T01:13:27.449", "ingestTimestamp" : "2026-06-14T20:26:38.600", "mongoId" : "68c2e42ff8b1b0376634c748", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3073396/apply", "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 991.01434, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca5bd74d8ee00a09b7ee5", "title" : "AI Product Developer", "company" : "Intellishore", "industry" : "Consulting", "salary" : { "min" : 500000.0, "max" : 750000.0, "currency" : "DKK", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for AI Product Developer in Copenhagen, Denmark, adjusted for mid-seniority and consulting industry." }, "location" : "Copenhagen", "locations" : [ "Copenhagen" ], "timestamp" : "2026-06-16T04:50:21.042", "fingerprint" : "a95208032f632a3639b321e2d71ad7db515690c0ee9b4c717c89a0ec91a4de53", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/intellishoredk/jobs/7749472003", "externalId" : "7749472003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Copenhagen", "country" : "Denmark", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "55.6867243,12.5700724" } ], "locationText" : "Copenhagen, Denmark", "technicalSkills" : "GenAI", "professionalSkills" : [ "Product thinking", "Design craft", "Front-end engineering" ], "hardSkillsList" : [ "User journeys", "Interface design" ], "hardSkills" : [ { "name" : "User journeys", "level" : "intermediate" }, { "name" : "Interface design", "level" : "intermediate" } ], "majorSkills" : "Product strategy, AI tools, User interfaces", "majorSkillsList" : [ "Product strategy", "AI tools", "User interfaces" ], "coreResponsibilities" : "Frame problem with client, Sit with client teams, Map workflows, Translate complexity into journeys, Move from idea to prototype, Use AI tools for productivity, Demo to stakeholders, Iterate against feedback, Build the thing, Ship client-facing POCs, Ship client-facing MVPs, Design and code as same act, Design GenAI interfaces, Wrap AI behavior in interfaces, Tell story around built products, Shape delivery experience", "teamCollaboration" : "Strategy teams; AI teams; Client teams; Cross-discipline teams", "projectManagementSkills" : [ "Roadmap", "User stories" ], "domainKnowledge" : "Data-driven products; AI-driven products; Health 3.0; Streaming responses; Tool use; Retrieval; Multi-step agents", "domainList" : [ "data-driven-products", "ai-driven-products", "health-3-0", "streaming-responses", "tool-use", "retrieval", "multi-step-agents" ], "domainSpecificKnowledge" : [ "Data-driven products", "AI-driven products", "Health 3.0", "Streaming responses", "Tool use", "Retrieval", "Multi-step agents" ], "toolProficiency" : [ "Vercel", "APIs" ], "communicationSkills" : "Case narratives; Signature demos", "continuousLearning" : "Explore new tools; Explore methods; Explore technologies", "innovationCreativity" : "Prototype development; Experiment development", "problemSolvingSkills" : "Ask clarifying questions", "specialRequirements" : "European candidates only, Located in Denmark", "qualificationsBasic" : "Experience building GenAI interfaces, Comfortable deploying to Vercel, Comfortable wiring up APIs, Fluent in AI-native tooling", "qualificationsPreferred" : "Agency background a plus, Studio background a plus, Consultancy background a plus", "workSiteFlexibility" : "Flexible", "rawDescription" : "Do you love the moment an idea becomes something you can click on? Do you enjoy sitting with the people who'll actually use what you make? Are you the kind of builder who can't quite tell where design ends and code begins - and likes it that way? For our Copenhagen office, we are looking for an AI Product Developer to help us design, prototype, and build the next generation of data- and AI-driven products for our clients. This is not a traditional UX designer role, and it's not a traditional front-end role either. It's a builder role for someone who lives at the intersection of product thinking, design craft, front-end engineering, and emerging AI tools. Who is Intellishore? Founded in 2013, Intellishore is home to 80+ passionate specialists in strategy, AI, and data, working from our Copenhagen and Zurich offices. We partner with leading organizations to shape the future of health, working with partners across the ecosystem to unlock the full potential of data and AI. Read more about our vision for Health 3.0 here: https://www.intellishore.dk/health We are builders who believe in an open and honest approach to consulting. We ask questions, stand by our beliefs, and cut through complexity to create clarity. For us, progress doesn’t come from technology alone - it happens when the right people have the right data, strategy, and tools to act. As a collective of developers and strategists, visionaries and pragmatists, we bring energy, expertise, and a passion for helping others succeed. Read more about our team here: https://www.intellishore.dk/about. What will you be working on? You’ll be working closely with our strategy and AI teams, turning strategies, models, and new workflows into products that our clients actually use. The role spans the full path from problem to shipped product: Frame the problem alongside the client. Sit with client teams. Map workflows. Ask the questions that get past surface requirements. Translate business and data complexity into clear user journeys and interfaces. Move from idea to working prototype in days. Use the latest AI tools to power your productivity to get there fastest. Demo to stakeholders. Iterate against real feedback. Build the thing. Ship client-facing POCs and MVPs. Design and code as the same act, not two phases with a handoff between them. Design GenAI interfaces that don't feel like AI slop in a box. Streaming responses, tool use, retrieval, multi-step agents, wrapped in interfaces that make complex AI behaviour feel coherent. Tell the story around what we have built. Hero visuals, case narratives, signature demos. The output that defines how Intellishore shows up to clients and the market. You’ll be a part of shaping the experience of what we deliver and how we show up.  Who are we looking for?  Successful candidates are curious, craft-led builders with entrepreneurial energy. You are perfect for this role if you: Are experienced in building GenAI interfaces. The things you've built work, look good, and were used by someone. You are comfortable deploying to Vercel and wiring up APIs. Care about the craft. Visual quality, interaction design, the small details. You think how something feels is part of whether it works. Are entrepreneurial and comfortable with ambiguity. You are the kind of person who'd rather fail fast than waiting for a full brief. Are collaborative. You enjoy working closely with people across disciplines - strategy, data scientists, engineers, clients. Are fluent in AI-native tooling. You multiply your productivity and quality through the latest AI tools and stay up to date on the latest developments. Have client experience. Agency, studio, or consultancy background is a plus. We don’t care what you studied - we care about what you’ve built. Show us interfaces, prototypes, visuals, experiments, or anything that demonstrates how you turn ideas into products or experiences when you apply. What can we offer you?  1 | Creative freedom and influence You’ll help shape how Intellishore designs and delivers experiences - not just follow templates. 2 | Entrepreneurial environment A fast-moving consultancy where ideas turn into action quickly. 3 | Meaningful impact Work at the intersection of health, AI, and data, helping shape solutions that matter and be a central part of building for Health 3.0.  4 | Learning & exploration Time and space to explore new tools, methods, and technologies - and bring them into practice. 5 | Strategic Seminar A yearly strategic seminar where all Intellishorians across locations spend time strategizing and team-building (in previous years, we've been to Iceland, Germany, Italy, and France) 6 | A strong community Intellishorians are curious, ambitious, and genuinely enjoy working together. Read more about our people and culture at: https://www.intellishore.dk/join  How to apply? Send us:  Your CV Your portfolio of interfaces, prototypes, visuals, motion graphics, experiments, or anything that demonstrates how you turn ideas into experiences (mandatory) A short motivational letter Please note:  Applicants will be invited to interviews on a rolling basis. We are currently only accepting applications from European candidates located in Denmark. For more information about the position, please reach out to Sofie Freund: sofie.freund@intellishore.dk / +45 93 98 17 27. ", "summaryDescription" : "AI Product Developer at Intellishore. Skills: Product strategy, AI tools, User interfaces. Frame problem with client. Sit with client teams", "postedDate" : "2026-06-14T20:12:05.890", "createdAt" : "2026-06-14T20:12:05.890", "lastUpdated" : "2026-06-16T04:50:21.042", "ingestTimestamp" : "2026-06-14T20:12:05.890", "mongoId" : "6a2ca5bd74d8ee00a09b7ee5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "User journeys", "Interface design", "Product strategy", "AI tools", "User interfaces", "Product thinking", "Design craft", "Front-end engineering", "Roadmap", "User stories", "Data-driven products", "AI-driven products", "Health 3.0", "Streaming responses", "Tool use", "Retrieval", "Multi-step agents", "Vercel", "APIs" ], "skillCount" : 19, "jobCategory" : "product", "jobSubcategory" : "product_management", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 982.72235, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Consulting", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2ca20f74d8ee00a09a73ae", "title" : "AI Developer com foco. NET PL/ SR", "company" : "CI&T", "industry" : "Prod_GU3", "salary" : { "min" : 185000.0, "max" : 275000.0, "currency" : "BRL", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior AI Developer in Brazil, adjusted for the technology industry and remote work." }, "location" : "Brazil", "locations" : [ "Brazil" ], "timestamp" : "2026-06-15T23:50:39.189", "fingerprint" : "a8e940388871f9fab268c74975e8746068b37d561444d6a7aa68a82fb9c336f3", "source" : "lever", "language" : "pt", "applyUrl" : "https://jobs.lever.co/ciandt/24f950fb-e514-40a8-a6fd-0179f667f6ef/apply", "externalId" : "24f950fb-e514-40a8-a6fd-0179f667f6ef", "industryFunction" : { }, "structuredLocations" : [ { "country" : "Brazil", "continent" : "sa", "workMode" : "remote" } ], "locationText" : "Brazil", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "NET, AWS, AI, Git, CI/CD", "professionalSkills" : [ "Spec-driven development", "SDLC", "IAC" ], "hardSkillsList" : [ "AI deployment", "AI-native execution", "Agentic SDLC", "Application modernization", "Data & AI", "Martech", "Business strategy", "Automações com agentes", "Multi-step tasks", "Tool usage", "Environment interaction", "Repositório", "API", "Quality control", "Production operation", "Security operation", "Model Context Protocol", "Structured prompt", "Multi-agent workflow", "Human-agent workflow" ], "hardSkills" : [ { "name" : "AI deployment", "level" : "intermediate" }, { "name" : "AI-native execution", "level" : "intermediate" }, { "name" : "Agentic SDLC", "level" : "intermediate" }, { "name" : "Application modernization", "level" : "intermediate" }, { "name" : "Data & AI", "level" : "intermediate" }, { "name" : "Martech", "level" : "intermediate" }, { "name" : "Business strategy", "level" : "intermediate" }, { "name" : "Automações com agentes", "level" : "intermediate" }, { "name" : "Multi-step tasks", "level" : "intermediate" }, { "name" : "Tool usage", "level" : "intermediate" }, { "name" : "Environment interaction", "level" : "intermediate" }, { "name" : "Repositório", "level" : "intermediate" }, { "name" : "API", "level" : "intermediate" }, { "name" : "Quality control", "level" : "intermediate" }, { "name" : "Production operation", "level" : "intermediate" }, { "name" : "Security operation", "level" : "intermediate" }, { "name" : "Model Context Protocol", "level" : "intermediate" }, { "name" : "Structured prompt", "level" : "intermediate" }, { "name" : "Multi-agent workflow", "level" : "intermediate" }, { "name" : "Human-agent workflow", "level" : "intermediate" } ], "majorSkills" : "AI Developer, NET, SDLC, AI", "majorSkillsList" : [ "AI Developer", "NET", "SDLC", "AI" ], "coreResponsibilities" : "Operate SDLC natively with AI, Use automations with agents, Execute multi-step tasks, Use tools, Interact with environment, Structure specifications for AI, Maintain quality control, Operate in production with security", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "AI Deployment; AI-native execution; Agentic SDLC; Application modernization; Data & AI; Martech; Business strategy", "domainList" : [ "ai-deployment", "ai-native-execution", "agentic-sdlc", "application-modernization", "data-ai", "martech", "business-strategy" ], "domainSpecificKnowledge" : [ "AI Deployment", "AI-native execution", "Agentic SDLC", "Application modernization", "Data & AI", "Martech", "Business strategy" ], "toolProficiency" : [ "Git", "CI/CD", "Issue tracking", "Observability" ], "continuousLearning" : "Plataforma de aprendizagem contínua; Plataforma online gratuita; Plataforma para aprendizagem de", "problemSolvingSkills" : "Debugging", "qualificationsBasic" : "Desenvolvimento com .NET, AWS, SDLC, Uso avançado de AI no desenvolvimento, Construção de agentes, Criação de skills reutilizáveis, Integração via MCP, Criação de slash-commands, Orquestração de workflows, Integração com ferramentas, Avaliação crítica de outputs de AI", "qualificationsPreferred" : "Residir na Região Metropolitana de Campinas", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Description Na CI&T , ajudamos grandes empresas a transformar o potencial da AI em impacto real nos negócios com AI Deployment, execução AI-native e tech-integrated business solutions. Com 30 anos de experiência em transformação tecnológica, aceleramos inovação com expertise em agentic SDLC, application modernization, Data & AI, martech e business strategy. Somos 8.000 CI&Ters em mais de 25 países, colaborando para construir soluções com impacto real. AI já faz parte da forma como trabalhamos, evoluímos e inovamos todos os dias. Importante: se você reside na Região Metropolitana de Campinas, sua presença nos escritórios da cidade será obrigatória, conforme a política de frequencia vigente. Olá, aqui é a Bia da CI&T! Sou Analista de Atração de Talentos e procuro pessoas localizadas no Brasil em um dos clientes da CI&T. Procuramos pessoas AI Engineer PL/SR que já opere o SDLC de forma nativa com IA — não como apoio pontual, mas como parte do fluxo. Isso inclui uso consistente de automações com agentes que executam tarefas multi-step, usam ferramentas e interagem com o ambiente (repos, pipelines, APIs). É importante que a pessoa saiba estruturar especificações que alimentam a IA, manter controle de qualidade e operar isso em produção com segurança. ⸻ Você precisa ter prática com: Experiência com desenvolvimento utilizando a linguagens com .NET AWS (infraestrutura como código IAC Spec-driven development (especificação como input primário da AI) Domínio sólido de SDLC (design → build → test → deploy → operate) Uso avançado de AI no desenvolvimento (codegen, testes, refactor, debugging) Construção de agentes (multi-step, tool usage, planning + execution) Criação de skills reutilizáveis e composição de capacidades Integração via MCP (Model Context Protocol) ou equivalente Criacao de slash-commands / interfaces operacionais baseadas em prompt estruturado Orquestração de workflows (multi-agente ou humano + agente) Integração com ferramentas (Git, CI/CD, issue tracking, observabilidade) Avaliação crítica de outputs de AI (qualidade, segurança, consistência) ## Additional Information Nossos benefícios: - Plano de saúde e odontológico; - Vale alimentação e refeição; - Auxílio-creche; - Licença parental estendida; - Parceria com academias e profissionais de saúde e bem-estar via Wellhub (Gympass) TotalPass; - Participação nos Lucros e Resultados (PLR); - Seguro de Vida; - Plataforma de aprendizagem contínua (CI&T University); - Clube de descontos; - Plataforma online gratuita dedicada à promoção da saúde física, mental e bem-estar; - Curso gestante e parentalidade responsável; - Parceria com plataformas de cursos online; - Plataforma para aprendizagem de idiomas; - E muitos outros Mais detalhes sobre os nossos benefícios aqui: https://ciandt.com/br/pt-br/carreiras Na CI&T, a inclusão começa no primeiro contato. Se você é pessoa com deficiência, é importante apresentar o seu laudo durante o processo seletivo. Consulte quais dados são necessários conter no laudo clicando aqui. Assim, podemos garantir o suporte e as adaptações que você merece. Se ainda não tem o laudo caracterizador, não se preocupe: podemos te apoiar para obtê-lo. Temos um time dedicado de Saúde e Bem-estar, especialistas em inclusão e grupos de afinidade que estarão com você em todas as etapas. Conte com a gente para fazer essa jornada lado a lado.", "summaryDescription" : "AI Developer com foco. NET PL/ SR at CI&T. Skills: AI Developer, NET, SDLC, AI. Operate SDLC natively with AI. Use automations with agents", "postedDate" : "2026-06-11T15:11:59.248", "createdAt" : "2026-06-11T15:11:59.248", "lastUpdated" : "2026-06-15T23:50:39.189", "ingestTimestamp" : "2026-06-14T22:02:49.552", "mongoId" : "6a2ca20f74d8ee00a09a73ae", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "150k-200k", "hasSalary" : false, "allSkills" : [ "AI deployment", "AI-native execution", "Agentic SDLC", "Application modernization", "Data & AI", "Martech", "Business strategy", "Automações com agentes", "Multi-step tasks", "Tool usage", "Environment interaction", "Repositório", "API", "Quality control", "Production operation", "Security operation", "Model Context Protocol", "Structured prompt", "Multi-agent workflow", "Human-agent workflow", "AI Developer", "NET", "SDLC", "AI", "Spec-driven development", "IAC", "AI Deployment", "Git", "CI/CD", "Issue tracking", "Observability" ], "skillCount" : 31, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 972.4381, "daysOld" : 4, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305119f292fd229cefa2cb", "title" : "Senior Developer Relations Manager", "industry" : "Product", "salary" : { "min" : 2500000.0, "max" : 4500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Developer Relations Manager in India, adjusted for seniority and industry." }, "location" : "India", "locations" : [ "India" ], "timestamp" : "2026-06-16T11:30:18.163", "fingerprint" : "4d4caa9a704fd769f2103786d9361b9e0604dbe327d3ac50ae515d9bf864eb18", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/23806128-ea2b-4fa5-a31f-129fb66e6787/apply", "externalId" : "23806128-ea2b-4fa5-a31f-129fb66e6787", "industryFunction" : { }, "structuredLocations" : [ { "country" : "India", "continent" : "as", "workMode" : "onsite" } ], "locationText" : "India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 8, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "C, C++, Python, AI/ML, GenAI, Deep learning, Machine learning, AWS, Azure, GCP, OCI, Docker, Kubernetes, VMware, KVM", "professionalSkills" : [ "Developer relations", "Cloud engineering", "Technical evangelism", "Stakeholder management", "Cross-functional collaboration" ], "hardSkillsList" : [ "AI model training", "Model deployment" ], "hardSkills" : [ { "name" : "AI model training", "level" : "intermediate" }, { "name" : "Model deployment", "level" : "intermediate" } ], "majorSkills" : "Developer relations, AI/ML, Cloud platforms", "majorSkillsList" : [ "Developer relations", "AI/ML", "Cloud platforms" ], "coreResponsibilities" : "Develop strategies to drive adoption, Build developer ecosystem, Grow developer ecosystem, Establish strategic relationships, Nurture strategic relationships, Lead technical evangelism activities, Promote adoption of SDKs, Promote adoption of libraries, Promote adoption of AI software tools, Integrate tools into workflows, Serve as technical mentor, Serve as advocate for AI, Serve as advocate for cloud technologies, Monitor industry trends, Monitor competitive landscape, Refine engagement strategies, Refine adoption strategies", "teamCollaboration" : "Cross-functional collaboration; Collaboration with product; Collaboration with engineering; Collaboration with marketing; Collaboration with sales", "domainKnowledge" : "AI computing platforms; Cloud-native architectures; Containerization; Virtualization; AI; GenAI; Deep learning; Machine learning", "domainList" : [ "ai-computing-platforms", "cloud-native-architectures", "containerization", "virtualization", "ai", "genai", "deep-learning", "machine-learning" ], "domainSpecificKnowledge" : [ "AI computing platforms", "Cloud-native architectures", "Containerization", "Virtualization", "AI", "GenAI", "Deep learning", "Machine learning" ], "communicationSkills" : "Technical evangelism; Workshops; Webinars; Meetups", "continuousLearning" : "Continuous technical learning", "innovationCreativity" : "Innovation-driven work environment", "outcomesObjectives" : "Drive adoption of AI computing platforms; Grow the developer ecosystem", "qualificationsBasic" : "Bachelor’s degree in Engineering, 8+ years of experience in developer relations, Hands-on experience with cloud platforms, Solid understanding of containerization, Programming skills in C, C++, and Python, Experience in AI/ML or GenAI-based applications, Experience with deep learning, Machine learning, AI model training and deployment, Excellent communication skills, Stakeholder management skills, Cross-functional collaboration skills", "qualificationsPreferred" : "Master's or PhD preferred", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities Develop and execute strategies to drive adoption of AI computing platforms across developers, startups, ISVs, and enterprise partners Build and grow the developer ecosystem in India in collaboration with product, engineering, marketing, and sales teams Establish and nurture strategic relationships with key AI-native startups, ISVs, and cloud developers Lead technical evangelism activities including workshops, webinars, meetups, and developer-focused events Promote adoption of SDKs, libraries, and AI software tools by integrating them into developer workflows and applications Serve as a technical mentor and advocate for AI and cloud technologies across the developer community Monitor industry trends and competitive landscape to continuously refine engagement and adoption strategies Requirements: Bachelor’s degree in Engineering, Computer Science, or related technical field; Master’s or PhD preferred 8+ years of experience in developer relations, cloud engineering, AI/ML development, or related technical roles Strong hands-on experience with cloud platforms (AWS, Azure, GCP, OCI, or similar) and modern cloud-native architectures Solid understanding of containerization and virtualization technologies (Docker, Kubernetes, VMware, KVM, etc.) Strong programming skills in C, C++, and Python with experience in AI/ML or GenAI-based applications Experience with deep learning, machine learning, or AI model training and deployment in production environments Excellent communication, stakeholder management, and cross-functional collaboration skills Ability to work independently in fast-paced, dynamic, and highly technical environments Benefits: Competitive compensation package with performance-based rewards Opportunity to work on world-leading AI and accelerated computing technologies High-impact role shaping global developer ecosystems and AI adoption Access to cutting-edge tools, platforms, and continuous technical learning opportunities Collaborative, innovation-driven, and highly technical work environment Exposure to global startups, ISVs, and enterprise technology leaders ## 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" : "Senior Developer Relations Manager. Skills: Developer relations, AI/ML, Cloud platforms. Develop strategies to drive adoption. Build developer ecosystem", "postedDate" : "2026-06-15T06:20:46.712", "createdAt" : "2026-06-15T06:20:46.712", "lastUpdated" : "2026-06-16T11:30:18.163", "ingestTimestamp" : "2026-06-16T03:20:59.798", "mongoId" : "6a305119f292fd229cefa2cb", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "AI model training", "Model deployment", "Developer relations", "AI/ML", "Cloud platforms", "Cloud engineering", "Technical evangelism", "Stakeholder management", "Cross-functional collaboration", "AI computing platforms", "Cloud-native architectures", "Containerization", "Virtualization", "AI", "GenAI", "Deep learning", "Machine learning" ], "skillCount" : 17, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 970.92914, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "68e6b1da70f0b99d58d66c0e", "title" : "Delivery Consultant - AI/ML", "company" : "AWS EMEA SARL (UK Branch)", "industry" : "Sales, Advertising, Account Management, Professional Services, Cloud Computing", "salary" : { "min" : 95000.0, "max" : 140000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior Delivery Consultant - AI/ML in London, UK, adjusted for industry and company size." }, "location" : "London, England, GBR", "locations" : [ "London, England, GBR" ], "certifications" : [ "Machine Learning Specialty" ], "timestamp" : "2026-06-15T03:14:45.808", "fingerprint" : "93aba80bf24b28a2bb8f50282920ec6427b17c8477d02612b6f3e67558afe5f0", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3102962/apply", "externalId" : "aa128d9e-22a7-4629-aef4-0a8161db9bf1", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, England, United Kingdom", "employmentType" : "FULL_TIME", "technicalSkills" : "AWS, EC2, S3, RDS, Lambda, IAM, VPC, CloudFormation, Python, Java, C#, AI/ML, GenAI, Generative AI, Foundation Models, Amazon Bedrock, Amazon SageMaker", "professionalSkills" : [ "Cloud architecture", "ML practitioner", "Business experience", "Technical role", "Analytical role", "Software development", "DevOps practices", "AI/ML solutions", "Customer success", "Technical expertise", "Best practices", "Project lifecycle", "Scalable solutions", "Secure solutions", "Migration strategies", "Industry trends", "Emerging technologies", "Innovative solutions", "Implementation process", "Performance optimization", "Risk management", "Enterprise cloud adoption", "Cloud computing initiatives", "Business outcomes", "Mathematical concepts" ], "hardSkillsList" : [ "ML building", "ML validating", "ML deploying", "Large datasets", "Software development", "Distributed computing" ], "softSkillsList" : [ "Mentoring", "Training" ], "hardSkills" : [ { "name" : "ML building", "level" : "intermediate" }, { "name" : "ML validating", "level" : "intermediate" }, { "name" : "ML deploying", "level" : "intermediate" }, { "name" : "Large datasets", "level" : "intermediate" }, { "name" : "Software development", "level" : "intermediate" }, { "name" : "Distributed computing", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" }, { "name" : "Training" } ], "majorSkills" : "AI/ML, Cloud architecture, GenAI models, AWS services", "majorSkillsList" : [ "AI/ML", "Cloud architecture", "GenAI models", "AWS services" ], "coreResponsibilities" : "Design AI/ML solutions, Develop AI/ML solutions, Interact with customer, Understand business problem, Aid in implementation, Use Foundation Models, Meet customer performance needs, Analyze historical data, Extract relevant information, Automate key processes, Optimize key processes, Design solutions, Implement solutions, Manage solutions, Gather requirements, Assess current infrastructure, Propose migration strategies, Provide guidance, Lead implementation process, Ensure adherence to best practices, Optimize performance, Manage risks", "teamCollaboration" : "Customer teams; AWS Partner Network; Customer teams; Global specialty practices", "domainKnowledge" : "Cloud-native architecture; Distributed systems; Generative AI trends; Large language models", "domainList" : [ "cloud-native-architecture", "distributed-systems", "generative-ai-trends", "large-language-models" ], "domainSpecificKnowledge" : [ "Cloud-native architecture", "Distributed systems", "Generative AI trends", "Large language models" ], "toolProficiency" : [ "Amazon Bedrock", "Amazon SageMaker" ], "communicationSkills" : "Convey concepts; Explain technical concepts", "continuousLearning" : "Mentoring; Training; Reusable artifacts", "problemSolvingSkills" : "Root cause analysis", "outcomesObjectives" : "Meet business objectives; Drive customer success; Achieve specific outcomes", "qualificationsBasic" : "3+ years experience in cloud architecture, 3+ years experience handling large datasets, 3+ years software development skills, 5+ years IT platform implementation, Hands-on implementation of ML building, Hands-on application of DevOps practices, Proficiency in Python, Proficiency in one additional language, Understanding of DevOps practices, Verbal and written communications skills, Ability to lead effectively across organizations", "qualificationsPreferred" : "3+ years Technical experience, 3+ years Application Development experience, AWS Professional or Specialty certifications, Experience training distributed ML models, Experience with deploying production-grade ML solutions, Experience with serverless technologies, Knowledge of AI/ML Technology stack, Knowledge of Generative AI trends, Serving ML models through realtime APIs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the project lifecycle. Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. Key job responsibilities As an experienced technology professional, you will be responsible for: 1. Design and develop robust and scalable AI/ML solutions for business problems 2. Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem 3. Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs 4. Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes 5. Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts 6. Comfortable working in a fast paced, highly collaborative, dynamic work environment 7. Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts About the team Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Basic Qualifications: - Experience implementing AWS services in a variety of distributed computing environments - - 3+ years experience in cloud architecture, a ML practitioner with hands-on implementation of ML systems; building, validating and deploying GenAI models - - 5+ years of professional experience in a business environment; experience of IT platform implementation in a highly technical or analytical role - - 3+ years experience of handling large datasets and strong software development skills with proficiency in one or more programming languages including Python and one additional language e.g., Java, C# - - Strong understanding of DevOps practices with practical hands-on application and strong interest in AI/ML solutions. Strong verbal and written communications skills and ability to lead effectively across organizations in English. Preferred Qualifications: - - 3+ years Technical experience preferred, knowledge of AI/ML Technology stack of AWS and Generative AI trends, patterns, anti-patterns - - 3+ years Application Development experience required with serverless technologies and experience training distributed ML models on CPU and GPU hardware - - Serving ML models through realtime APIs and experience with deploying production-grade machine learning solutions on public cloud platforms. Knowledge of vertical use cases for large language models in industries like finance, healthcare, manufacturing etc - - AWS experience preferred, with proficiency in a wide range of AWS services (e.g., EC2, S3, RDS, Lambda, IAM, VPC, CloudFormation). AWS Professional or Specialty level certifications (e.g., Machine Learning Specialty) - - Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates. 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.", "summaryDescription" : "Delivery Consultant - AI/ML at AWS EMEA SARL (UK Branch). Skills: AI/ML, Cloud architecture, GenAI models, AWS services. Design AI/ML solutions. 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We are a team of technologists and legal experts who build proprietary technology and human-in-the-loop workflows that meaningfully improve how lawyers and machines work together — delivering speed, consistency, and quality across high-stakes work. Our systems review complex documents faster and with exceptional accuracy, combining advanced AI with structured legal expertise. Clients receive AI-powered redlines, commentary, and negotiation guidance within hours, at a predictable, volume-based price. Backed by Sequoia, Index Ventures, and Bain Capital Ventures, we're building the end-to-end contracting platform for the next generation of fast-growing companies. THE TEAM The Engineering team builds the core systems, infrastructure, and developer tooling that power Crosby’s AI-first platform. We work across backend, frontend, and AI systems to enable fast iteration, high-quality outputs, and reliable production systems. We prioritize speed, leverage, and strong engineering foundations — investing in systems that make the entire team more effective. THE ROLE As an AI Developer Experience Engineer at Crosby, you'll play a critical role in building the internal systems that enable our team to develop, evaluate, and ship AI features quickly and reliably. You’ll focus on improving the developer experience around LLMs, data, and experimentation — creating tools and infrastructure that accelerate iteration while maintaining quality. You’ll partner closely with engineers, data scientists, and researchers to streamline workflows across prompting, evaluation, fine-tuning, and deployment. This role is for someone who is obsessed with leverage — building systems that make other engineers dramatically more productive. RESPONSIBILITIES 1. Build AI developer tooling: Design and implement internal tools for prompt management, evaluation, experimentation, and model iteration. 2. Improve iteration speed: Create systems that enable rapid testing, debugging, and comparison of model outputs across different approaches. 3. Own evaluation infrastructure: Develop frameworks for benchmarking, regression testing, and monitoring AI system performance. 4. Streamline data workflows: Build pipelines and tooling to support data collection, labeling, and feedback loops for model improvement. 5. Support production systems: Partner with engineering teams to ensure AI features are reliable, observable, and easy to maintain in production. 6. Enable the team: Identify bottlenecks in the development process and build systems that increase developer velocity and confidence. WHO YOU ARE 1. 3–7+ years of software engineering experience, ideally working on developer tools, infrastructure, or platform teams 2. Strong proficiency in Python and experience building backend systems and internal tooling 3. Hands-on experience working with LLMs, APIs (e.g., OpenAI, Anthropic), and modern AI workflows 4. Experience building systems for experimentation, evaluation, or data pipelines 5. Strong systems thinking with the ability to design tools that scale across teams 6. Highly pragmatic with a focus on improving developer velocity and real-world outcomes 7. Strong communicator who can work closely with engineers, researchers, and product teams 8. Proactive, resourceful, and excited about building foundational systems in a fast-moving environment EQUAL OPPORTUNITY Crosby is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the New York City Fair Chance Act. Pursuant to New York Labor Law Section 194-b, the US Pay Range for this position is listed below. Final compensation will be determined based on skills, experience, and qualifications. 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We are a performance-driven company that believes in rewarding excellence and investing in our people. Our structured career development program empowers associates to grow quickly into expanded roles and responsibilities based on merit. With operations throughout the United States, we offer a highly competitive compensation and benefits package, including: Annual bonus program Paid time off Health, dental, vision, and life insurance 401(k)-retirement plan Night and swing shift differential pay for select roles Copilot Studio Agent Developer & Enablement Engineer About the Role We are looking for a Copilot Studio Engineer to join our Information Technology team in Atlanta, GA. This is a full-time, in-person position. We are seeking a Copilot Studio Engineer to design, build, and scale intelligent agent solutions that enhance how our teams work. This role partners closely with business stakeholders to translate operational challenges into AI-powered solutions while enabling broader adoption through training, tools, and best practices. Key Responsibilities Agent Design & Development Design, build, test, and deploy Copilot Studio agents from concept through production Build supporting components including Power Automate flows, Dataverse data structures, knowledge sources, and integrations Apply best practices in prompt design, topics, orchestration, and grounding Validate and monitor agent performance, accuracy, and adoption Enablement, Training & Evangelism Train associates and citizen developers through workshops, office hours, and documentation Evangelize AI use cases and demonstrate value to non-technical users Serve as a coach for teams building their first agents Develop reusable templates, guides, and best-practice resources Business Partnership Partner with stakeholders to translate problems into agent solutions Advise when agent-based solutions are appropriate Ensure alignment with governance, security, and platform standards Qualifications Required: 3+ years of experience with Power Platform (Power Apps, Power Automate, Dataverse) 1+ year of experience with Copilot Studio Experience designing conversational agents Experience translating business needs into solutions Strong communication skills Fully in-office position Preferred: Experience with training or enablement programs Familiarity with AI Builder and Microsoft 365 Copilot Integration experience with APIs and connectors Power Platform certifications Portfolio of delivered solutions Holder is committed to Equal Opportunity Employment (EOE). Substance abuse testing and a background screening is a condition of employment and Holder Construction does not sponsor applicants for immigration status or benefits.", "summaryDescription" : "Copilot Studio Agent Developer & Enablement Engineer at Holder Construction. Skills: Copilot Studio, Power Platform, Agent development. Design Copilot Studio agents. 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From staff augmentation to dedicated IT teams and general software engineering, our nearshore technology services empower businesses to thrive in an ever-evolving digital landscape. About the Role As a Senior Engineer, you will own the technical health and architectural evolution of mission-critical .NET backends. You will act as the primary anchor for complex 3-tier architectures and SQL databases, orchestrating high-performance API integrations and modernizing system workflows. This role requires an autonomous mindset to navigate diverse codebases, provide clarity through documentation, and drive technical excellence across the delivery lifecycle. Your success is measured by system reliability, the proactive management of technical debt, and your ability to mentor and elevate the engineering team. Key Responsibilities Backend Execution: Lead the development of robust .NET architectures, ensuring high performance, security, and scalability. API Orchestration: Design and evolve seamless RESTful integrations to automate and streamline enterprise workflows. Database Mastery: Manage SQL databases environments, focusing on schema design, query optimization, and performance tuning. Team Influence: Elevate team output through deep code reviews, technical mentorship of mid-level and junior engineers, and clear communication with stakeholders. Continuous Improvement: Proactively identify technical debt, reverse-engineer complex logic, and implement modern methodologies to improve efficiency. Requirements Experience: 5+ years of dedicated backend development experience. Tech Stack: Advanced proficiency in C#, .NET Core / .NET 5+, and ASP.NET Web API. Data: Strong experience in SQL databases management, complex stored procedures, and performance tuning. Cloud & DevOps: Deep understanding of CI/CD, Git, and cloud-native environments (GCP, Azure or AWS). Architecture: Proven experience with microservices or distributed 3-tier architectures. Communication: Advanced English proficiency (written and verbal) for collaboration with US-based clients. Environment: Mandatory experience in nearshore/offshore client-facing startup cultures. What you’ll love: USA Contractor / 100% Remote Competitive Pay (USD) Holidays Off & Paid Time Off Health insurance assistance program Opportunity to work with high-growth US-based companies and cutting-edge tech stacks.", "summaryDescription" : "Senior. NET Developer at CodeRoad. Skills: NET, SQL databases, API integrations, System modernization. Own technical health. 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Puram Hobli, Ward No. 85, Bangalore" ], "timestamp" : "2026-06-16T02:39:14.979", "fingerprint" : "508db6c28884b3eb6e32b78ed4411d73a20634136059b00cfed4e293026620c6", "source" : "taleo", "language" : "en", "applyUrl" : "https://tas-daimler.taleo.net/careersection/ex/jobdetail.ftl?job=877691", "externalId" : "877691", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bangalore", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bangalore, Karnataka, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "AI/ML, Deep Learning, PyTorch, TensorFlow, Python, C++, Computer Vision, OpenCV, Sensor Fusion, CAN, Ethernet, AUTOSAR, QNX, CARLA, IPG CarMaker, Reinforcement learning, Predictive modeling", "professionalSkills" : [ "System design", "Model optimization", "Performance optimization", "Latency optimization", "Memory optimization", "Edge deployment", "ECU deployment", "Stakeholder management" ], "hardSkillsList" : [ "Object detection", "Semantic segmentation", "Tracking", "Sensor data processing", "Model training", "Model validation", "Model deployment", "Quantization", "Pruning", "Hardware acceleration" ], "hardSkills" : [ { "name" : "Object detection", "level" : "intermediate" }, { "name" : "Semantic segmentation", "level" : "intermediate" }, { "name" : "Tracking", "level" : "intermediate" }, { "name" : "Sensor data processing", "level" : "intermediate" }, { "name" : "Model training", "level" : "intermediate" }, { "name" : "Model validation", "level" : "intermediate" }, { "name" : "Model deployment", "level" : "intermediate" }, { "name" : "Quantization", "level" : "intermediate" }, { "name" : "Pruning", "level" : "intermediate" }, { "name" : "Hardware acceleration", "level" : "intermediate" } ], "majorSkills" : "AI/ML models, Deep Learning, Computer Vision, Sensor Fusion", "majorSkillsList" : [ "AI/ML models", "Deep Learning", "Computer Vision", "Sensor Fusion" ], "coreResponsibilities" : "Lead design of AI/ML models, Develop AI/ML models, Implement AI/ML models, Develop data pipelines, Manage data pipelines, Collect automotive sensor data, Clean automotive sensor data, Annotate automotive sensor data, Augment automotive sensor data, Optimize ML models, Deploy ML models, Test AI models, Evaluate AI models, Integrate AI software components, Propose innovative solutions, Prototype innovative solutions", "teamCollaboration" : "Verification and validation teams; Cross-functional teams", "domainKnowledge" : "Automotive platforms; Automotive sensor data; Edge devices; ECUs; Safety-critical systems; Automotive communication protocols; Automotive architectures; ISO 26262; Automotive operating systems; Automotive engineering", "domainList" : [ "automotive-platforms", "automotive-sensor-data", "edge-devices", "ecus", "safety-critical-systems", "automotive-communication-protocols", "automotive-architectures", "iso-26262", "automotive-operating-systems", "automotive-engineering" ], "domainSpecificKnowledge" : [ "Automotive platforms", "Automotive sensor data", "Edge devices", "ECUs", "Safety-critical systems", "Automotive communication protocols", "Automotive architectures", "ISO 26262", "Automotive operating systems", "Automotive engineering" ], "toolProficiency" : [ "PyTorch", "TensorFlow", "OpenCV", "CARLA", "IPG CarMaker" ], "innovationCreativity" : "Prototyping innovative solutions", "problemSolvingSkills" : "Root cause analysis", "qualificationsBasic" : "3–5 years of professional experience in AI/ML solutions, Experience in the automotive domain, Bachelor’s or Master’s degree, Expertise in PyTorch, Expertise in TensorFlow, Programming skills in Python, Programming skills in C++, Hands-on experience with Computer Vision algorithms, Experience with OpenCV, Proven experience with automotive sensor data processing, Proven experience with Sensor Fusion techniques, Familiarity with automotive communication protocols, Familiarity with CAN, Familiarity with Ethernet, Understanding of safety-critical systems, Understanding of ISO 26262", "qualificationsPreferred" : "Experience with MLOps practices, Experience with model lifecycle management, Familiarity with AUTOSAR, Familiarity with QNX, Knowledge of simulation tools, Experience in reinforcement learning, Experience in predictive modeling, Domain knowledge in automotive engineering, Exposure to international projects, Exposure to global stakeholder management, Experience with Daimler systems", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "About MBRDI: Mercedes-Benz Research and Development India (MBRDI), headquartered in Bengaluru with a satellite office in Pune, is the largest R&D center for Mercedes-Benz Group AG outside of Germany. Our mission is to drive innovation and excellence in automotive engineering, digitalization, and sustainable mobility solutions, shaping the future of mobility. Key Responsibilities: Design and Development: Lead the end-to-end design, development, and implementation of robust AI/ML models (e.g., Deep Learning models for perception, prediction, and control) for production use in automotive platforms. Data Pipeline Management: Develop and manage large-scale data pipelines for the collection, cleaning, annotation, and augmentation of complex automotive sensor data (e.g., LiDAR, RADAR, camera, ultrasonic) required for model training and validation. Model Optimization and Deployment: Optimize ML models for performance, latency, and memory constraints on Edge devices and automotive-grade Electronic Control Units (ECUs) , utilizing techniques like quantization, pruning, and hardware acceleration. Validation and Testing: Collaborate with verification and validation (V&V) teams to rigorously test and evaluate AI models against safety-critical standards and real-world driving scenarios. System Integration: Integrate developed AI software components with the vehicle’s operating system and other hardware/software subsystems, ensuring seamless functionality and reliability. Research and Innovation: Stay abreast of the latest AI/ML research and automotive technologies, proactively proposing and prototyping innovative solutions to enhance product performance and features. Required Qualifications Experience: 3–5 years of professional experience in developing and deploying AI/ML solutions, with a significant portion of this experience directly in the automotive domain . Education: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related quantitative field. Technical Proficiency: Expertise in common ML/DL frameworks ( PyTorch, TensorFlow ). Strong programming skills in Python and C++ (essential for production-level embedded systems). Hands-on experience with Computer Vision algorithms (e.g., object detection, semantic segmentation, tracking) and libraries like OpenCV . Proven experience with automotive sensor data processing and Sensor Fusion techniques. Automotive Domain Knowledge: Familiarity with automotive communication protocols ( CAN, Ethernet ) and architectures. Understanding of safety-critical systems and standards ( ISO 26262 ). ✨ Preferred Skills (Nice to Have) Experience with MLOps practices and tools for model lifecycle management. Familiarity with automotive operating systems like AUTOSAR or QNX . Knowledge of simulation tools (e.g., CARLA, IPG CarMaker) for testing AI models. Experience in reinforcement learning or predictive modeling for vehicle diagnostics or user behavior. Educational Qualifications: Bachelor's / Master’s degree in Engineering disciplines such as Computer Science, Information Technology, or related fields. Additional certifications (if any): Agile, DevOps, etc. Preferred Qualifications (Good to Have): Domain knowledge in automotive engineering or related fields. Exposure to international projects and global stakeholder management. Experience with Daimler systems or similar global platforms. Why Join Us? Be part of a purpose-driven organization that’s shaping the future of mobility. Work on cutting-edge technologies and global projects. Thrive in a collaborative, diverse, and inclusive environment. Access world-class infrastructure and learning opportunities. Equal Opportunity Statement: At MBRDI, we are committed to diversity and inclusion. We welcome applications from all qualified individuals, regardless of gender, background, or ability. Mercedes-Benz Research and Development India Private Limited", "summaryDescription" : "AI Engineer at MBRDI. Skills: AI/ML models, Deep Learning, Computer Vision, Sensor Fusion. Lead design of AI/ML models. Develop AI/ML models", "createdAt" : "2026-06-14T21:32:30.120", "lastUpdated" : "2026-06-16T02:39:14.979", "ingestTimestamp" : "2026-06-14T21:32:30.120", "mongoId" : "6a191e7758b93c861e39f822", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Object detection", "Semantic segmentation", "Tracking", "Sensor data processing", "Model training", "Model validation", "Model deployment", "Quantization", "Pruning", "Hardware acceleration", "AI/ML models", "Deep Learning", "Computer Vision", "Sensor Fusion", "System design", "Model optimization", "Performance optimization", "Latency optimization", "Memory optimization", "Edge deployment", "ECU deployment", "Stakeholder management", "Automotive platforms", "Automotive sensor data", "Edge devices", "ECUs", "Safety-critical systems", "Automotive communication protocols", "Automotive architectures", "ISO 26262", "Automotive operating systems", "Automotive engineering", "PyTorch", "TensorFlow", "OpenCV", "CARLA", "IPG CarMaker" ], "skillCount" : 37, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 964.4771, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Automotive", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c8c8d74d8ee00a0975cb1", "title" : "Software Engineer, AI/ML Infrastructure", "company" : "Thumbtack", "industry" : "Engineering", "salary" : { "min" : 115000.0, "max" : 155000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Software Engineer, AI/ML Infrastructure in the US technology industry, adjusted for remote work and company size." }, "location" : "Remote, United States", "locations" : [ "Remote, United States" ], "timestamp" : "2026-06-16T02:10:51.179", "fingerprint" : "b8ec64424dd142f1ddbeca77cd2fec5d04a923012a071b1a818ab2eefecc185b", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/thumbtack/3efb1a7b-cfaf-475a-86a9-abff37581b4b/application", "externalId" : "3efb1a7b-cfaf-475a-86a9-abff37581b4b", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "THUMBTACK HELPS MILLIONS OF PEOPLE CONFIDENTLY CARE FOR THEIR HOMES. Thumbtack is the one app you need to take care of and improve your home — from personalized guidance to AI tools and a best-in-class hiring experience. Every day in every county of the U.S., people turn to Thumbtack to complete urgent repairs, seasonal maintenance and bigger improvements. We help homeowners know which projects to do, when to do them and who to hire from our growing community of 300,000 local service businesses. If making an impact inspires you, join us. Imagine what we’ll build together. ABOUT THE MACHINE LEARNING INFRASTRUCTURE TEAM At Thumbtack, our challenges span a wide range of areas, including search, recommendations, matchmaking, pricing, safety, content generation, fraud detection, and more. The ML Infrastructure team is responsible for centralizing, standardizing and evolving AI/ML infrastructure that enables these experiences. We empower product engineering teams by providing scalable, high-performance systems that drive AI innovation at scale. To read more about some of the engineering challenges at Thumbtack, visit our engineering blog https://www.thumbtack.com/engineering/. THE CHALLENGE As a Software Engineer on the ML Infrastructure team, you will work closely with product and platform engineering teams to build and evolve core AI platform capabilities. You will help design and improve systems that allow teams to develop, run, and scale GenAI-powered applications in production. Your work will directly support AI-driven experiences used by millions of customers and pros across the Thumbtack ecosystem. WHAT YOU’LL DO - Build and evolve core AI platform capabilities that enable teams to develop, run, and scale GenAI-powered applications across Thumbtack. - Contribute to the design, development, and deployment of scalable tools and infrastructure to support the efforts of our applied scientists, including traditional ML model training and serving systems, feature and data workflows, CI/CD, orchestration, deployment, and evaluation tooling. - Work hands on across the stack, from backend services and execution infrastructure to integrations with AI models and tooling. - Partner with senior engineers to evaluate next-generation AI infrastructure frameworks and tools that help product teams harness advances in AI. - Drive projects to completion with a strong focus on business impact and measurable outcomes. - Solve complex technical problems and stay up to date with advances in this rapidly evolving space. IN ORDER TO BE SUCCESSFUL, YOU MUST BRING - 1 to 3 years of professional software engineering experience. - Strong fundamentals in data structures, algorithms, and software design. - Proficiency in at least one major programming language, and the ability to work across multiple languages. Our primary stack includes Go and Python. - Experience working with relational or NoSQL databases such as Postgres or DynamoDB. - Demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output - Comfort operating in a fast-paced environment with a certain level of ambiguity, especially when learning and picking up new technologies when projects require it. - You operate with a bias to action, quickly learning what is needed and taking decisive steps to move work forward in ambiguous, fast-paced environments. EXPECTED SALARY RANGES - For candidates living in San Francisco / Bay Area, San Jose, New York City, or Seattle metros, the expected salary range for the role is currently $145,400 - $188,100. - For candidates living in Austin, TX or Washington DC metros or in California, Massachusetts, New Jersey, or Washington states, the expected salary range for the role is currently $130,900 - $169,400. - For candidates living in all other US locations, the expected salary range for this role is currently $123,300 - $159,500. Actual offered salaries will vary and will be based on various factors, such as calibrated job level, qualifications, skills, competencies, and proficiency for the role. Actual offered salaries will vary and will be based on various factors, such as calibrated job level, qualifications, skills, competencies, and proficiency for the role. Thumbtack embraces diversity. We are proud to be an equal opportunity workplace and do not discriminate on the basis of sex, race, color, age, pregnancy, sexual orientation, gender identity or expression, religion, national origin, ancestry, citizenship, marital status, military or veteran status, genetic information, disability status, or any other characteristic protected by federal, provincial, state, or local law. We also will consider for employment qualified applicants with arrest and conviction records, consistent with applicable law. Thumbtack is committed to working with and providing reasonable accommodation to individuals with disabilities. If you would like to request a reasonable accommodation for a medical condition or disability during any part of the application process, please contact: recruitingops@thumbtack.com. If you are a California resident, please review information regarding your rights under California privacy laws contained in Thumbtack’s Privacy policy available at https://www.thumbtack.com/privacy/. We put as much craftsmanship into candidate safety as we do into the hiring experience itself. While scammers may try to impersonate our team, we’ll never ask you for money, banking info, or SSNs during hiring. Check out our blueprint on how to spot the fakes. https://careers.thumbtack.com/recruiting-scams", "summaryDescription" : "Software Engineer, AI/ML Infrastructure at Thumbtack", "createdAt" : "2026-06-14T19:29:33.741", "lastUpdated" : "2026-06-16T02:10:51.179", "ingestTimestamp" : "2026-06-14T19:29:33.741", "mongoId" : "6a2c8c8d74d8ee00a0975cb1", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 115000, "salaryAnnualMax" : 155000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Junior", "dataQualityScore" : 0.6666667, "_score" : 960.7197, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3055e3f292fd229cf22b05", "title" : "AI Engineer", "company" : "Roger", "industry" : "Engineering", "salary" : { "min" : 200000.0, "max" : 250000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "San Francisco Office", "locations" : [ "San Francisco Office" ], "timestamp" : "2026-06-16T10:39:27.762", "fingerprint" : "df944208edd362da6134370188e842610e7feb8f66d7a26904a2dbf583b9b8f9", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/rogerhealthcare/5c5a96ca-819b-4fe2-97c3-50e7245f8937/application", "externalId" : "5c5a96ca-819b-4fe2-97c3-50e7245f8937", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 7, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "LLMs, Open source models", "professionalSkills" : [ "Software engineering", "AI/ML", "Agentic systems", "Inference infrastructure", "Model accuracy", "Clinical outcomes" ], "hardSkillsList" : [ "Model training", "Model fine-tuning", "Eval datasets", "Monitoring infrastructure", "Agentic infrastructure", "Inference infrastructure", "Scalable systems" ], "hardSkills" : [ { "name" : "Model training", "level" : "intermediate" }, { "name" : "Model fine-tuning", "level" : "intermediate" }, { "name" : "Eval datasets", "level" : "intermediate" }, { "name" : "Monitoring infrastructure", "level" : "intermediate" }, { "name" : "Agentic infrastructure", "level" : "intermediate" }, { "name" : "Inference infrastructure", "level" : "intermediate" }, { "name" : "Scalable systems", "level" : "intermediate" } ], "majorSkills" : "AI/ML, LLM, Agentic systems", "majorSkillsList" : [ "AI/ML", "LLM", "Agentic systems" ], "coreResponsibilities" : "Train open source models, Fine-tune open source models, Build eval datasets, Build eval pipelines, Design accuracy measurement, Build inference infrastructure, Build agentic infrastructure, Partner on interfaces, Keep up with research, Bring research into production, Prototype quickly, Harden systems", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Healthcare AI; Home health; Clinical documentation; LLM in healthcare", "domainList" : [ "healthcare-ai", "home-health", "clinical-documentation", "llm-in-healthcare" ], "domainSpecificKnowledge" : [ "Healthcare AI", "Home health", "Clinical documentation", "LLM in healthcare" ], "documentationSkills" : "Clinical documentation", "continuousLearning" : "Keep up with research", "problemSolvingSkills" : "Troubleshooting; Root cause analysis", "outcomesObjectives" : "Push accuracy beyond off-the-shelf; Improve accuracy continuously; Turn outcomes into improvements", "qualificationsBasic" : "7+ years software engineering experience, Meaningful depth in AI/ML, Shipped real AI software, Experience building agentic systems, Comfort building scalable infrastructure", "qualificationsPreferred" : "Startup experience, Product mindset, Comfort across the stack, Operate in ambiguity, High standards for reliability", "workSiteFlexibility" : "Flexible", "rawDescription" : "ABOUT THE ROLE Roger is an AI platform that frees home health clinicians from paperwork so they can focus on what matters: delivering life-changing care to our most vulnerable elderly patients in the comfort of their homes. Backed by leading healthcare investors like SignalFire, we've powered millions of visits, deployed to thousands of clinicians, and we're just getting started. The administrative work behind home health is messy, unstructured, and high-stakes. From clinical documentation to the operational busywork that organizations serving these vulnerable populations face every day, turning dense, nuanced information into accurate records requires LLM systems that extract structure from unstructured data, validate their own outputs, learn from a vast and growing dataset, and continuously improve in accuracy. We are now looking for an AI Engineer to build the intelligence layer at the core of Roger: training and fine-tuning models on our data, building the eval and monitoring infrastructure that keeps them accurate, and shipping LLM-powered workflows that clinicians rely on every day. There is a wide gap between a demo of an AI product and one that actually works for real clinicians caring for real patients, and we are hiring engineers who build on the right side of that gap. WHAT YOU'LL DO - Train and fine-tune open source models, leveraging our vast proprietary dataset to push accuracy beyond what off-the-shelf models can do. - Build eval datasets and pipelines that let us measure model accuracy rigorously and improve it continuously. - Design how we measure accuracy in the first place: the metrics, harnesses, and feedback loops that turn real clinical outcomes into measurable model improvements. - Build scalable, cost-efficient inference infrastructure with great monitoring and observability. - Build better agentic infrastructure and partner on the interfaces that turn model capability into a great clinician experience. - Stay at the frontier: keep up with the latest research, frontier model capabilities, and open source frameworks, and bring the best of it into production. - Prototype quickly, then harden into scalable, secure, and reliable production systems. YOU MIGHT BE A GOOD FIT IF YOU HAVE - 7+ years of professional software engineering experience, with meaningful depth in AI/ML. - Experience training, fine-tuning, or evaluating LLMs and open source models, with real opinions about what works and what does not. - Shipped real AI software to real users. You can describe something you built, what broke, and how you fixed it. - Strong instincts for evals, observability, and the feedback loops that turn user feedback into measurable improvement. - Experience building agentic systems: tool use, generator and critic loops, planners and executors, and orchestration where one agent's output drives another's work. - Comfort building infrastructure that is fast, reliable, and cost-efficient at scale. - Startup experience shipping real features in high-growth environments. - A product mindset, comfort across the stack, and the ability to operate in ambiguity without a clean spec. - High standards for reliability and accuracy when real clinicians and patients depend on your work. Why Join Us? \uD83C\uDFE5 Platinum health, dental, and vision insurance \uD83C\uDFD6️ Flexible PTO \uD83E\uDD16 Be at the forefront of LLM innovation in healthcare \uD83D\uDE80 Founded by AI Researchers from Cornell and Amazon Alexa \uD83D\uDC69‍⚕️ Make a tangible difference in the lives of clinicians and patients \uD83E\uDDE0 Work on a mission that matters, backed by AI innovation and top-tier investors Make a Real Difference: Hear from our Users \uD83D\uDC68‍⚕️ “If I had to give Roger a rating out of 10, I’d give it an 11! You guys changed my life!!” - G.M. from San Francisco, Registered Nurse \uD83D\uDC69‍⚕️ “Roger AI saves me hours per day. I can easily focus on my patients now too.” - J.L. from Tucson, Registered Nurse \uD83D\uDC69‍⚕️ “Being a single mom is tough, but with Roger I can take the time to go to my daughter’s soccer game and also pursue further education.” - T.M. from Dallas, Licensed Vocational Nurse If you're interested in joining a fast-growing healthcare AI startup, we'd love to hear from you TODAY! In person and remote opportunities available.", "summaryDescription" : "AI Engineer at Roger. Skills: AI/ML, LLM, Agentic systems. Train open source models. 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Skills: Computer Vision, AI, ML", "postedDate" : "2026-06-16T01:51:42.293", "createdAt" : "2026-06-16T01:51:42.293", "lastUpdated" : "2026-06-16T15:06:12.719", "ingestTimestamp" : "2026-06-16T01:51:42.293", "mongoId" : "6a307fadf292fd229c05c29e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 155000, "salaryAnnualMax" : 215000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Computer Vision", "AI", "ML", "Augmented Reality" ], "skillCount" : 4, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "_score" : 954.4048, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "68b706967fc9a711f0f6ee85", "title" : "Senior Specialist SA, AI/ML", "company" : "Amazon Web Services Japan GK", "industry" : "Solutions Architect, Solution Architect, Cloud Computing", "salary" : { "min" : 1.2E7, "max" : 1.8E7, "currency" : "JPY", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Specialist SA, AI/ML in Tokyo, Japan, adjusted for seniority and company size within the technology industry." }, "location" : "Tokyo, JPN", "locations" : [ "Tokyo, JPN" ], "timestamp" : "2026-06-15T10:53:04.750", "fingerprint" : "dd8f47df147fa594b4587855c29d4b962dec1fa6da7bbf5c10e70e9e454fc47e", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3069875/apply", "externalId" : "504f2e87-1d0c-44e1-a857-6f19f11d305c", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Tokyo", "country" : "Japan", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "35.6768601,139.7638947" } ], "locationText" : "Tokyo, Japan", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI, ML, AWS", "professionalSkills" : [ "System development", "Service implementation", "Solution architecture" ], "hardSkillsList" : [ "Machine learning", "Cloud technologies" ], "hardSkills" : [ { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Cloud technologies", "level" : "intermediate" } ], "majorSkills" : "AI/ML, Cloud computing, Solutions architecture", "majorSkillsList" : [ "AI/ML", "Cloud computing", "Solutions architecture" ], "coreResponsibilities" : "Advocate AI/ML value on AWS, Address AI/ML challenges, Collaborate with customer teams, Create reference architectures, Develop best practices, Share information externally, Host internal study sessions, Gather new AWS service info, Organize new AWS feature info, Propose solutions to customers, Keep up with ML technologies, Track industry trends, Identify AWS actions, Lead AWS initiatives, Provide customer feedback, Contribute to product development, Collaborate with global teams, Participate in company initiatives, Expand coverage areas", "teamCollaboration" : "Customer-facing teams; Account managers; Other SAs; Global teams; Product development teams", "domainKnowledge" : "AI/ML workloads; Cloud technologies; Machine learning", "domainList" : [ "ai-ml-workloads", "cloud-technologies", "machine-learning" ], "domainSpecificKnowledge" : [ "AI/ML workloads", "Cloud technologies", "Machine learning" ], "communicationSkills" : "Customer communication; Explain technologies", "documentationSkills" : "Reference architectures; Best practices", "continuousLearning" : "Continuous skill development; Learn cloud knowledge; Learn new technologies; Learn AWS services", "problemSolvingSkills" : "Problem resolution", "qualificationsBasic" : "7+ years AI/ML experience, Customer communication skills, Explain advanced technologies, Work across organizations, Continuous learning habit, English reading/writing", "qualificationsPreferred" : "ML model development experience, Distributed training experience, Commercial systems ML experience, Define business challenges AI/ML", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "機械学習担当スペシャリストソリューションアーキテクト (Specialist SA, AI/ML) はAmazon Web Services(AWS)のソリューションアーキテクト(SA)チームの一員として活動します。チームにおいてAI/MLを中心としたワークロードに深い知見をもつ専門家として、様々なお客様のAI/ML技術を活用した取り組みを、クラウドのメリットを最大限活用する形で支援し、ビジネス面や技術面の課題解決をリードすることでお客様に貢献していきます。 AI/ML技術は大変注目を集めている分野であり、お客様も高い興味や期待を持っています。このポジションのミッションは、AI/ML技術の活用に取り組むお客様の技術課題・ビジネス課題を解決することを通じて、より多くのお客様にAWSでAI/MLワークロードを実行していただけるようにすることです。機械学習モデルの開発に取り組むお客様にはそのための支援を、既存のモデルを活用することによる価値創造を目指すお客様にはそれに適した支援を提供します。また、イベントやウェブセミナーでの登壇をはじめとする対外的な情報発信に携わるチャンスもあります。 AWSのクラウド技術はお客様のフィードバックやご要望に基づき日々進化を続けています。AWSがお客様に提供するサービスは多岐にわたります。そのため、入社後も最新技術やトレンドを学び続けることが必要不可欠です。そのため、このポジションに応募する時点ではAWSやクラウド技術を身につけていることは必須ではありません。継続的なスキルアップの一環として、入社後にクラウドに関する知識を身につけようとする意欲を重視します。 SAとしての活動を通じて、AI/ML技術に取り組むお客様のトレンドや、技術開発のトレンドに理解を深めるとともに、様々なAWSクラウドの技術に触れ、興味を持ち、学びを深めていくことを期待しています。それには、あなたが今まで培ってきた技術や経験が充分に活かされるはずです。多様なお客様と、先進的な技術の活用について議論を重ね、価値の実現に貢献していくことは、このポジションならではの経験になるはずです。 As a Machine Learning Specialist Solutions Architect (Specialist SA, AI/ML) at Amazon Web Services (AWS), you will be part of the Solutions Architect (SA) team. With deep expertise in AI/ML workloads, you will contribute to customers' initiatives leveraging AI/ML technologies by maximizing the benefits of the cloud, leading the resolution of business and technical challenges. AI/ML technologies are highly sought-after, and customers have high interest and expectations. Your mission is to enable more customers to run AI/ML workloads on AWS by solving their technical and business challenges in adopting AI/ML technologies. You will provide support for customers developing machine learning models or those seeking to create value by leveraging existing models. Additionally, you may have opportunities for external outreach, such as speaking at events and webinars. AWS cloud technologies continuously evolve based on customer feedback and requests. AWS offers a wide range of services, so it is essential to keep learning about the latest technologies and trends, even after joining. At the time of application, having AWS or cloud technology knowledge is not a prerequisite. Instead, we value your willingness to acquire cloud knowledge as part of your continuous skill development after joining. Through your activities as an SA, you will deepen your understanding of customer trends in AI/ML adoption and technology development trends, while gaining exposure to various AWS cloud technologies, sparking your interest, and deepening your learning. Your existing technical expertise and experience will undoubtedly be valuable. Engaging in discussions with diverse customers and contributing to the realization of value through advanced technology adoption will provide a unique experience in this role. Key job responsibilities 主に日本企業のお客様を対象に、AI/MLワークロードをAWSで実行する価値訴求や、それにまつわる課題解決をにないます。お客様に向けた活動は、そのお客様を担当する営業担当者・他チームのSAなどからなるお客様担当チームと連携しておこないます。リファレンスアーキテクチャ、ベストプラクティス、その他のコンテンツを作成し、情報共有を行います。社外に向けたセミナーで共有することもあれば、社内向けの勉強会を主催したり、内部向けに資料共有という形を取ることもあります。 AWSの新サービスや新機能についての情報を収集・整理し、お客様に提案可能な体制を整えます。加えて、日進月歩の機械学習技術についてキャッチアップを継続するとともに、業界や世の中のトレンドをキャッチし、AWSとして取るべきアクションがあれば声を上げ、時にはその実行をリードします。お客様の声をAWSの製品開発チームなどにフィードバックし、お客様にとって最良のサービスを提供するAWSの取り組みに貢献します。また、グローバルチームと連携しつつ全社的な取り組みに参画することもあります。ご自身の自信のある領域を軸とした日々の業務を通じて経験を積み、徐々に他の領域についてもカバー範囲を広げられるよう取り組みを続けます。 You will primarily engage with Japanese customers, advocating the value of running AI/ML workloads on AWS and addressing related challenges. You will collaborate with customer-facing teams, including account managers and other SAs, to conduct customer-facing activities. You will create reference architectures, best practices, and other content, sharing information through external seminars, internal study sessions, or internal document sharing. You will gather and organize information about new AWS services and features, ensuring readiness to propose solutions to customers. Additionally, you will continuously keep up with the rapidly evolving machine learning technologies and industry trends, raising your voice and sometimes leading initiatives on actions AWS should take. You will provide customer feedback to AWS product development teams, contributing to AWS's efforts to deliver optimal services for customers. You may also collaborate with global teams and participate in company-wide initiatives. Starting with your areas of expertise, you will gradually expand your coverage through daily work and experience accumulation. About the team 私たちはチャレンジャーです。多様なお客様がAWSを使う理由は、また多様であり、これをサポートするために決まったやり方は存在しません。私たちはお客様に気づきを与え、常識を覆す原動力となるべく、常にチャレンジを繰り返しながら学習し、より最適な方法を探るよう活動しています。私たちは多様なお客様を対応するため、多様なバックグランドを持つメンバーが集まり、それぞれの強みを活かして活動しつつ、相互に影響し合うことで学びを継続しています。入社後のメンタリング、マネージャとの定期的な1on1、チームでの定期的な活動の振り返り、社内の他のSAらとの意見交換などを通じて、新しいスキルを学ぶこと、成長していくことをサポートしています。私たちは技術が好きです。AWSはもちろん、テクノロジー全般に関する健全な好奇心を持ち、チームで議論します。 We are challengers. The reasons why diverse customers use AWS are also diverse, and there is no set way to support this. We continue to learn by constantly challenging ourselves and exploring more optimal ways to provide insights and drive unique thinking for our customers. To serve our diverse customers, we bring together members with diverse backgrounds, leveraging each other's strengths while mutually influencing and continuing to learn from one another. Through post-hire mentoring, regular 1-on-1s with managers, periodic team retrospectives, and exchanging ideas with other SAs within the company, we support learning new skills and growing. We love technology. We have a healthy curiosity about AWS and technology in general, and discuss it as a team. AWSについて: https://aws.amazon.com/jp/careers/#how_we_work Amazon は男女雇用機会均等法を順守しています。人種、出身国、性別、性的指向、障がい、年齢、その他の属性によって差別することなく、平等に採用選考の機会を提供しています。障がいをお持ちの方は、以下をご覧ください。https://www.amazon.jobs/en/disability/jp/ #AWSJAPAN #aws-jp-sa-ap Basic Qualifications: - AI/ML技術を利用した研究開発、サービス実装、システム開発といった業務に関する7年以上の経験(Over 7 years of experience in research and development, service implementation, and system development utilizing AI/ML technologies.) - お客様と的確にコミュニケーションができる能力、また高度な技術を平易な言葉で説明できる能力(Ability to communicate effectively with customers and explain advanced technologies in plain language) - 社内外の組織を自ら横断して働くことができる能力(Ability to work across internal and external organizations independently.) - 日々進化するクラウド技術や、自身にとって新しい技術領域について継続的に学ぶ好奇心と学習の習慣(Curiosity and habit of continuous learning about evolving cloud technologies and new technology domains) - 読み書きに支障がないレベルの英語力。流ちょうなものでなくとも、英語での会話に抵抗感がないこと(English proficiency for reading and writing, and willingness to engage in conversations without hesitation, even if not fluent) Preferred Qualifications: - 機械学習モデルの開発や、大規模モデルの分散トレーニングの実践経験(Experience in developing machine learning models, and distributed training of large-scale models) - 機械学習モデルを組み込んだ商用システムの開発・運用経験(Experience in developing and operating commercial systems incorporating machine learning models) - 解決すべきビジネス課題を定義し、AI/ML技術によって解決する事を目的としたプロジェクトの経験(Experience in defining business challenges to be solved, with the aim of solving them using AI/ML technologies) 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" : "Senior Specialist SA, AI/ML at Amazon Web Services Japan GK. Skills: AI/ML, Cloud computing, Solutions architecture. Advocate AI/ML value on AWS. Address AI/ML challenges", "postedDate" : "2026-06-14T01:45:06.885", "createdAt" : "2026-06-14T01:45:06.885", "lastUpdated" : "2026-06-15T10:53:04.750", "ingestTimestamp" : "2026-06-14T01:45:06.885", "mongoId" : "68b706967fc9a711f0f6ee85", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3069875/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Machine learning", "Cloud technologies", "AI/ML", "Cloud computing", "Solutions architecture", "System development", "Service implementation", "Solution architecture", "AI/ML workloads" ], "skillCount" : 9, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "_score" : 954.387, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c8b6874d8ee00a0972c27", "title" : "Principal Developer Advocate, AI", "company" : "Temporal", "industry" : "Developer Relations", "salary" : { "min" : 260000.0, "max" : 325000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "United States", "locations" : [ "United States" ], "timestamp" : "2026-06-15T08:08:32.470", "fingerprint" : "653813c1c67a3e958a1d82204cfa69ce584bcaee6654e572df4b2d65d9a9b983", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/temporal/8ff8a510-5468-44c2-8f48-d46acb39d76f/application", "externalId" : "8ff8a510-5468-44c2-8f48-d46acb39d76f", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI, Python, LLMs, Agents, Retrieval-augmented generation, Function calling, Inference, AI agent frameworks, Model-provider APIs", "professionalSkills" : [ "Technical content creation", "Community building", "Ecosystem engagement", "Roadmap contribution", "Strategy contribution", "Developer experience", "Go-to-market strategy" ], "hardSkillsList" : [ "AI production", "System operation", "Technical writing", "Technical talks" ], "softSkillsList" : [ "Mentoring" ], "hardSkills" : [ { "name" : "AI production", "level" : "intermediate" }, { "name" : "System operation", "level" : "intermediate" }, { "name" : "Technical writing", "level" : "intermediate" }, { "name" : "Technical talks", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "AI Engineering, Developer Advocacy, Production AI, Agentic Systems", "majorSkillsList" : [ "AI Engineering", "Developer Advocacy", "Production AI", "Agentic Systems" ], "coreResponsibilities" : "Represent Temporal at conferences, Deliver talks on reliability, Deliver talks on state, Deliver talks on orchestration, Create content for AI engineers, Create content for backend developers, Demonstrate Temporal's role, Forge ties with AI framework maintainers, Forge ties with open-source communities, Forge ties with ecosystem partners, Gather feedback from AI engineers, Channel feedback to Product, Channel feedback to Engineering, Shape the roadmap, Sharpen developer experience, Align content with releases, Align engagement with releases, Align content with go-to-market, Align engagement with go-to-market, Mentor peers, Raise bar for AI skills", "teamCollaboration" : "Product; Engineering; Marketing; Sales", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Reliability; State; Orchestration; Agentic systems; AI systems; Production AI; AI research; AI tooling; Distributed systems", "domainList" : [ "reliability", "state", "orchestration", "agentic-systems", "ai-systems", "production-ai", "ai-research", "ai-tooling", "distributed-systems" ], "domainSpecificKnowledge" : [ "Reliability", "State", "Orchestration", "Agentic systems", "AI systems", "Production AI", "AI research", "AI tooling", "Distributed systems" ], "toolProficiency" : [ "AI frameworks", "Model provider APIs" ], "communicationSkills" : "Technical content; Compelling talks; Technical writing", "documentationSkills" : "Blogs; Tutorials; Guides", "continuousLearning" : "Evolving AI research; Evolving AI tooling", "problemSolvingSkills" : "Troubleshooting AI systems", "outcomesObjectives" : "Strengthen Temporal's position", "qualificationsBasic" : "8+ years software engineer, AI engineer focus, AI products to production, Build, evaluate, deploy, operate systems, Visibility in AI community, Compelling technical talks, Compelling technical writing, Hands-on depth AI tools, LLMs and agents, Retrieval-augmented generation, Function calling, Evaluation and observability, Inference in real systems, AI agent frameworks, Major model-provider APIs, Proficient in Python, Polyglots welcome", "qualificationsPreferred" : "Public platform, Experience carrying pager, Building AI agent frameworks, Contributing to AI agent frameworks, Familiarity with Temporal, Building AI products with Temporal, Building AI features with Temporal, Open-source contributions AI, Open-source contributions distributed systems, Stewardship AI, Stewardship distributed systems, Prior Developer Relations experience, Prior Developer Advocacy experience", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "Summary: The Principal Developer Advocate, AI is a senior individual-contributor practitioner who serves as a crucial voice for Temporal in the AI engineering community. You’ll earn developers’ trust in this emerging discipline by shipping standout technical content, building real relationships across the AI ecosystem, and sharing what you’ve learned from your hard-won perspective as someone who has built and operated production AI systems. The world's best AI products are built on Temporal. We give developers the primitives to build reliable, long-running, stateful AI applications, and scale them faster than ever before. In this role, you'll help bring Temporal to the next generation of AI engineers. As a senior individual contributor, you'll be a leader in the developer community and within our company, contributing to our AI strategy and roadmap. What You’ll Do: - Represent Temporal at industry conferences, meetups, and workshops, delivering compelling talks on reliability, state, and orchestration in agentic systems - Create influential, high-quality content for AI engineers and backend developers (blogs, tutorials, guides, talks, and videos) that demonstrates Temporal's essential role in reliable AI systems - Forge strong ties with AI framework maintainers, open-source communities, and ecosystem partners to strengthen Temporal's position as critical infrastructure for AI - Act as a key community voice, gathering feedback from AI engineers and channeling it back to Product and Engineering to shape the roadmap and sharpen Temporal's developer experience - Work closely with Product, Engineering, Marketing, and Sales to align content and engagement with new releases and our go-to-market strategy in the AI space - Informally mentor peers and raise the bar for your team's collective AI engineering skills What You’ll Bring: - 8+ years as a software engineer, most recently as an AI engineer with a clear focus on getting AI into production - A track record of shipping AI products or features to production. You understand the discipline of building, evaluating, deploying, and operating real systems, not just prototyping - Existing, demonstrable visibility in the AI engineering community. What that looks like could vary: a popular blog, YouTube channel, podcast, widely used open-source project, social media following, or your role as a frequent conference speaker - A track record of compelling technical talks and writing which clearly establishes your credibility in the eyes of an aspiring AI engineer - Hands-on depth with the tools and patterns of production AI: LLMs and agents, retrieval-augmented generation, function calling, evaluation and observability, and inference in real systems, including working knowledge of AI agent frameworks and the major model-provider APIs - You’re likely proficient in Python and/or TypeScript; polyglots who pick up languages easily are welcome - Curiosity that keeps you on top of rapidly evolving AI research and tooling Nice to Have: - A strong public platform. The kind that makes you recognizable online or when attending a conference - Experience carrying the pager for production AI systems - Experience building or contributing to AI agent frameworks or toolkits - Familiarity with Temporal. Even better: experience building AI products or features using Temporal - Open-source contributions or stewardship in the AI or distributed systems communities - Prior experience in a Developer Relations or Developer Advocacy role Compensation: - The estimated pay range for this role is $260,000 - $325,000. - Additionally, this role is eligible to participate in Temporal's equity plan.", "summaryDescription" : "Principal Developer Advocate, AI at Temporal. Skills: AI Engineering, Developer Advocacy, Production AI, Agentic Systems. Represent Temporal at conferences. 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