{ "count" : 39911, "data" : [ { "id" : "68b706997fc9a711f0f6fe9a", "title" : "2026 Applied Science Internship - Natural Language Processing and Speech Technologies - United States, PhD Student Science", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, studentprograms", "salary" : { "min" : 65.0, "max" : 107.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T04:09:02.109", "fingerprint" : "4cbe0e33cb0d73eeb88883708e5a77b2ce8c8f06e42ed630c13c19332735cbf4", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3051025/apply", "externalId" : "f9b6653f-37f5-4ebe-879b-4ea9deac0e7e", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "technicalSkills" : "NLP, NLU, LLMs, Deep Learning, Speech Recognition, Conversational AI, Natural Language Modeling, Multimodal Learning, LSTM, Transformer-based models, Signal processing, Information extraction, Audio processing, Speaker detection, Large language models, Multilingual modeling, Java, C++, Python", "professionalSkills" : [ "Applied science", "Research problems", "Conversational AI", "Natural language understanding", "Large language models", "Reinforcement learning", "Multimodal learning", "Natural language modeling", "Speech recognition", "Text-to-speech", "Question answering", "Signal processing", "Information extraction", "Audio processing", "Speaker detection", "Multilingual modeling" ], "hardSkillsList" : [ "Natural Language Processing", "Speech Recognition", "Large Language Models", "Deep Learning", "Reinforcement Learning", "Human Feedback/HITL", "Conversational AI", "Multimodal Learning", "Natural Language Modeling", "Text-to-Speech", "Question Answering", "Signal Processing", "Information Extraction", "Audio Processing", "Speaker Detection", "Multilingual Modeling", "Statistical analysis" ], "softSkillsList" : [ "Critical thinking", "Attention to detail" ], "hardSkills" : [ { "name" : "Natural Language Processing", "level" : "intermediate" }, { "name" : "Speech Recognition", "level" : "intermediate" }, { "name" : "Large Language Models", "level" : "intermediate" }, { "name" : "Deep Learning", "level" : "intermediate" }, { "name" : "Reinforcement Learning", "level" : "intermediate" }, { "name" : "Human Feedback/HITL", "level" : "intermediate" }, { "name" : "Conversational AI", "level" : "intermediate" }, { "name" : "Multimodal Learning", "level" : "intermediate" }, { "name" : "Natural Language Modeling", "level" : "intermediate" }, { "name" : "Text-to-Speech", "level" : "intermediate" }, { "name" : "Question Answering", "level" : "intermediate" }, { "name" : "Signal Processing", "level" : "intermediate" }, { "name" : "Information Extraction", "level" : "intermediate" }, { "name" : "Audio Processing", "level" : "intermediate" }, { "name" : "Speaker Detection", "level" : "intermediate" }, { "name" : "Multilingual Modeling", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Critical thinking" }, { "name" : "Attention to detail" } ], "majorSkills" : "Natural Language Processing, Speech Technologies, Large Language Models, Conversational AI", "majorSkillsList" : [ "Natural Language Processing", "Speech Technologies", "Large Language Models", "Conversational AI" ], "coreResponsibilities" : "Develop novel algorithms, Develop scalable algorithms, Develop modeling techniques, Advance state-of-the-art in NLP, Advance state-of-the-art in speech recognition, Advance state-of-the-art in text-to-speech, Advance state-of-the-art in question answering, Advance state-of-the-art in conversational modeling, Tackle groundbreaking research problems, Leverage LSTM models, Leverage transformer-based models, Leverage signal processing, Leverage information extraction, Leverage audio processing, Leverage speaker detection, Leverage large language models, Leverage multilingual modeling, Collaborate with cross-functional teams, Solve complex business problems, Embrace ambiguity, Demonstrate attention to detail", "teamCollaboration" : "Cross-functional teams; Diverse groups", "domainKnowledge" : "Natural Language Processing; Speech Technologies; Conversational AI; Large Language Models; Reinforcement Learning; Deep Learning; Multimodal Learning; Human Feedback/HITL", "domainList" : [ "natural-language-processing", "speech-technologies", "conversational-ai", "large-language-models", "reinforcement-learning", "deep-learning", "multimodal-learning", "human-feedback-hitl" ], "domainSpecificKnowledge" : [ "Natural Language Processing", "Speech Technologies", "Conversational AI", "Large Language Models", "Reinforcement Learning", "Deep Learning", "Multimodal Learning", "Human Feedback/HITL" ], "continuousLearning" : "Mentorship from industry luminaries", "innovationCreativity" : "Explore innovative approaches; Bold ideas celebrated", "problemSolvingSkills" : "Tackle complex research problems", "qualificationsBasic" : "Enrolled in a PhD, 18 years of age or older, Work 40 hours/week minimum, Commit to 12 week internship maximum, Can relocate to where the internship is based, Experience programming in Java, C++, Python or related language, Experience with Natural Language Processing/Understanding, Experience with Large Language Models, Experience with Reinforcement Learning, Experience with Human Feedback/HITL, Experience with Deep Learning, Experience with Speech Recognition, Experience with Conversational AI, Experience with Natural Language Modeling, Experience with Multimodal Learning", "qualificationsPreferred" : "Publications at top-tier conferences or journals, Experience in designing experiments, Statistical analysis of results, Experience in building speech recognition systems, Experience in building machine translation systems, Experience in building natural language processing systems", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Shape the Future of Human-Machine Interaction Are you a master of natural language processing, eager to push the boundaries of conversational AI? Amazon is seeking exceptional graduate students to join our cutting-edge research team, where they will have the opportunity to explore and push the boundaries of natural language processing (NLP), natural language understanding (NLU), and speech recognition technologies. Imagine waking up each morning, fueled by the excitement of tackling complex research problems that have the potential to reshape the world. You'll dive into production-scale data, exploring innovative approaches to natural language understanding, large language models, reinforcement learning with human feedback, conversational AI, and multimodal learning. Your days will be filled with brainstorming sessions, coding sprints, and lively discussions with brilliant minds from diverse backgrounds. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated.. Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available for Natural Language Processing & Speech Applied Science Internships in, but not limited to, Bellevue, WA; Boston, MA; Cambridge, MA; New York, NY; Santa Clara, CA; Seattle, WA; Sunnyvale, CA. Key job responsibilities We are particularly interested in candidates with expertise in: NLP/NLU, LLMs, Reinforcement Learning, Human Feedback/HITL, Deep Learning, Speech Recognition, Conversational AI, Natural Language Modeling, Multimodal Learning. In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of Natural Language Processing and Speech Technologies. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on natural language processing, speech recognition, text-to-speech (TTS), text recognition, question answering, NLP models (e.g., LSTM, transformer-based models), signal processing, information extraction, conversational modeling, audio processing, speaker detection, large language models, multilingual modeling, and more. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. A day in the life - Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in natural language processing, speech recognition, text-to-speech, question answering, and conversational modeling. - Tackle groundbreaking research problems on production-scale data, leveraging techniques such as LSTM, transformer-based models, signal processing, information extraction, audio processing, speaker detection, large language models, and multilingual modeling. - Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in NLP/NLU, LLMs, reinforcement learning, human feedback/HITL, deep learning, speech recognition, conversational AI, natural language modeling, and multimodal learning. - Thrive in a fast-paced, ever-changing environment, embracing ambiguity and demonstrating strong attention to detail. Basic Qualifications: - Are enrolled in a PhD - Are 18 years of age or older - Work 40 hours/week minimum and commit to 12 week internship maximum - Can relocate to where the internship is based - Experience programming in Java, C++, Python or related language - Experience with one or more of the following: Natural Language Processing/Understanding, Large Language Models, Reinforcement Learning, Human Feedback/HITL, Deep Learning, Speech Recognition, Conversational AI, Natural Language Modeling, Multimodal Learning Preferred Qualifications: - Have publications at top-tier peer-reviewed conferences or journals - Experience in designing experiments and statistical analysis of results - Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $65.38/hr in our lowest geographic market up to $107.40/hr in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "2026 Applied Science Internship - Natural Language Processing and Speech Technologies - United States, PhD Student Science at Amazon.com Services LLC. Skills: Natural Language Processing, Speech Technologies, Large Language Models, Conversational AI. Develop novel algorithms. 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Generative AI; Intelligent robotics; Applied robotics; Computer vision; Reinforcement learning; Motion planning; Multimodal LLMs; World models; Image tokenization; Video tokenization; Real2Sim transfer; Sim2real transfer; Bimanual manipulation; Scene understanding; Vision-language-action models", "domainList" : [ "large-language-models", "generative-ai", "intelligent-robotics", "applied-robotics", "computer-vision", "reinforcement-learning", "motion-planning", "multimodal-llms", "world-models", "image-tokenization", "video-tokenization", "real2sim-transfer", "sim2real-transfer", "bimanual-manipulation", "scene-understanding", "vision-language-action-models" ], "domainSpecificKnowledge" : [ "Large language models", "Generative AI", "Intelligent robotics", "Applied robotics", "Computer vision", "Reinforcement learning", "Motion planning", "Multimodal LLMs", "World models", "Image tokenization", "Video tokenization", "Real2Sim transfer", "Sim2real transfer", "Bimanual manipulation", "Scene understanding", "Vision-language-action models" ], "toolProficiency" : [ "Python", "PyTorch", "JAX" ], "communicationSkills" : "Communicate effectively", "continuousLearning" : "Mentorship", "innovationCreativity" : "Groundbreaking discoveries; Bold ideas; Innovation", "problemSolvingSkills" : "Problem-solving skills", "specialRequirements" : "Full-time 40h/week, 12 week internship, May 2026 to September 2026", "outcomesObjectives" : "Deliver impactful solutions", "qualificationsBasic" : "Enrolled in a PhD, 18 years of age or older, Work 40 hours/week minimum, Commit to 12 week internship, Can relocate to where internship is based, Experience programming in Java, C++, Python or related language", "qualificationsPreferred" : "Publications at top-tier peer-reviewed conferences or journals, Experience in designing experiments, Statistical analysis of results", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you a brilliant mind seeking to push the boundaries of what's possible with intelligent robotics? Join our elite team of researchers and engineers - led by Pieter Abeel, Rocky Duan, and Peter Chen - at the forefront of applied science, where we're harnessing the latest advancements in large language models (LLMs) and generative AI to reshape the world of robotics and unlock new realms of innovation. As an Applied Science Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge robotics technologies. You'll dive deep into exciting research projects at the intersection of AI and robotics. This internship is not just about executing tasks – it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning to tackle real-world problems and deliver impactful solutions. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied robotics and AI, where your contributions will shape the future of intelligent systems and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Must be eligible and available for a full-time (40h/ week) 12 week internship between May 2026 and September 2026. Amazon has positions available in San Francisco, CA and Seattle, WA. The ideal candidate should possess: - Strong background in machine learning, deep learning, and/or robotics - Publication record at science conferences such as NeurIPS, CVPR, ICRA, RSS, CoRL, and ICLR. - Experience in areas such as multimodal LLMs, world models, image/video tokenization, real2Sim/Sim2real transfer, bimanual manipulation, open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, and end-to-end vision-language-action models. - Proficiency in Python, Experience with PyTorch or JAX - Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a team Apply now and embark on an extraordinary journey of discovery and innovation! Key job responsibilities - Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and generative AI for robotics - Tackle challenging, groundbreaking research problems on production-scale data, with a focus on robotic perception, manipulation, and control - Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning - Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment, and communicate effectively with diverse stakeholders Basic Qualifications: - Are enrolled in a PhD - Are 18 years of age or older - Work 40 hours/week minimum and commit to 12 week internship maximum - Can relocate to where the internship is based - Experience programming in Java, C++, Python or related language Preferred Qualifications: - Have publications at top-tier peer-reviewed conferences or journals - Experience in designing experiments and statistical analysis of results Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $65.38/hr in our lowest geographic market up to $107.40/hr in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "2026 Applied Science Internship - United States, PhD Student Science Recruiting at Amazon.com Services LLC. Skills: AI, Robotics, LLMs, Deep learning. Develop novel algorithms. 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Awe-inspiring reality; Cutting-edge AI capabilities; Accelerating innovation; Next generation of AI applications; Innovative frameworks; Groundbreaking research; Emerging best practices; Innovations in the field; Novel approaches; Highly innovative ML models; Latest ML techniques", "problemSolvingSkills" : "Solve complex business problems; Think critically", "outcomesObjectives" : "Shape the future of AI; Propel humanity forward; Leave an indelible mark", "qualificationsBasic" : "Enrolled in a PhD, 18 years of age or older, Work 40 hours/week minimum, Commit to 12 week internship maximum, Can relocate to where internship is based, Experience programming in Java, C++, Python or related language, Experience with Knowledge Graphs and Extraction, Experience with Neural Networks/GNNs, Experience with Data Structures and Algorithms, Experience with Time Series, Experience with Machine Learning, Experience with Natural Language Processing, Experience with Deep Learning, Experience with Large Language Models, Experience with Graph Modeling, Experience with Programming/Scripting Languages", "qualificationsPreferred" : "Publications at top-tier peer-reviewed conferences or journals, Experience building machine learning models, Developing algorithms for business application, Experience with MxNet, Experience with TensorFlow", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Unleash Your Potential at the Forefront of AI Innovation At Amazon, we're on a mission to revolutionize the way the world leverages machine learning. Amazon is seeking graduate student scientists who can turn revolutionary theory into awe-inspiring reality. As an Applied Science Intern focused on Information and Knowledge Management in Machine Learning, you will play a critical role in developing the systems and frameworks that power Amazon's machine learning capabilities. You'll be at the epicenter of this transformation, shaping the systems and frameworks that power our cutting-edge AI capabilities. Imagine a role where you develop intuitive tools and workflows that empower machine learning teams to discover, reuse, and build upon existing models and datasets, accelerating innovation across the company. You'll leverage natural language processing and information retrieval techniques to unlock insights from vast repositories of unstructured data, fueling the next generation of AI applications. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA. Key job responsibilities We are particularly interested in candidates with expertise in: Knowledge Graphs and Extraction, Neural Networks/GNNs, Data Structures and Algorithms, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Large Language Models, Graph Modeling, Knowledge Graphs and Extraction, Programming/Scripting Languages In this role, you'll collaborate with brilliant minds to develop innovative frameworks and tools that streamline the lifecycle of machine learning assets, from data to deployed models in areas at the intersection of Knowledge Management within Machine Learning. You will conduct groundbreaking research into emerging best practices and innovations in the field of ML operations, knowledge engineering, and information management, proposing novel approaches that could further enhance Amazon's machine learning capabilities. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. A day in the life - Develop scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Design, development and evaluation of highly innovative ML models for solving complex business problems. - Research and apply the latest ML techniques and best practices from both academia and industry. - Think about customers and how to improve the customer delivery experience. - Use and analytical techniques to create scalable solutions for business problems. Basic Qualifications: - Are enrolled in a PhD - Are 18 years of age or older - Work 40 hours/week minimum and commit to 12 week internship maximum - Can relocate to where the internship is based - Experience programming in Java, C++, Python or related language - Experience with one or more of the following: Knowledge Graphs and Extraction, Neural Networks/GNNs, Data Structures and Algorithms, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Large Language Models, Graph Modeling, Knowledge Graphs and Extraction, Programming/Scripting Languages Preferred Qualifications: - Have publications at top-tier peer-reviewed conferences or journals - Experience building machine learning models or developing algorithms for business application - Experience with popular deep learning frameworks such as MxNet and Tensor Flow Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $65.38/hr in our lowest geographic market up to $107.40/hr in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "2026 Applied Science Internship - Information & Knowledge Management (Machine Learning) - United States, PhD Student Science at Amazon.com Services LLC. Skills: Machine Learning, Information Management, Knowledge Graphs, Deep Learning. Develop systems and frameworks. Develop intuitive tools and workflows", "postedDate" : "2026-06-13T03:07:44.487", "createdAt" : "2026-06-13T03:07:44.487", "lastUpdated" : "2026-06-15T01:45:26.517", "ingestTimestamp" : "2026-06-13T03:07:44.487", "mongoId" : "68b706997fc9a711f0f6fe98", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3051018/apply", "salaryAnnualMin" : 135200, "salaryAnnualMax" : 222560, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Information retrieval techniques", "Data analysis", "Model development", "Model validation", "Model implementation", "ML model development", "Algorithm development", "Critical thinking", "Effective communication", "Machine Learning", "Information Management", "Knowledge Graphs", "Deep Learning", "Knowledge Engineering", "ML operations", "Information and Knowledge Management", "Neural Networks", "GNNs", "Data Structures", "Algorithms", "Time Series", "Large Language Models", "Graph Modeling", "Knowledge engineering" ], "skillCount" : 24, "jobCategory" : "data", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "68c2e43bf8b1b0376634c90e", "title" : "2026 Applied Science Internship - United States, Undergrad Student Science Recruiting, Frontier AI & Robotics", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, studentprograms", "salary" : { "min" : 62.0, "max" : 102.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "San Francisco, California, USA", "locations" : [ "San Francisco, California, USA" ], "timestamp" : "2026-06-15T08:37:55.349", "fingerprint" : "ba6c0f834f0ecfb96e751ba1800ba9e25c395e7fe4c7944a52e803e6e1cf3c89", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3071340/apply", "externalId" : "596dd496-6aa3-47eb-91e0-83a74d9f1e77", "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", "technicalSkills" : "Machine learning, Deep learning, Robotics, LLMs, Generative AI, Python, PyTorch, JAX, Java, C++", "professionalSkills" : [ "Applied science", "Robotics research", "AI research", "Computer vision", "Motion planning", "Multimodal LLMs", "World models", "Image tokenization", "Video tokenization", "Real2Sim transfer", "Sim2real transfer", "Bimanual manipulation", "Scaling LLMs", "Vision-language-action models" ], "hardSkillsList" : [ "Reinforcement learning", "Algorithm development", "Modeling techniques" ], "softSkillsList" : [ "Critical thinking", "Effective communication" ], "hardSkills" : [ { "name" : "Reinforcement learning", "level" : "intermediate" }, { "name" : "Algorithm development", "level" : "intermediate" }, { "name" : "Modeling techniques", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Critical thinking" }, { "name" : "Effective communication" } ], "majorSkills" : "AI, Robotics, Deep learning, LLMs", "majorSkillsList" : [ "AI", "Robotics", "Deep learning", "LLMs" ], "coreResponsibilities" : "Develop novel algorithms, Develop modeling techniques, Advance state-of-the-art in LLMs for robotics, Tackle research problems on production-scale data, Focus on robotic perception, Focus on robotic manipulation, Focus on robotic control, Collaborate with cross-functional teams, Solve complex business problems, Work independently, Thrive in a fast-paced environment, Communicate effectively with diverse stakeholders", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Intelligent robotics; Generative AI for robotics; Robotic perception; Robotic manipulation; Robotic control", "domainList" : [ "intelligent-robotics", "generative-ai-for-robotics", "robotic-perception", "robotic-manipulation", "robotic-control" ], "domainSpecificKnowledge" : [ "Intelligent robotics", "Generative AI for robotics", "Robotic perception", "Robotic manipulation", "Robotic control" ], "communicationSkills" : "Communicate effectively", "continuousLearning" : "Mentorship from industry luminaries", "innovationCreativity" : "Groundbreaking discoveries; Unlock new realms of innovation; Bold ideas celebrated", "problemSolvingSkills" : "Excellent problem-solving skills", "qualificationsBasic" : "Enrolled in a Bachelor's degree or above, 18 years of age or older, Work 40 hours/week minimum, Commit to 12 week internship maximum, Can relocate to where the internship is based, Experience programming in Java, C++, Python or related language", "qualificationsPreferred" : "Publications at top-tier peer-reviewed conferences or journals, Experience in designing experiments, Statistical analysis of results", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you a brilliant mind seeking to push the boundaries of what's possible with intelligent robotics? Join our elite team of researchers and engineers - led by Pieter Abeel, Rocky Duan, and Peter Chen - at the forefront of applied science, where we're harnessing the latest advancements in large language models (LLMs) and generative AI to reshape the world of robotics and unlock new realms of innovation. As an Applied Science Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge robotics technologies. You'll dive deep into exciting research projects at the intersection of AI and robotics. This internship is not just about executing tasks – it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning to tackle real-world problems and deliver impactful solutions. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied robotics and AI, where your contributions will shape the future of intelligent systems and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available in San Francisco, CA. The ideal candidate should possess: - Strong background in machine learning, deep learning, and/or robotics - Publication record at science conferences such as NeurIPS, CVPR, ICRA, RSS, CoRL, and ICLR. - Experience in areas such as multimodal LLMs, world models, image/video tokenization, real2Sim/Sim2real transfer, bimanual manipulation, open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, and end-to-end vision-language-action models. - Proficiency in Python, Experience with PyTorch or JAX - Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a team Apply now and embark on an extraordinary journey of discovery and innovation! Key job responsibilities - Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and generative AI for robotics - Tackle challenging, groundbreaking research problems on production-scale data, with a focus on robotic perception, manipulation, and control - Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning - Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment, and communicate effectively with diverse stakeholders Basic Qualifications: - Are enrolled in a Bachelor's degree or above - Are 18 years of age or older - Work 40 hours/week minimum and commit to 12 week internship maximum - Can relocate to where the internship is based - Experience programming in Java, C++, Python or related language Preferred Qualifications: - Have publications at top-tier peer-reviewed conferences or journals - Experience in designing experiments and statistical analysis of results Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $62.21/hr in our lowest geographic market up to $102.31/hr in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "2026 Applied Science Internship - United States, Undergrad Student Science Recruiting, Frontier AI & Robotics at Amazon.com Services LLC. Skills: AI, Robotics, Deep learning, LLMs. Develop novel algorithms. Develop modeling techniques", "postedDate" : "2026-06-13T11:08:27.553", "createdAt" : "2026-06-13T11:08:27.553", "lastUpdated" : "2026-06-15T08:37:55.349", "ingestTimestamp" : "2026-06-13T11:08:27.553", "mongoId" : "68c2e43bf8b1b0376634c90e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3071340/apply", "salaryAnnualMin" : 128960, "salaryAnnualMax" : 212160, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Reinforcement learning", "Algorithm development", "Modeling techniques", "Critical thinking", "Effective communication", "AI", "Robotics", "Deep learning", "LLMs", "Applied science", "Robotics research", "AI research", "Computer vision", "Motion planning", "Multimodal LLMs", "World models", "Image tokenization", "Video tokenization", "Real2Sim transfer", "Sim2real transfer", "Bimanual manipulation", "Scaling LLMs", "Vision-language-action models", "Intelligent robotics", "Generative AI for robotics", "Robotic perception", "Robotic manipulation", "Robotic control" ], "skillCount" : 28, "jobCategory" : "data", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Robotics" }, { "id" : "6a305739f292fd229cf35bcb", "title" : "Medical Science Liaison / Senior Medical Science Liaison - United Kingdom", "company" : "Beeline Medicines", "salary" : { "min" : 120000.0, "max" : 170000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Medical Science Liaison in the United Kingdom, adjusted for the biotech industry and remote work." }, "location" : "United States", "locations" : [ "United States" ], "timestamp" : "2026-06-16T08:56:06.268", "fingerprint" : "e9d632f61231f3f232a9c68528c11606712cab70dccabd62a9c533bcad72fddf", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/beelinemedicines/jobs/4286218009", "externalId" : "4286218009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "minimumEducation" : "PharmD, PhD, or MD", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "remoteFriendly" : true, "rawDescription" : "About Beeline Medicines: Beeline Medicines is a clinical‑stage biotechnology company focused on developing and delivering category-leading precision therapies to transform the lives of people living with autoimmune and inflammatory diseases. With a portfolio of potential best-in-class and first-in-disease therapeutic candidates that directly target key pathways governing dysregulated immunological and inflammatory responses, the Company is developing medicines that have the opportunity to provide durable, life-changing impact. Led by an established executive team and backed by world-class life science investors, each day Beeline Medicines is determined to bring the scientific rigor and operational excellence to get to what matters for patients – realizing a world where people with immune-mediated diseases can live life fully. Job Summary: We are seeking talented field-based scientific professionals to join our Medical Affairs team as a Medical Science Liaison (MSL) or Senior Medical Science Liaison (Senior MSL) within our Immunology ensuring optimal allocation of time and resources to maximize impact. Conduct sophisticated, peer-to-peer scientific exchange with senior thought leaders, clinical investigators, and HCPs — including discussions of emerging clinical data, nuanced benefit-risk considerations, and evolving disease paradigms relevant to organization's I including KME identification, scientific input into agenda design, and synthesis of outcomes into strategic recommendations. Perform other duties and responsibilities as assigned. Qualifications: Education: Advanced degree required — PharmD, PhD, or MD in a relevant life sciences, pharmacy, or biomedical field. Post-doctoral training, clinical fellowship, or residency in a relevant discipline strongly preferred. Minimum of 5 years of MSL or field-based medical affairs experience in the pharmaceutical or biotech industry, with demonstrated expertise in immunology, inflammation, or a closely related therapeutic area preferred. Prior involvement in IIS management or clinical trial support activities preferred. Clinical-stage biotech experience a plus Advanced scientific and clinical expertise in immunology and inflammation — demonstrates deep, current knowledge of disease biology, treatment algorithms, clinical trial endpoints, emerging mechanisms, and the competitive I experience with digital engagement platforms and virtual scientific exchange, with consistent documentation quality that reflects field excellence standards. Leverage AI-driven and omnichannel engagement strategies to complement in-person interactions; optimizing reach, frequency, and scientific exchange effectiveness with key stakeholders. Deep working knowledge of medical affairs compliance — including PhRMA guidelines, FDA regulations, and IIS management frameworks — demonstrated through a sustained record of compliant, high-quality field interactions and the ability to guide junior colleagues on compliance questions. Operates with full strategic independence — manages territory, KOL engagement plans, and field priorities without day-to-day guidance; proactively identifies opportunities and addresses challenges with sound judgment and organizational awareness. Highly sophisticated scientific communicator — engages senior KOLs, principal investigators, and academic thought leaders in nuanced, data-rich scientific dialogue that builds long-term credibility and trust for Beeline's I&I platform. Skilled at synthesizing and presenting complex field intelligence in structured, executive-ready internal communications — delivers strategic actionable recommendations and tracking downstream impact to refine engagement strategy and maximize organizational value to Medical Affairs and clinical leadership with clarity and confidence. Experienced facilitator and presenter — equally effective in one-on-one KOL settings, investigator meetings, advisory board participation, and large medical congress environments, with a demonstrated ability to adapt scientific communication style to audience needs. Ability to safely and successfully operate a motor vehicle is required. Valid Driver’s License and a driving record in compliance with company standards Position may require ability to travel 50%+ as needed of time or more including occasional overnight stay driven by business need. Must be able to work evenings and weekends, as needed, for physician or patient events (both in person and virtual). Depending on geography, must have the ability to manage a multi-state territory with diverse customer base. Salary Range: The expected salary range for this position varies by location and will be communicated based on the country or region in which the selected candidate is hired. Actual pay will be determined based on experience, qualifications, location, and other job-related factors permitted by applicable local law. A discretionary annual bonus and long-term incentive award (e.g., equity) may be available based on individual and Company performance. Salary Range £65,000—£99,000 GBP Benefits: We offer a comprehensive benefits package tailored to the country and region in which you are hired, in compliance with local laws and practices. Benefits may include, but are not limited to: Competitive health and wellness coverage (structure and premiums vary by country) Paid time off, public holidays, and additional leave entitlements in accordance with local requirements Flexible work arrangements / hybrid schedule Benefits vary by location and are subject to eligibility requirements, local regulations, and plan terms. Specific benefit details applicable to your country or region will be provided during the offer process. Equal Employment Opportunity: Beeline Medicines is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, age, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. Reasonable Accommodation: If you require a reasonable accommodation to participate in the application or interview process, please contact careers@beelinemedicines.com to request an accommodation. We are committed to providing equal access to all candidates. Privacy Upon submission of this form I understand that Beeline Medicines is based in the United States and personal data submitted in the form will be transferred and accessed in the U.S., Information about Beeline Medicines privacy practices can be found at Privacy Policy - Beeline Medicines", "summaryDescription" : "Medical Science Liaison / Senior Medical Science Liaison - United Kingdom at Beeline Medicines", "postedDate" : "2026-06-15T23:18:45.902", "createdAt" : "2026-06-15T23:18:45.902", "lastUpdated" : "2026-06-16T08:56:06.268", "ingestTimestamp" : "2026-06-15T23:18:45.902", "mongoId" : "6a305739f292fd229cf35bcb", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "general", "jobSubcategory" : "general", "seniorityLevel" : "Senior", "dataQualityScore" : 0.7777778, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.98 }, { "id" : "68c2e42bf8b1b0376634c6b5", "title" : "Senior Applied Scientist, Healthcare and Life Science", "company" : "Amazon Development Center U.S., Inc.", "industry" : "Machine Learning Science, Applied Science, Cloud Computing", "salary" : { "min" : 150400.0, "max" : 260000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T04:57:12.110", "fingerprint" : "be64cf30f4db50ee5274189526d52616f425141204df8073c2c0c44e80ead2af", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3076380/apply", "externalId" : "01633c2f-2860-4146-b798-9191c24aad48", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, R, SQL, Spark, Scala, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, AWS, GCP, Azure, SageMaker, Vertex AI, Synapse, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, Tableau, Power BI, Looker", "professionalSkills" : [ "Data engineering", "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis" ], "hardSkillsList" : [ "Regression analysis", "Classification models", "Clustering algorithms", "Time-series forecasting", "A/B testing", "Causal inference" ], "hardSkills" : [ { "name" : "Regression analysis", "level" : "intermediate" }, { "name" : "Classification models", "level" : "intermediate" }, { "name" : "Clustering algorithms", "level" : "intermediate" }, { "name" : "Time-series forecasting", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "majorSkills" : "Machine Learning, Data Engineering, Business Intelligence, Statistical Modeling", "majorSkillsList" : [ "Machine Learning", "Data Engineering", "Business Intelligence", "Statistical Modeling" ], "coreResponsibilities" : "Develop and deploy machine learning models, Design and implement data pipelines, Build and maintain business intelligence dashboards, Perform data analysis and generate insights, Collaborate with cross-functional teams, Stay current with industry trends", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Healthcare data; Life science data", "domainList" : [ "healthcare-data", "life-science-data" ], "domainSpecificKnowledge" : [ "Healthcare data", "Life science data" ], "toolProficiency" : [ "SQL", "Python", "R", "Spark", "Dbt", "Snowflake", "BigQuery", "Databricks", "Airflow", "Tableau", "Power BI", "Looker", "Scikit-learn", "TensorFlow", "PyTorch", "AWS", "GCP", "Azure" ], "qualificationsBasic" : "5+ years of experience in data science or related field, Proficiency in SQL, Bachelor's degree in Computer Science, Statistics, Mathematics, or related quantitative field", "qualificationsPreferred" : "PhD in a relevant field, Experience with cloud platforms (AWS, GCP, Azure), Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch), Experience with BI platforms (Tableau, Power BI, Looker)", "remoteFriendly" : false, "workSiteFlexibility" : "onsite", "rawDescription" : "We are looking for an exceptional senior applied scientist to join the AWS Applied AI Life Sciences organization. You will invent, implement, and deploy state of the art machine learning algorithms and intelligent AI systems to solve complex problems in healthcare and life sciences area, making a meaningful impact on patient lives. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. Key job responsibilities - Design, develop, and deploy novel Agentic systems and ML solutions for complex healthcare challenges - Navigate ambiguity and create clarity in early-stage product development - Establish best practices for ML experimentation, evaluation, development and deployment - Collaborate with product managers, engineers, and domain experts to transform research into production-quality features - Mentor junior scientists and contribute to the technical strategy of the team A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. About the team We are a multidisciplinary team of product managers, engineers, scientists, and domain experts working at the intersection of AI/ML and healthcare. We leverage AWS's expertise in secure, scalable cloud computing and applied AI to solve complex challenges in healthcare and life sciences. Our team values customer obsession, technical excellence, innovation, and a commitment to improving patient outcomes through technology. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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. Basic Qualifications: - PhD, or Master's degree and 6+ years of applied research experience - 5+ years of building machine learning models for business application experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning - Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, etc.) - Applied Research experience in Biostatistics, Pharmacology, Pharmacometrics, or other related fields. Preferred Qualifications: - Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability - Experience with predictive modeling in healthcare, pharmacology, or clinical trial contexts - Experience working with healthcare data (e.g., EHR, clinical trials, medical claims) - Familiarity with time series analysis, causal inference methods and explainable AI approaches - Understanding of synthetic data generation techniques (e.g., GANs) for healthcare applications - Experience in applying Generative AI and building Agentic systems. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Senior Applied Scientist, Healthcare and Life Science at Amazon Development Center U.S., Inc.. Skills: Machine Learning, Data Engineering, Business Intelligence, Statistical Modeling. Develop and deploy machine learning models. Design and implement data pipelines", "postedDate" : "2026-06-14T19:48:02.728", "createdAt" : "2026-06-14T19:48:02.728", "lastUpdated" : "2026-06-16T04:57:12.110", "ingestTimestamp" : "2026-06-14T19:48:02.728", "mongoId" : "68c2e42bf8b1b0376634c6b5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3076380/apply", "salaryAnnualMin" : 150400, "salaryAnnualMax" : 260000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Regression analysis", "Classification models", "Clustering algorithms", "Time-series forecasting", "A/B testing", "Causal inference", "Machine Learning", "Data Engineering", "Business Intelligence", "Statistical Modeling", "Data engineering", "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Healthcare data", "Life science data", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "SQL", "Python", "R", "Spark", "Dbt", "Snowflake", "BigQuery", "Databricks", "Airflow", "Tableau", "Power BI", "Looker", "Scikit-learn", "TensorFlow", "PyTorch", "AWS", "GCP", "Azure" ], "skillCount" : 41, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "6a3056b3f292fd229cf2d4c2", "title" : "Speech Language Pathologist", "company" : "BAYADA Home Health Care", "industry" : "Healthcare", "salary" : { "min" : 80.0, "max" : 90.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Field", "locations" : [ "Field", "Home Health - Field" ], "timestamp" : "2026-06-16T08:33:00.677", "fingerprint" : "e0013674a46e98928bcdcc605ea69ae24a8b7824869e208bf872e8f0fca38c3e", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/bayada/jobs/8592627002", "externalId" : "8592627002", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Milton", "state" : "Pennsylvania", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "41.0177269,-76.8530840" }, { "city" : "Mifflinburg", "state" : "Pennsylvania", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.9175820,-77.0477501" }, { "city" : "Selinsgrove", "state" : "Pennsylvania", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7993524,-76.8619072" }, { "city" : "Beavertown", "state" : "Pennsylvania", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7536190,-77.1693212" } ], "locationText" : "Milton, Pennsylvania, United States; Mifflinburg, Pennsylvania, United States; Selinsgrove, Pennsylvania, United States; Beavertown, Pennsylvania, United States", "experienceMinYears" : 1, "rawDescription" : "Make an Impact as a Speech Language Pathologist at BAYADA Home Health Care. BAYADA Home Health Care is currently seeking a Speech Language Pathologist (SLP) to join our Big Island Visits team. SLP’s work with clients in their home, craft treatment plans, and apply innovative techniques to help them reach their goals. You will be an integral member of a multi-disciplinary health care team that provides skilled nursing and rehabilitative care to clients, affording them the opportunity to remain at home. We believe our clients and their families deserve the highest quality home health care delivered with compassion, excellence, and reliability. Delivering this care is our highest priority and greatest joy. We want you to join us! How You’ll Make an Impact: Perform thorough evaluations to assess, diagnose and provide therapeutic interventions for clients who are experiencing, speech, language, communication or swallowing difficulties Develop a treatment plan based on the evaluation, physician’s orders and recommended goals Continually assess and revise the speech therapy care plan and participate with BAYADA Clinicians in the multidisciplinary care plan, as appropriate Educate and instruct patients, family members, or other patient representatives, in rehabilitative care and activities necessary to promote the client's health, safety and independent living Accurately document observations, interventions and evaluations pertaining to patient care management and services provided, utilizing a state-of-the-art touch pad tablet Compensation referral bonuses Paid Time Off: PTO (paid time off) and paid holidays Reimbursements: Mileage reimbursement or schedule-specific benefits Life Insurance: Employer-paid life insurance Wellness: Employee Assistance Program (EAP) Qualifications for a BAYADA Speech Language Pathologist: A current license as a Speech Language Pathologist in Hawaii One year experience as a Speech Language Pathologist Thrive in a Culture That Cares: We put your well-being first, fostering an inclusive and collaborative environment of belonging where you can achieve your goals. Don't just take our word for it: Voted by Star-Advertiser Readers as the #1 Non-Medical Home Care Provider   Forbes Top 10 Employer in Hawaii, 3 years in a row  Newsweek's Greatest Workplace for Overall, Women, Parents & Families, Diversity Forbes Best Employers for Veterans Be part of a caring, professional team that is instrumental in providing the highest quality care while developing your career with an industry leader. Apply now for immediate consideration. As a BAYADA Speech Language Pathologist you will be prepared to succeed. Paid training from day one in the office, in the home, and online to make sure you feel confident. Clinical support whenever you need it around the clock. BAYADA recognizes and rewards our SLPs who set and maintain the highest standards of excellence. We can’t wait to meet you! Locations We’re Hiring: Hilo, Hawaii Type: Per Diem Base Pay, depending upon qualifications and subject to negotiation: $80-$90 per point As an accredited, regulated, certified, and licensed home health care provider, BAYADA complies with all state/local mandates. BAYADA is celebrating 50 years of compassion, excellence, and reliability. Learn more about our 50th anniversary celebration and how you can join in here. BAYADA Home Health Care, Inc., and its associated entities and joint venture partners, are Equal Opportunity Employers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, age, disability, pregnancy or maternity, sexual orientation, gender identity, citizenship status, military status, or any other similarly protected status in accordance with federal, state and local laws. Hence, we strongly encourage applications from people with these identities or who are members of other marginalized communities.", "summaryDescription" : "Speech Language Pathologist at BAYADA Home Health Care", "postedDate" : "2026-06-15T23:19:47.007", "createdAt" : "2026-06-15T23:19:47.007", "lastUpdated" : "2026-06-16T08:33:00.677", "ingestTimestamp" : "2026-06-15T23:19:47.007", "mongoId" : "6a3056b3f292fd229cf2d4c2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMax" : 90, "salaryBand" : "<30k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "healthcare", "jobSubcategory" : "support", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "68b706997fc9a711f0f6fe99", "title" : "2026 Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning)", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, studentprograms", "salary" : { "min" : 65.0, "max" : 107.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T00:59:44.852", "fingerprint" : "d9bc2f5a28dbd10103bdb337b1d4cde39238a2f6d123ab4089ebae3b51e08e5d", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3051006/apply", "externalId" : "022be1fe-bf03-4920-9103-42ef8c109fe0", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "technicalSkills" : "Java, C++, Python, Optimization, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised Learning, Unsupervised Learning, Deep Learning, Predictive Modeling", "professionalSkills" : [ "Applied science", "Machine learning", "Data science", "Data engineering", "Business intelligence", "Analytics engineering", "Quantitative analysis", "ML algorithms", "Modeling techniques", "Research problems", "Scalable algorithms", "Data analyses", "Model development", "Model validation", "Model implementation" ], "hardSkillsList" : [ "Bayesian optimization", "Multi-armed bandits", "Statistical modeling", "Graph models", "Deep reinforcement learning", "Supervised learning", "Semi-supervised learning", "Unsupervised learning", "Advanced statistical modeling", "Graph models", "Predictive modeling", "Scalable algorithms", "Modeling techniques", "RL algorithms", "Data analyses", "Model development", "Model validation", "Model implementation" ], "softSkillsList" : [ "Critical thinking", "Effective communication" ], "hardSkills" : [ { "name" : "Bayesian optimization", "level" : "intermediate" }, { "name" : "Multi-armed bandits", "level" : "intermediate" }, { "name" : "Statistical modeling", "level" : "intermediate" }, { "name" : "Graph models", "level" : "intermediate" }, { "name" : "Deep reinforcement learning", "level" : "intermediate" }, { "name" : "Supervised learning", "level" : "intermediate" }, { "name" : "Semi-supervised learning", "level" : "intermediate" }, { "name" : "Unsupervised learning", "level" : "intermediate" }, { "name" : "Advanced statistical modeling", "level" : "intermediate" }, { "name" : "Graph models", "level" : "intermediate" }, { "name" : "Predictive modeling", "level" : "intermediate" }, { "name" : "Scalable algorithms", "level" : "intermediate" }, { "name" : "Modeling techniques", "level" : "intermediate" }, { "name" : "RL algorithms", "level" : "intermediate" }, { "name" : "Data analyses", "level" : "intermediate" }, { "name" : "Model development", "level" : "intermediate" }, { "name" : "Model validation", "level" : "intermediate" }, { "name" : "Model implementation", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Critical thinking" }, { "name" : "Effective communication" } ], "majorSkills" : "Reinforcement Learning, Optimization, Machine Learning, Deep Learning", "majorSkillsList" : [ "Reinforcement Learning", "Optimization", "Machine Learning", "Deep Learning" ], "coreResponsibilities" : "Conduct research into theory and application of deep, Propose and deploy solutions, Develop and implement novel, scalable algorithms, Develop and implement modeling techniques, Tackle challenging, groundbreaking research problems, Develop novel RL algorithms, Apply RL algorithms to complex, real-world challenges, Develop scalable, efficient, automated processes for data analyses, Develop scalable, efficient, automated processes for model development, Develop scalable, efficient, automated processes for model validation, Develop scalable, efficient, automated processes for model implementation, Design, development and evaluation of highly innovative ML, Research and apply the latest ML techniques, Research and apply the latest ML best practices, Think about customers, Improve the customer delivery experience, Use analytical techniques to create scalable solutions", "teamCollaboration" : "Work with product managers; Work with scientists; Work with software engineers; Work alongside global experts; Work collaboratively with diverse groups; Work with cross-functional teams", "domainKnowledge" : "Reinforcement Learning; Optimization; Machine Learning; Bayesian optimization; Time series; Multi-armed bandits; Supervised learning; Semi-supervised learning; Unsupervised learning; Advanced statistical modeling; Graph models; Deep learning; Predictive modeling; Large Language Models", "domainList" : [ "reinforcement-learning", "optimization", "machine-learning", "bayesian-optimization", "time-series", "multi-armed-bandits", "supervised-learning", "semi-supervised-learning", "unsupervised-learning", "advanced-statistical-modeling", "graph-models", "deep-learning", "predictive-modeling", "large-language-models" ], "domainSpecificKnowledge" : [ "Reinforcement Learning", "Optimization", "Machine Learning", "Bayesian optimization", "Time series", "Multi-armed bandits", "Supervised learning", "Semi-supervised learning", "Unsupervised learning", "Advanced statistical modeling", "Graph models", "Deep learning", "Predictive modeling", "Large Language Models" ], "communicationSkills" : "Communicate effectively", "continuousLearning" : "Learn; Grow", "innovationCreativity" : "Boundary-pushing; Revolutionary theory; Awe-inspiring reality; Innovation; Bold ideas", "problemSolvingSkills" : "Solve complex business problems; Solve complex business problems", "outcomesObjectives" : "Advance the state-of-the-art; Shape the future of AI; Propel humanity forward; Leave an indelible mark on the world of technology", "qualificationsBasic" : "Enrolled in a PhD, 18 years of age or older, Work 40 hours/week minimum, Commit to 12 week internship maximum, Can relocate to where the internship is based, Experience programming in Java, C++, Python or related language, Experience with Optimization, Experience with Programming/Scripting Languages, Experience with Statistics, Experience with Reinforcement Learning, Experience with Causal Inference, Experience with Large Language Models, Experience with Time Series, Experience with Graph Modeling, Experience with Supervised/Unsupervised Learning, Experience with Deep Learning, Experience with Predictive Modeling", "qualificationsPreferred" : "Publications at top-tier peer-reviewed conferences or journals, Experience in state-of-the-art deep learning models architecture design, Deep learning training and optimization experience, Model pruning experience", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Unlock the Future with Amazon Science! Calling all visionary minds passionate about the transformative power of machine learning! Amazon is seeking boundary-pushing graduate student scientists who can turn revolutionary theory into awe-inspiring reality. Join our team of visionary scientists and embark on a journey to revolutionize the field by harnessing the power of cutting-edge techniques in bayesian optimization, time series, multi-armed bandits and more. At Amazon, we don't just talk about innovation – we live and breathe it. You'll conducting research into the theory and application of deep reinforcement learning. You will work on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. You will propose and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA. Key job responsibilities We are particularly interested in candidates with expertise in: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of Reinforcement Learning and Optimization within Machine Learning. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on developing novel RL algorithms and applying them to complex, real-world challenges. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. A day in the life - Develop scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Design, development and evaluation of highly innovative ML models for solving complex business problems. - Research and apply the latest ML techniques and best practices from both academia and industry. - Think about customers and how to improve the customer delivery experience. - Use and analytical techniques to create scalable solutions for business problems. Basic Qualifications: - Are enrolled in a PhD - Are 18 years of age or older - Work 40 hours/week minimum and commit to 12 week internship maximum - Can relocate to where the internship is based - Experience programming in Java, C++, Python or related language - Experience with one or more of the following: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling Preferred Qualifications: - Have publications at top-tier peer-reviewed conferences or journals - Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $65.38/hr in our lowest geographic market up to $107.40/hr in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "2026 Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) at Amazon.com Services LLC. Skills: Reinforcement Learning, Optimization, Machine Learning, Deep Learning. Conduct research into theory and application of deep. 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MCP Protocol; Cloud-native architecture", "domainList" : [ "agentic-layer", "mcp-protocol", "cloud-native-architecture" ], "domainSpecificKnowledge" : [ "Agentic Layer", "MCP Protocol", "Cloud-native architecture" ], "toolProficiency" : [ "Azure AI Search", "Redis", "Cosmos DB", "Azure Functions", "Azure Container Apps" ], "qualificationsBasic" : "8+ Years of experience, Hands-on experience with Agentic Layer A2A frameworks, Hands-on experience with MCP Protocol, AI/ML engineering expertise, Vector embeddings expertise, Prompt engineering expertise, Context engineering expertise, Programming skills in Python, Java, or Go, Proficiency in deploying solutions on Azure Cloud, Experience with Azure AI Search, Experience with Redis, Experience with Cosmos DB, Ability to design Azure Functions, Ability to manage Azure Functions, Ability to design Azure Container Apps, Ability to manage Azure Container Apps, Understanding of cloud-native architecture, Understanding of scalability, Understanding of performance optimization, 12+ years Data Science, 6+ years AI/ML engineering, 6+ years programming skills, 6+ years databases, 6+ years Azure Functions and Azure Container Apps", "qualificationsPreferred" : "Blob Storage experience a plus, Iceberg experience a plus", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We provide Recruitment and Staffing services to many industries and domain through our innovative and customized solutions and passionate commitment to research. Ability to understand the hiring strategies, availability of talent and compensation benchmarking makes us proud hiring partner for various industries. We work as trusted business partners and always strive to deliver the most value and highest return on investment for our clients. We are highly trained business professionals with strong understanding of clients need. We work closely with the leading staffing trade associations, training, and research organizations to ensure we are knowledgeable of the latest industry trends and technologies. Client is looking for 8+ Years of experienced Hands-on experience with Agentic Layer A2A frameworks and MCP Protocol. Expertise in AI/ML engineering, specifically vector embeddings, prompt engineering, and context engineering. Strong programming skills in at least two of the following: Python, Java, Go. Proficiency in deploying solutions on Azure Cloud. Experience with databases such as Azure AI Search, Redis, and Cosmos DB (Blob Storage and Iceberg are plus). Proven ability to design and manage Azure Functions and Azure Container Apps. Strong understanding of cloud-native architecture, scalability, and performance optimization. Must Have Skills: Skill 1 – Yrs of Exp – 12+ - Data Science - Agentic Layer A2A frameworks and MCP Protocol Skill 2 - Yrs of Exp – 6+ - AI/ML engineering, specifically vector embeddings, prompt engineering, and context engineering SKill 3 - Yrs Of Exp - 6+ - programming skills in at least two of the following: Python, Java, Go. Proficiency in deploying solutions on Azure Cloud SKill 4 - Yrs Of Exp - 6+ - databases such as Azure AI Search, Redis, and Cosmos DB (Blob Storage and Iceberg are plus) Skill 5 - Yrs of Exp - 6+ - ability to design and manage Azure Functions and Azure Container Apps & cloud-native architecture, scalability, and performance optimization. Regards, Mohammed ilyas, PH - 229-264-4024 or Text - 229-469-1455 or You can share the updated resume at Mohammed@vtekis. com ## Additional Information All your information will be kept confidential according to EEO guidelines.", "summaryDescription" : "Data Science at Syncreon Consulting. Skills: Agentic AI, AI/ML engineering, Azure Cloud. Understand hiring strategies. Understand talent availability", "postedDate" : "2026-06-15T14:52:48.000", "createdAt" : "2026-06-16T01:42:05.034", "lastUpdated" : "2026-06-16T11:54:21.385", "ingestTimestamp" : "2026-06-16T01:42:05.034", "mongoId" : "6a308a5df292fd229c0960c7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 155000, "salaryAnnualMax" : 215000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data Science", "AI/ML engineering", "Programming", "Cloud deployment", "Database management", "Cloud-native architecture", "Agentic AI", "Azure Cloud", "Agentic Layer", "MCP Protocol", "Azure AI Search", "Redis", "Cosmos DB", "Azure Functions", "Azure Container Apps" ], "skillCount" : 15, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a30592df292fd229cf458d6", "title" : "Data Science", "company" : "Syncreon Consulting", "industry" : "Computer And Network Security", "salary" : { "min" : 155000.0, "max" : 210000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "The estimation is based on the market baseline for a Senior Data Scientist in Los Angeles, with adjustments for the technology industry and contract employment type." }, "location" : "Los Angeles, CA, United States", "locations" : [ "Los Angeles", "CA", "United States" ], "timestamp" : "2026-06-16T07:25:21.403", "fingerprint" : "9094f61c3263137a24a7caf6d5579375deb6ca0b1231429c973f94ad45db7d8d", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/SyncreonConsulting/744000132219904-data-science-agentic-ai-", "externalId" : "744000132219904", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Los Angeles", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "34.0536909,-118.2427660" } ], "locationText" : "Los Angeles, California, United States", "employmentType" : "CONTRACT", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "entry", "technicalSkills" : "MCP Protocol, Python, Java, Go, Azure Cloud, Azure AI Search, Redis, Cosmos DB, Blob Storage, Iceberg, Azure Functions, Azure Container Apps", "professionalSkills" : [ "AI/ML engineering", "Prompt engineering", "Context engineering", "Cloud-native architecture", "Performance optimization" ], "hardSkillsList" : [ "Vector embeddings", "Scalability" ], "hardSkills" : [ { "name" : "Vector embeddings", "level" : "intermediate" }, { "name" : "Scalability", "level" : "intermediate" } ], "majorSkills" : "Agentic AI, AI/ML engineering, Azure Cloud", "majorSkillsList" : [ "Agentic AI", "AI/ML engineering", "Azure Cloud" ], "coreResponsibilities" : "Understand hiring strategies, Understand talent availability, Understand compensation benchmarking, Deliver value to clients, Deliver highest return on investment, Work closely with staffing trade associations, Work with training organizations, Work with research organizations, Design Azure Functions, Manage Azure Functions, Design Azure Container Apps, Manage Azure Container Apps", "domainKnowledge" : "Agentic Layer; MCP Protocol; Vector embeddings; Prompt engineering; Context engineering; Cloud-native architecture", "domainList" : [ "agentic-layer", "mcp-protocol", "vector-embeddings", "prompt-engineering", "context-engineering", "cloud-native-architecture" ], "domainSpecificKnowledge" : [ "Agentic Layer", "MCP Protocol", "Vector embeddings", "Prompt engineering", "Context engineering", "Cloud-native architecture" ], "toolProficiency" : [ "Azure Functions", "Azure Container Apps" ], "qualificationsBasic" : "8+ Years of experience, Hands-on experience with Agentic Layer A2A frameworks, Hands-on experience with MCP Protocol, AI/ML engineering expertise, Vector embeddings expertise, Prompt engineering expertise, Context engineering expertise, Programming skills in at least two of Python, Java, Go, Proficiency in deploying solutions on Azure Cloud, Experience with Azure AI Search, Experience with Redis, Experience with Cosmos DB, Ability to design Azure Functions, Ability to manage Azure Functions, Ability to design Azure Container Apps, Ability to manage Azure Container Apps, Understanding of cloud-native architecture, Understanding of scalability, Understanding of performance optimization, 12+ Yrs of Exp - Data Science, 6+ Yrs of Exp - AI/ML engineering, 6+ Yrs of Exp - programming skills, 6+ Yrs of Exp - databases, 6+ Yrs of Exp - Azure Functions and Azure Container Apps", "qualificationsPreferred" : "Blob Storage experience a plus, Iceberg experience a plus", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We provide Recruitment and Staffing services to many industries and domain through our innovative and customized solutions and passionate commitment to research. Ability to understand the hiring strategies, availability of talent and compensation benchmarking makes us proud hiring partner for various industries. We work as trusted business partners and always strive to deliver the most value and highest return on investment for our clients. We are highly trained business professionals with strong understanding of clients need. We work closely with the leading staffing trade associations, training, and research organizations to ensure we are knowledgeable of the latest industry trends and technologies. Client is looking for 8+ Years of experienced Hands-on experience with Agentic Layer A2A frameworks and MCP Protocol. Expertise in AI/ML engineering, specifically vector embeddings, prompt engineering, and context engineering. Strong programming skills in at least two of the following: Python, Java, Go. Proficiency in deploying solutions on Azure Cloud. Experience with databases such as Azure AI Search, Redis, and Cosmos DB (Blob Storage and Iceberg are plus). Proven ability to design and manage Azure Functions and Azure Container Apps. Strong understanding of cloud-native architecture, scalability, and performance optimization. Must Have Skills: Skill 1 – Yrs of Exp – 12+ - Data Science - Agentic Layer A2A frameworks and MCP Protocol Skill 2 - Yrs of Exp – 6+ - AI/ML engineering, specifically vector embeddings, prompt engineering, and context engineering SKill 3 - Yrs Of Exp - 6+ - programming skills in at least two of the following: Python, Java, Go. Proficiency in deploying solutions on Azure Cloud SKill 4 - Yrs Of Exp - 6+ - databases such as Azure AI Search, Redis, and Cosmos DB (Blob Storage and Iceberg are plus) Skill 5 - Yrs of Exp - 6+ - ability to design and manage Azure Functions and Azure Container Apps & cloud-native architecture, scalability, and performance optimization. Regards, Mohammed ilyas, PH - 229-264-4024 or Text - 229-469-1455 or You can share the updated resume at Mohammed@vtekis. com ## Additional Information All your information will be kept confidential according to EEO guidelines.", "summaryDescription" : "Data Science at Syncreon Consulting. Skills: Agentic AI, AI/ML engineering, Azure Cloud. Understand hiring strategies. Understand talent availability", "postedDate" : "2026-06-15T14:52:48.000", "createdAt" : "2026-06-15T23:46:49.654", "lastUpdated" : "2026-06-16T07:25:21.403", "ingestTimestamp" : "2026-06-15T23:46:49.654", "mongoId" : "6a30592df292fd229cf458d6", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 155000, "salaryAnnualMax" : 210000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Vector embeddings", "Scalability", "Agentic AI", "AI/ML engineering", "Azure Cloud", "Prompt engineering", "Context engineering", "Cloud-native architecture", "Performance optimization", "Agentic Layer", "MCP Protocol", "Azure Functions", "Azure Container Apps" ], "skillCount" : 13, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "693072a870f0b99d58ffb89e", "title" : "Manager, Applied Science", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, Advertising", "salary" : { "min" : 165500.0, "max" : 286000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "timestamp" : "2026-06-14T22:25:38.660", "fingerprint" : "41996b45728078aa7837cd5bb08b7ac82d2309c8b7ce77292bcbf0914d4a861e", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3134438/apply", "externalId" : "88834260-daba-4391-8156-07af69d9291a", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "Machine Learning, Natural Language Processing, Reinforcement Learning, Deep Learning, Large Language Models, Generative Artificial Intelligence, Information Retrieval, Analytics", "professionalSkills" : [ "Science leadership", "Organizational ability", "Technical strength", "Product focus", "Business understanding" ], "hardSkillsList" : [ "Applied science", "Model implementation", "AI/ML services" ], "softSkillsList" : [ "Leadership", "Mentorship" ], "hardSkills" : [ { "name" : "Applied science", "level" : "intermediate" }, { "name" : "Model implementation", "level" : "intermediate" }, { "name" : "AI/ML services", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentorship" } ], "majorSkills" : "Generative AI, Large Language Models, Applied Science", "majorSkillsList" : [ "Generative AI", "Large Language Models", "Applied Science" ], "coreResponsibilities" : "Drive end-to-end applied science projects, Provide technical/science leadership, Research new AI approaches, Recruit Applied Scientists, Provide mentorship, Establish team mechanisms, Build AI models in production, Write vision documents, Build scalable team mechanisms, Define scientific vision, Translate direction into plans", "teamCollaboration" : "Collaborative team environment; Scientists and software engineers", "domainKnowledge" : "Advertising; B2B Sales; Sales AI; Sales intelligence models; Advertiser insights; Foundational Model post-training; Continual pre-training; Fine-tuning; Reinforcement learning techniques", "domainList" : [ "advertising", "b2b-sales", "sales-ai", "sales-intelligence-models", "advertiser-insights", "foundational-model-post-training", "continual-pre-training", "fine-tuning", "reinforcement-learning-techniques" ], "domainSpecificKnowledge" : [ "Advertising", "B2B Sales", "Sales AI", "Sales intelligence models", "Advertiser insights", "Foundational Model post-training", "Continual pre-training", "Fine-tuning", "Reinforcement learning techniques" ], "communicationSkills" : "Explain complex technical approaches; Convey complex technical concepts", "documentationSkills" : "Write vision documents", "continuousLearning" : "Knowledge-sharing; Mentorship", "innovationCreativity" : "Innovative thinking; Creativity; Invent new experiences", "qualificationsBasic" : "3+ years management experience, Knowledge of ML, NLP, Information Retrieval, Ph.D. or Master's degree, 5 years relevant experience (Ph.D.), 10 years relevant experience (Master's), 2+ years LLM/Foundational Model experience, Scientific publication track record", "qualificationsPreferred" : "Experience building ML models, Experience developing algorithms for business, Delivering scalable ML/NLP/Gen AI solutions, Building conversational experiences, Building AI agents, Clear communication of complex technical concepts", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you interested in shaping the future of Advertising and B2B Sales through Generative AI solutions? We are a growing science and engineering team with an exciting charter and need your passion, innovative thinking, and creativity to help take our products to new heights. Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Within the Advertising Sales organization, we are building a central AI/ML team and are seeking a top science leader to build new, Generative AI powered services that will transform the way account teams operate. This includes building autonomously orchestrated AI Agents that directly connect with advertisers, as well as core AI services that augment internal products with improved embeddings, fine-tuned LLMs and custom guardrails. As a part of our team, you will bring deep expertise in Natural Language Processing (NLP), Reinforcement Learning (RL), Deep Learning (DL), Large Language Models (LLM) and/or Generative Artificial Intelligence to build and refine models that can be implemented in production. You will be a thought leader as we chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders, leaders and customers. We are seeking a true owner who can provide science leadership, establish a vision and charter for the team, foster a collaborative and innovative team environment, and manage a team of scientists and software engineers to drive long-term success. You can build a team, launch AI models in production, write vision documents and build scalable team mechanisms. Impact and Career Growth: You will invent new experiences and influence customer-facing AI experiences; this is your opportunity to work within the fastest growing businesses across all of Amazon with visibility to senior leadership and an opportunity to grow quickly! Define a long-term scientific vision for our advertising sales business, driven from our customers' needs, translating that direction into specific plans for scientists, engineers and product teams. This role combines scientific leadership, organizational ability, technical strength, product focus, and business understanding. We’re also 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. Key job responsibilities - Drive end-to-end applied science projects that have a high degree of ambiguity, scale and complexity - Provide technical / science leadership related to Large Language Models, Natural Language Processing (NLP) and Reinforcement Learning (RL) . - Research new and innovative Machine Learning / Artificial Intelligence approaches. - Recruit high performing Applied Scientists to the team and provide mentorship. - Establish team mechanisms, including team building, vision setting, planning, and document reviews. About the team Sales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows. Basic Qualifications: - 3+ years of scientists or machine learning engineers management experience - Knowledge of ML, NLP, Information Retrieval and Analytics - Ph.D. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, Reinforcement Learning, Mathematics, or a related field plus 5 years of relevant experience, or Master’s degree plus 10 years of relevant work experience - 2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques. - Scientific publication track record at top-tier AI/ML/NLP conferences or journals Preferred Qualifications: - Experience building machine learning models or developing algorithms for business application - Proven track record of delivering scalable and high-quality ML/ NLP / Gen AI solutions (models and infrastructure) to customers and experience with building conversational experiences and AI agents. - Strong communication skills with the ability to clearly convey complex technical concepts to diverse audiences, including senior leadership. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165,500/year in our lowest geographic market up to $286,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Manager, Applied Science at Amazon.com Services LLC. Skills: Generative AI, Large Language Models, Applied Science. Drive end-to-end applied science projects. Provide technical/science leadership", "postedDate" : "2026-06-13T02:55:50.771", "createdAt" : "2026-06-13T02:55:50.771", "lastUpdated" : "2026-06-14T22:25:38.660", "ingestTimestamp" : "2026-06-13T02:55:50.771", "mongoId" : "693072a870f0b99d58ffb89e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3134438/apply", "salaryAnnualMin" : 165500, "salaryAnnualMax" : 286000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Applied science", "Model implementation", "AI/ML services", "Leadership", "Mentorship", "Generative AI", "Large Language Models", "Applied Science", "Science leadership", "Organizational ability", "Technical strength", "Product focus", "Business understanding", "Advertising", "B2B Sales", "Sales AI", "Sales intelligence models", "Advertiser insights", "Foundational Model post-training", "Continual pre-training", "Fine-tuning", "Reinforcement learning techniques" ], "skillCount" : 22, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Advertising" }, { "id" : "693072a470f0b99d58ffb649", "title" : "Applied Science Manager, Fire TV Science", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, alexa and amazon devices", "salary" : { "min" : 165500.0, "max" : 286000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Sunnyvale, California, USA", "locations" : [ "Sunnyvale, California, USA" ], "timestamp" : "2026-06-15T02:35:12.995", "fingerprint" : "89266b20fc421fab056a5e5309323026968eb6f3937e1c1a61593f6734a687f5", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3136037/apply", "externalId" : "ffb34a9f-a40d-4ccf-8794-64a96127f391", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Sunnyvale", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.3688301,-122.0363490" } ], "locationText" : "Sunnyvale, California, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "ML, NLP, Information Retrieval, GenAI", "professionalSkills" : [ "Query understanding", "Content discovery", "Customer engagement", "Applied projects", "Production support", "Prompt engineering", "Personalization models" ], "hardSkillsList" : [ "Model evaluation", "Algorithm development", "Scalable solutions" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Model evaluation", "level" : "intermediate" }, { "name" : "Algorithm development", "level" : "intermediate" }, { "name" : "Scalable solutions", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Language Understanding, Machine Learning, Recommender Systems", "majorSkillsList" : [ "Language Understanding", "Machine Learning", "Recommender Systems" ], "coreResponsibilities" : "Lead Language Understanding sub-team, Own query understanding components, Own query understanding models, Lead a team of scientists, Mentor scientists, Foster professional development, Foster technical growth, Establish research vision, Execute research vision, Collaborate with Search workstreams, Collaborate with Recommendations workstreams, Contribute to cross-functional initiatives, Expand technical influence, Design scalable solutions, Address technical challenges, Deliver customer benefit, Balance workstreams, Prioritize workstreams, Drive adoption of approaches, Stay at forefront of advances, Conduct model evaluations, Review model evaluations, Interface with Alexa team, Resolve domain conflicts, Brainstorm with leads, Explore synergies, Prototype query understanding approaches, Prioritize production issues, Engage with engineering partners, Engage with product partners, Challenge the status quo, Identify automation opportunities, Stay current with NLU research", "teamCollaboration" : "Cross-functional initiatives; Search workstreams; Recommendations workstreams; Engineering partners; Product partners; Alexa central team", "projectManagementSkills" : [ "Prioritize workstreams", "Balance workstreams" ], "domainKnowledge" : "Language Understanding; Recommender Systems; Information Retrieval; Machine Learning; NLU research", "domainList" : [ "language-understanding", "recommender-systems", "information-retrieval", "machine-learning", "nlu-research" ], "domainSpecificKnowledge" : [ "Language Understanding", "Recommender Systems", "Information Retrieval", "Machine Learning", "NLU research" ], "communicationSkills" : "Written communication; Verbal communication", "continuousLearning" : "Stay current with NLU research", "innovationCreativity" : "Prototype query understanding approaches", "problemSolvingSkills" : "Address technical challenges; Resolve domain conflicts", "specialRequirements" : "Regular travel between sites", "outcomesObjectives" : "Deliver lasting customer benefit; Ensure high-impact outcomes", "qualificationsBasic" : "4+ years management experience, Knowledge of ML, Knowledge of NLP, Knowledge of Information Retrieval, Knowledge of Analytics", "qualificationsPreferred" : "PhD Preferred, Experience building ML models, Experience developing algorithms, Knowledge of deep learning, Knowledge of machine learning, Knowledge of statistics, Experience delivering results, Experience hiring scientists, Experience leading scientists, Experience developing junior members, Experience communicating complex concepts, Experience leveraging GenAI techniques, Experience leveraging GenAI models", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Help re-invent how millions of people watch TV! Fire TV remains the #1 best-selling streaming media player in the US, with over 100 million active users. Our goal is to be the global leader in delivering entertainment, with the broadest selection of content, innovative devices, and personalized experiences for customers. Our Fire TV Science team is an interdisciplinary group working at the intersection of Language Understanding (LU), Recommender Systems, Information Retrieval, and Machine Learning (ML). Through close collaboration with engineering and product teams, we develop and deploy innovative algorithms that enhance content discovery and customer engagement. Within this team, our Language Understanding sub-team owns all query understanding components and models that power search and content discovery on Fire TV. Our work directly contributes to making our devices delightful to use and indispensable for the household. Key job responsibilities - Be a hands-on lead for our Language Understanding (LU) sub-team, owning all our query understanding components and models - Lead and mentor a team of 6 scientists, fostering their professional development and technical growth while establishing and executing the research vision - Collaborate closely with Search and Recommendations workstreams within the broader Fire TV Science team, contributing to cross-functional initiatives and expanding technical influence beyond the LU domain - Drive end-to-end impact by designing scalable solutions that systematically address technical challenges and deliver lasting customer benefit - Balance and prioritize multiple workstreams spanning long-term research, applied projects, and production support to ensure high-impact outcomes - Drive adoption of state-of-the-art approaches across the organization by staying at the forefront of relevant technological advances, spanning language understanding models, LLM evaluations, prompt engineering, search and personalization models, and more A day in the life As the Language Understanding sub-team lead, you'll balance hands-on technical work with team leadership and cross-functional collaboration. Your day might include conducting and reviewing model evaluations, interfacing with the Alexa central team on LLM routing and architectural design questions, resolving domain conflicts, and brainstorming with Search and Recommendations leads to explore synergies. You'll dive into code to prototype novel query understanding approaches, prioritize production issues, and engage with engineering and product partners on upcoming features. Throughout, you'll challenge the status quo, identify automation opportunities to free time for higher-impact work, and stay current with NLU research. The role involves regular travel between our two sites. Basic Qualifications: - 4+ years of scientists or machine learning engineers management experience - Knowledge of ML, NLP, Information Retrieval and Analytics - PhD Preferred Qualifications: - Experience building machine learning models or developing algorithms for business application - Knowledge of deep learning, machine learning and statistics - Experience delivering results for large, cross-functional initiatives/projects - Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track - Experience effectively communicating complex concepts through written and verbal communication - Experience leveraging GenAI techniques and models to solve technical business problems Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165,500/year in our lowest geographic market up to $286,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Applied Science Manager, Fire TV Science at Amazon.com Services LLC. Skills: Language Understanding, Machine Learning, Recommender Systems. Lead Language Understanding sub-team. Own query understanding components", "postedDate" : "2026-06-13T06:20:24.744", "createdAt" : "2026-06-13T06:20:24.744", "lastUpdated" : "2026-06-15T02:35:12.995", "ingestTimestamp" : "2026-06-13T06:20:24.744", "mongoId" : "693072a470f0b99d58ffb649", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3136037/apply", "salaryAnnualMin" : 165500, "salaryAnnualMax" : 286000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Model evaluation", "Algorithm development", "Scalable solutions", "Leadership", "Mentoring", "Language Understanding", "Machine Learning", "Recommender Systems", "Query understanding", "Content discovery", "Customer engagement", "Applied projects", "Production support", "Prompt engineering", "Personalization models", "Prioritize workstreams", "Balance workstreams", "Information Retrieval", "NLU research" ], "skillCount" : 19, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "69cf3f042beec4dd3d933fff", "title" : "Sr. Applied Science Manager", "company" : "Amazon.com Services LLC", "industry" : "Applied Science, Artificial Intelligence", "salary" : { "min" : 218000.0, "max" : 295900.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T06:21:21.433", "fingerprint" : "3d98f3f5e95431c99222e3cb55a1dd941260f202bad976a601f0d79ab90903c1", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10382644/apply", "externalId" : "8d65e720-8c46-40ff-9d1a-471ead711e3d", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "Machine Learning, AI, LLMs, RAG", "professionalSkills" : [ "Scientific roadmap", "ML systems", "Business requirements", "Technical deliverables", "ML frameworks", "Research plans", "Scientific rigor", "Business objectives" ], "hardSkillsList" : [ "Model performance", "Model scalability", "Experimentation", "A/B testing", "Data-driven decision making" ], "softSkillsList" : [ "Leadership", "Mentorship" ], "hardSkills" : [ { "name" : "Model performance", "level" : "intermediate" }, { "name" : "Model scalability", "level" : "intermediate" }, { "name" : "Experimentation", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Data-driven decision making", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentorship" } ], "majorSkills" : "Artificial intelligence, Machine learning, Natural language processing", "majorSkillsList" : [ "Artificial intelligence", "Machine learning", "Natural language processing" ], "coreResponsibilities" : "Lead and manage teams, Provide mentorship, Provide career development, Provide performance management, Define technical roadmap, Execute technical roadmap, Work with new technologies, Work with new methodologies, Translate business requirements, Deliver stable solutions, Participate in development cycle, Evaluate ML frameworks, Make strategic decisions, Collaborate with engineers, Collaborate with scientists, Define architecture, Define research plans, Drive scientific rigor, Partner with cross-functional teams, Align science initiatives, Publish research findings, Represent Amazon at conferences, Establish best practices, Improve model evaluation, Improve model monitoring, Improve continuous improvement", "teamCollaboration" : "Cross-functional teams; Science and engineering teams; Business stakeholders", "domainKnowledge" : "Artificial intelligence; Machine learning; Natural language processing; Large language models; RAG techniques", "domainList" : [ "artificial-intelligence", "machine-learning", "natural-language-processing", "large-language-models", "rag-techniques" ], "domainSpecificKnowledge" : [ "Artificial intelligence", "Machine learning", "Natural language processing", "Large language models", "RAG techniques" ], "toolProficiency" : [ "ML frameworks" ], "communicationSkills" : "Publish research findings; Represent Amazon", "innovationCreativity" : "AI innovation; Machine learning innovation", "problemSolvingSkills" : "Data-driven decision making", "outcomesObjectives" : "Improve information-driven experience", "qualificationsBasic" : "10+ years building ML/AI solutions, Master's degree in Computer Science, Experience distilling informal customer requirements, Experience hiring and leading scientists", "qualificationsPreferred" : "PhD in Computer Science, Experience with machine learning technologies, Experience with Reinforcement Learning, Experience with Deep Learning, Experience with Computer Vision, Experience with Natural Language Processing, 10+ years applying ML to complex problems, 5+ years people management experience, Experience leading teams of five or more scientists", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The AGI Information organization is at the forefront of artificial intelligence and machine learning innovation, developing AI systems used across AWS, Alexa, and other Amazon businesses that transform how customers interact with information, in particular integrating a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques). Our team combines world-class research with production-scale engineering to deliver impactful AI-driven products and services. We're looking for an experienced leader who can drive scientific excellence while building and mentoring high-performing teams of applied scientists and machine learning engineers. If you are deeply familiar with LLMs, natural language processing, and machine learning and have experience managing high-performing research teams, this may be the right opportunity for you. Our fast-paced environment requires a high degree of independence in making decisions and driving ambitious research agendas all the way to production. You will work with other science and engineering teams as well as business stakeholders to maximize velocity and impact of your team's contributions. It's an exciting time to be a leader in AI research. In Amazon's AGI Information team, you can make your mark by improving information-driven experience of Amazon customers worldwide! Key job responsibilities * Lead and manage teams of applied scientists and machine learning engineers, providing mentorship, career development, and performance management * Define and execute the technical roadmap for applied science initiatives, balancing innovation with business impact * Work with new technologies and methodologies that improve model performance, usability, and scalability of ML systems * Translate complex business requirements into technical deliverables and deliver operationally stable solutions that provide exceptional customer experiences * Participate in the full development cycle, end-to-end, from research and design to implementation, testing, documentation, delivery, and maintenance * Evaluate and make strategic decisions around the use of new or existing ML frameworks, tools, and technologies * Collaborate with Senior Engineers, Principal Engineers, and Principal Scientists across the organization to define architecture and research plans for the next three years * Drive scientific rigor through experimentation, A/B testing, and data-driven decision making Partner with cross-functional teams including product management, engineering, and business stakeholders to align science initiatives with business objectives * Publish research findings and represent Amazon at top-tier conferences and in the scientific community * Establish best practices for ML development, including model evaluation, monitoring, and continuous improvement Basic Qualifications: - 10+ years of building large-scale machine learning and AI solutions at Internet scale experience - Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent) - Experience building large-scale machine learning and AI solutions at Internet scale - Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives - Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track Preferred Qualifications: - PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent) - Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications - 10+ years of practical work applying ML to solve complex problems for large-scale applications experience - 5+ years of people management experience - Experience leading, mentoring and growing teams of scientists (teams of five or more scientists) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Seattle - 218,800.00 - 295,900.00 USD annually", "summaryDescription" : "Sr. Applied Science Manager at Amazon.com Services LLC. Skills: Artificial intelligence, Machine learning, Natural language processing. Lead and manage teams. Provide mentorship", "postedDate" : "2026-06-13T17:11:48.137", "createdAt" : "2026-06-13T17:11:48.137", "lastUpdated" : "2026-06-15T06:21:21.433", "ingestTimestamp" : "2026-06-13T17:11:48.137", "mongoId" : "69cf3f042beec4dd3d933fff", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10382644/apply", "salaryAnnualMin" : 218000, "salaryAnnualMax" : 295900, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Model performance", "Model scalability", "Experimentation", "A/B testing", "Data-driven decision making", "Leadership", "Mentorship", "Artificial intelligence", "Machine learning", "Natural language processing", "Scientific roadmap", "ML systems", "Business requirements", "Technical deliverables", "ML frameworks", "Research plans", "Scientific rigor", "Business objectives", "Large language models", "RAG techniques" ], "skillCount" : 20, "jobCategory" : "other", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "69fda4e24c40e2acd1b99669", "title" : "Applied Scientist, Pricing Science", "company" : "Amazon.com Services LLC", "industry" : "Applied Science, north america stores", "salary" : { "min" : 142000.0, "max" : 193200.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T04:38:47.952", "fingerprint" : "927e7fc4072ac383bc3da9276c77608e7c06fea0e1c0fabd65b6ad66f8e47a46", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10414298/apply", "externalId" : "96eb5de3-edf1-49fb-a019-3c403fd2d194", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, Java, C++, ML, Causal inference, Econometrics", "professionalSkills" : [ "Pricing experimentation", "Causal identification", "ML pipelines", "Production quality", "Business impact", "Methodology proposals", "Experiment design" ], "hardSkillsList" : [ "CATE estimation", "Model selection", "Evaluation standards", "Offline evaluation", "Simulation analysis" ], "hardSkills" : [ { "name" : "CATE estimation", "level" : "intermediate" }, { "name" : "Model selection", "level" : "intermediate" }, { "name" : "Evaluation standards", "level" : "intermediate" }, { "name" : "Offline evaluation", "level" : "intermediate" }, { "name" : "Simulation analysis", "level" : "intermediate" } ], "majorSkills" : "Causal inference, Machine learning, Pricing science", "majorSkillsList" : [ "Causal inference", "Machine learning", "Pricing science" ], "coreResponsibilities" : "Build causal ML pipelines, Design causal estimation models, Train causal estimation models, Evaluate causal estimation models, Deploy causal estimation models, Own science on heterogeneous treatment effects, Support pricing experiment analysis, Contribute causal analysis methodology, Build reusable tooling for economists, Connect model outputs to business outcomes, Define business metric per model, Deliver model evaluation reports, Evaluate novel techniques, Assess applicability of emerging methods, Write internal methodology proposals, Write internal documentation, Write methodology papers, Make pipelines extensible, Document pipelines for scientists, Collaborate across disciplines, Partner with Sr. Economist, Align with SDE and DE partners, Align with PMs on experiment design", "teamCollaboration" : "Economists; Engineers; Sr. Economist; SDE partners; DE partners; PMs; Experimentation platform team", "domainKnowledge" : "Pricing; Customer lifetime value; Econometrics; ML pipelines; Causal ML; Pricing weblabs; A/B testing; Synthetic DiD; Generalized random forests; Causal representation learning; Competitiveness signal; Inventory signal; Optimization system; Randomization design", "domainList" : [ "pricing", "customer-lifetime-value", "econometrics", "ml-pipelines", "causal-ml", "pricing-weblabs", "a-b-testing", "synthetic-did", "generalized-random-forests", "causal-representation-learning", "competitiveness-signal", "inventory-signal", "optimization-system", "randomization-design" ], "domainSpecificKnowledge" : [ "Pricing", "Customer lifetime value", "Econometrics", "ML pipelines", "Causal ML", "Pricing weblabs", "A/B testing", "Synthetic DiD", "Generalized random forests", "Causal representation learning", "Competitiveness signal", "Inventory signal", "Optimization system", "Randomization design" ], "communicationSkills" : "Methodology papers; Science proposal", "documentationSkills" : "Internal documentation; Methodology papers; Internal write-up", "problemSolvingSkills" : "Optimization anomaly investigation; Trace model input gap; Trace unmodeled dynamic", "outcomesObjectives" : "Changes in LTV estimates; Pricing errors avoided; Economists can use built tools", "qualificationsBasic" : "Master's degree and 4+ years experience, Experience programming in Java, C++, Python, Experience in algorithms and data structures, Experience in parsing, Experience in numerical optimization, Experience in data mining, Experience in parallel and distributed computing, Experience in high-performance computing", "qualificationsPreferred" : "PhD, Experience using Unix/Linux, Experience in professional software development, Usage of generative AI tools, Willingness to learn AI prompting, Ability to recognize AI opportunities", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Pricing is one of the most consequential decisions Amazon makes — and the science behind it needs to be causally rigorous, not just predictive. The P2 Optimization Science (P2OS) team builds the machine learning systems that power Amazon's pricing decisions at scale: demand lift models, customer lifetime value frameworks, and the experimentation infrastructure that validates whether our pricing changes actually work. We're hiring an Applied Scientist to own causal inference at the intersection of ML and pricing experimentation. This role exists because our team has identified a real gap: the methodological bridge between econometric analysis (owned by our economists) and production-scale ML pipelines (owned by our engineers) needs a practitioner who lives in both worlds. You'll build CATE estimation models, design analysis workflows for pricing weblabs, and develop the reusable causal ML infrastructure that the broader team — including non-ML scientists — can rely on. This is not a research role. The bias here is toward shipping production-quality causal pipelines with real downstream business impact. You'll measure success by what changes in LTV estimates, what pricing errors your models help avoid, and whether the economists on your team can actually use what you build. If you're a scientist who wants to work on hard causal identification problems in a high-stakes production environment — and who finds satisfaction in making rigorous methods accessible to a broader team — this role is for you. Key job responsibilities * Build causal ML pipelines for pricing — Design, train, evaluate, and deploy end-to-end causal estimation models for pricing use cases. * Own the science on heterogeneous treatment effects — Be the team SME on causal ML methodology: identification strategies, model selection, evaluation standards, and the tradeoffs between econometric and ML approaches to causal estimation. * Support pricing experiment analysis — Contribute causal analysis methodology to pricing weblab and A/B test post-analysis; build reusable tooling that economists can use without requiring ML expertise * Connect model outputs to business outcomes — Define, before writing code, what business metric each model moves; deliver model evaluation reports framed around pricing errors avoided and LTV estimate changes. * Evaluate and adopt novel techniques — Assess applicability of emerging causal inference methods (synthetic DiD, generalized random forests, causal representation learning) to Amazon's pricing context; write internal methodology proposals for adoption * Write internal documentation and methodology papers — Produce at least one internal write-up per half that connects a causal ML technique to a concrete pricing use case; make pipelines extensible and well-documented so other scientists can build on them. * Collaborate across disciplines — Partner closely with the Sr. Economist on identification strategy and causal assumptions; work with SDE and DE partners on production deployment; align with PMs on experiment design requirements A day in the life As an Applied Scientist on the P2OS team, your work directly shapes the prices customers see on hundreds of millions of Amazon products. In a given workweek, you might: * Investigate an optimization anomaly in simulation and trace it back to a model input gap or an unmodeled market dynamic * Design an offline evaluation framework to benchmark competing optimization approaches before committing to online testing * Collaborate with Sr. Economists on the identification strategy for the model you're building for a pricing lab * Present a science proposal for incorporating a new competitiveness or inventory signal into an optimization system * Work cross-team with the experimentation platform team on randomization design. * Develop and write up a novel scientific finding — preparing a paper or technical report for submission to a top-tier venue such as KDD, NeurIPS, or the ACM Conference on Economics and Computation Basic Qualifications: - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications: - Experience using Unix/Linux - Experience in professional software development - Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices. - Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually", "summaryDescription" : "Applied Scientist, Pricing Science at Amazon.com Services LLC. Skills: Causal inference, Machine learning, Pricing science. Build causal ML pipelines. Design causal estimation models", "postedDate" : "2026-06-13T17:18:07.779", "createdAt" : "2026-06-13T17:18:07.779", "lastUpdated" : "2026-06-15T04:38:47.952", "ingestTimestamp" : "2026-06-13T17:18:07.779", "mongoId" : "69fda4e24c40e2acd1b99669", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10414298/apply", "salaryAnnualMin" : 142000, "salaryAnnualMax" : 193200, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "CATE estimation", "Model selection", "Evaluation standards", "Offline evaluation", "Simulation analysis", "Causal inference", "Machine learning", "Pricing science", "Pricing experimentation", "Causal identification", "ML pipelines", "Production quality", "Business impact", "Methodology proposals", "Experiment design", "Pricing", "Customer lifetime value", "Econometrics", "Causal ML", "Pricing weblabs", "A/B testing", "Synthetic DiD", "Generalized random forests", "Causal representation learning", "Competitiveness signal", "Inventory signal", "Optimization system", "Randomization design" ], "skillCount" : 28, "jobCategory" : "other", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "693c2b9370f0b99d584401e5", "title" : "Sr. Manager, Applied Science, Supply Chain Optimization Technologies", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, operations", "salary" : { "min" : 196900.0, "max" : 340300.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "timestamp" : "2026-06-15T01:54:29.623", "fingerprint" : "5603ce8463899823d3512cccef790ecd6cfd21cf0cdb19f83d89cd5c2e2edc92", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3137353/apply", "externalId" : "34ebdd70-8cfe-4250-8430-4a85efa8057b", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceLevel" : "Manager", "technicalSkills" : "Python, Machine Learning, Reinforcement Learning, Data Processing", "professionalSkills" : [ "Supply Chain Optimization", "Inventory Planning", "Forecasting", "Logistics", "Business Analytics", "Optimization Techniques", "Statistical Modeling" ], "hardSkillsList" : [ "Statistical Machine Learning", "Reinforcement Learning", "Large-scale data processing" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Statistical Machine Learning", "level" : "intermediate" }, { "name" : "Reinforcement Learning", "level" : "intermediate" }, { "name" : "Large-scale data processing", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Machine Learning, Reinforcement Learning, Supply Chain Optimization", "majorSkillsList" : [ "Machine Learning", "Reinforcement Learning", "Supply Chain Optimization" ], "coreResponsibilities" : "Lead technical innovation in RL, Build and develop high-performing team, Foster collaboration, Mentor top talent, Create balanced culture, Bridge technical possibilities with business requirements, Provide strategic judgment, Evaluate technology feasibility, Manage implementation risk, Drive cross-functional collaboration, Interface with product teams, Interface with leadership, Interface with partner organizations, Translate business needs into technical solutions", "teamCollaboration" : "Cross-functional collaboration; Interface with product teams; Interface with partner organizations", "domainKnowledge" : "Supply Chain Optimization; Inventory Planning; Forecasting; Logistics", "domainList" : [ "supply-chain-optimization", "inventory-planning", "forecasting", "logistics" ], "domainSpecificKnowledge" : [ "Supply Chain Optimization", "Inventory Planning", "Forecasting", "Logistics" ], "communicationSkills" : "Verbal communication; Written communication; Presentation skills", "innovationCreativity" : "Drive innovation; Research next generation solutions", "problemSolvingSkills" : "Solving toughest real-world problems", "outcomesObjectives" : "Build world's most efficient supply chain; Run world's most efficient supply chain; Continuously improve supply chain", "qualificationsBasic" : "Ph.D. in Computer Science, Ph.D. in Applied Mathematics, Ph.D. in Statistics, Hands-on ML model building, Hands-on optimization model building, 3+ years managing science team, Expertise in modern Python, Large-scale data processing", "qualificationsPreferred" : "Manage business improvement quantification, Manage analytics improvement quantification, Manage optimization improvement quantification, Manage statistical modeling improvement, Manage senior scientists, Develop junior members, Peer-reviewed scientific contributions, Familiarity with inventory planning, Forecasting knowledge, Planning knowledge, Optimization knowledge, Logistics knowledge, Verbal communication skills, Written communication skills, Presentation skills, Convey mathematical concepts to non-experts, Work effectively in cross-functional team", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you seeking an environment where you can drive innovation? Do you want to be at the forefront of solving the toughest real-world supply chain problems? Do you want to play a key role in the future of Amazon's Stores business? Come and join us! Supply Chain Optimization Technologies (SCOT) owns Amazon's global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon's business goals and to make our customers happy. We decide how to place and move inventory within Amazon's fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars worldwide. Check our website if you are curious to learn more about the breadth of problems we tackle: https://www.amazon.science/tag/supply-chain-optimization-technologies We are seeking a Sr. Manager of Applied Science with expertise in Statistical Machine Learning and/or Reinforcement Learning to drive research, development, and deployment of AI technology that empowers SCOT to build, run, and continuously improve the world's most efficient supply chain. To achieve this goal, we accelerate ML / RL software adoption through our partnerships and infrastructure. In this role, you will manage a team of scientists tasked researching the next generation of solutions to power buying, placement, and fulfillment decisions, while translating customer needs into reusable software infrastructure that accelerates adoption and deployment. Key job responsibilities - Lead technical innovation in reinforcement learning applications for complex supply chain environments, solving unique challenges and ensuring practical implementation in real-world deployments. - Build and develop a high-performing team by fostering collaboration, mentoring top talent, and creating a balanced culture of technical excellence. - Bridge technical possibilities with business requirements by providing strategic judgment, evaluating technology feasibility, and managing implementation risk. - Drive cross-functional collaboration by interfacing with product teams, leadership, and partner organizations to translate business needs into technical solutions. Basic Qualifications: - Ph.D. in Computer Science, Applied Mathematics, Statistics or a closely-related field. - Hands-on experience building machine learning or optimization models in a business environment. - Demonstrated experience managing a science team for three or more years. - Expertise in modern Python with applications of efficient large-scale data processing in complex systems. Preferred Qualifications: - Ability to manage and quantify improvement in multiple business areas resulting from business analytics, optimization techniques, and/or statistical modeling. - Prior experience managing senior scientists as well as a successful record of developing junior members from academia/industry to a successful career track in a business environment. - Significant peer-reviewed scientific contributions in premier journals and conferences. - Familiarity with inventory planning concepts - forecasting, planning, optimization, and logistics - gained through work experience or graduate level education. - Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts. - Proven ability to work effectively in a cross-functional team. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $196,900/year in our lowest geographic market up to $340,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Sr. Manager, Applied Science, Supply Chain Optimization Technologies at Amazon.com Services LLC. Skills: Machine Learning, Reinforcement Learning, Supply Chain Optimization. Lead technical innovation in RL. Build and develop high-performing team", "postedDate" : "2026-06-13T01:52:31.568", "createdAt" : "2026-06-13T01:52:31.568", "lastUpdated" : "2026-06-15T01:54:29.623", "ingestTimestamp" : "2026-06-13T01:52:31.568", "mongoId" : "693c2b9370f0b99d584401e5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3137353/apply", "salaryAnnualMin" : 196900, "salaryAnnualMax" : 340300, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistical Machine Learning", "Reinforcement Learning", "Large-scale data processing", "Leadership", "Mentoring", "Machine Learning", "Supply Chain Optimization", "Inventory Planning", "Forecasting", "Logistics", "Business Analytics", "Optimization Techniques", "Statistical Modeling" ], "skillCount" : 13, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2a660774d8ee00a062b967", "title" : "Applied Science Manager, Personalization", "company" : "Amazon Development Center", "industry" : "Machine Learning Science, Applied Science, Retail", "salary" : { "min" : 450000.0, "max" : 700000.0, "currency" : "ILS", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Applied Science Manager in E-Commerce in Haifa, Israel, adjusted for manager seniority and Amazon's company size." }, "location" : "Haifa, Haifa, ISR", "locations" : [ "Haifa, Haifa, ISR" ], "timestamp" : "2026-06-15T03:05:05.373", "fingerprint" : "0ccaff8498f7e7bcc9a13643e0b83491306584a1d455f520993ce0a55271ce0d", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10442944/apply", "externalId" : "90e6941a-c5af-4e51-8fa5-7aea20d0cbb8", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Haifa", "state" : "Haifa", "country" : "Israel", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "32.8191218,34.9983856" } ], "locationText" : "Haifa, Haifa, Israel", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 3, "experienceLevel" : "Manager", "technicalSkills" : "Large Language Models, Machine learning, Generative AI", "professionalSkills" : [ "Applied research", "Technical vision", "Research agenda" ], "hardSkillsList" : [ "Information Retrieval", "Recommendation Systems", "NLP" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Information Retrieval", "level" : "intermediate" }, { "name" : "Recommendation Systems", "level" : "intermediate" }, { "name" : "NLP", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Large Language Models, Personalization, Applied Science", "majorSkillsList" : [ "Large Language Models", "Personalization", "Applied Science" ], "coreResponsibilities" : "Lead a team of scientists, Set the technical vision, Drive the research agenda, Deliver production-ready solutions, Hire world-class scientists, Mentor world-class scientists, Develop world-class scientists, Foster a culture of innovation, Foster a culture of scientific rigor, Partner closely with engineering teams, Partner closely with product teams, Translate ambitious research into customer-facing impact, Represent your team's work to senior leadership", "teamCollaboration" : "Cross-team collaboration; Engineering teams; Product teams; Senior leadership", "domainKnowledge" : "Information Retrieval; Large Language Models; Recommendation Systems; E-commerce personalization", "domainList" : [ "information-retrieval", "large-language-models", "recommendation-systems", "e-commerce-personalization" ], "domainSpecificKnowledge" : [ "Information Retrieval", "Large Language Models", "Recommendation Systems", "E-commerce personalization" ], "communicationSkills" : "Written communication; Verbal communication", "innovationCreativity" : "Innovation; Scientific rigor", "outcomesObjectives" : "Deliver production-ready solutions; Customer-facing impact", "qualificationsBasic" : "Master's degree, 3+ years scientists or machine learning engineers management experience, 3+ years experience leading teams that build and deploy ML models, Experience leading applied research, Demonstrated ability to think strategically, Demonstrated ability to communicate effectively, Demonstrated ability to drive cross-team collaboration", "qualificationsPreferred" : "PhD or equivalent research experience, Experience with LLM training, fine-tuning, or adaptation, Experience with sequential recommendation, Experience with user intent/mission modeling, Experience with behavioral modeling", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you a scientist interested in pushing the state of the art in Information Retrieval, Large Language Models and Recommendation Systems? Are you interested in innovating on behalf of millions of customers, helping them accomplish their every day goals? Do you wish you had access to large datasets and tremendous computational resources? Do you want to join a team of capable scientist and engineers, building the future of e-commerce? Answer yes to any of these questions, and you will be a great fit for our team at Amazon. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, generative AI, large-scale data systems, and user experience design to deliver the best shopping experiences for our customers. Our team is building next-generation personalization systems powered by Large Language Models. We are tackling novel research challenges to help customers discover products they'll love - at Amazon scale and latency requirements. We are a team uniquely placed within Amazon, to have a direct window of opportunity to influence how customers will think about their shopping journey in the future. As an Applied Science Manager, you will lead a team of scientists working at the frontier of LLM-based personalization. You will set the technical vision, drive the research agenda, and ensure your team delivers production-ready solutions. You will hire, mentor, and develop world-class scientists while fostering a culture of innovation and scientific rigor. You will partner closely with engineering and product teams to translate ambitious research into customer-facing impact, and represent your team's work to senior leadership. Please visit https://www.amazon.science for more information. Basic Qualifications: - PhD or equivalent research experience, or Master's degree - 3+ years of scientists or machine learning engineers management experience - 3+ years of experience leading teams that build and deploy ML models for business applications - Experience leading applied research in one or more of: Recommendation Systems, Information Retrieval, NLP, or Large Language Models - Demonstrated ability to think strategically, communicate effectively (written and verbal) with senior leadership, and drive cross-team collaboration Preferred Qualifications: - Experience with LLM training, fine-tuning, or adaptation (e.g., tokenizer modification, domain adaptation) - Experience with sequential recommendation, user intent/mission modeling, or behavioral modeling 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" : "Applied Science Manager, Personalization at Amazon Development Center. Skills: Large Language Models, Personalization, Applied Science. Lead a team of scientists. Set the technical vision", "postedDate" : "2026-06-13T07:10:33.156", "createdAt" : "2026-06-13T07:10:33.156", "lastUpdated" : "2026-06-15T03:05:05.373", "ingestTimestamp" : "2026-06-13T07:10:33.156", "mongoId" : "6a2a660774d8ee00a062b967", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10442944/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Information Retrieval", "Recommendation Systems", "NLP", "Leadership", "Mentoring", "Large Language Models", "Personalization", "Applied Science", "Applied research", "Technical vision", "Research agenda", "E-commerce personalization" ], "skillCount" : 12, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2c953374d8ee00a098c912", "title" : "Speech-Language Pathologist", "company" : "Ally Behavior Centers", "location" : "Chantilly, Virginia, USA", "locations" : [ "Chantilly", "Virginia", "USA" ], "certifications" : [ "ASHA certification", "BLS", "Speech Therapy licensure" ], "timestamp" : "2026-06-15T08:40:20.570", "fingerprint" : "02c1b0577f7a3d5c69b8c5fa10d503f3dbbb3f8880d4fe67818fdd81a0b532d7", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/allybehaviorcenters/jobs/4115174009", "externalId" : "4115174009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Chantilly", "state" : "Virginia", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite" } ], "locationText" : "Chantilly, Virginia, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Master", "experienceMinYears" : 3, "experienceMaxYears" : 6, "experienceLevel" : "Mid", "technicalSkills" : "Speech Therapy", "professionalSkills" : [ "Applied Behavior Analysis (ABA) therapy, early intervention for children with autism, HIPAA protocol." ], "hardSkillsList" : [ "Speech Therapy", "parent training", "client caseload management", "diaper changing", "toileting assistance" ], "softSkillsList" : [ "energetic, motivated, enthusiasm, patience, calm demeanor" ], "hardSkills" : [ { "name" : "Speech Therapy", "level" : "intermediate" }, { "name" : "parent training", "level" : "intermediate" }, { "name" : "client caseload management", "level" : "intermediate" }, { "name" : "diaper changing", "level" : "intermediate" }, { "name" : "toileting assistance", "level" : "intermediate" } ], "softSkills" : [ { "name" : "energetic, motivated, enthusiasm, patience, calm demeanor" } ], "majorSkills" : "Speech Therapy, ABA therapy, client caseload management, parent training, collaboration", "majorSkillsList" : [ "Speech Therapy, ABA therapy, client caseload management, parent training, collaboration" ], "coreResponsibilities" : "Carry a client caseload of up to 23 clients, complete parent training, meet billable hour expectations, collaborate with OTs and BCBAs, attend team meetings, maintain client confidentiality, and communicate with families and clinical teams.", "teamCollaboration" : "Collaborate with Occupational Therapists and Board Certified Behavior Analysts to coordinate the therapy of shared clients. Performance in team settings & collaboration with others.", "toolProficiency" : [ "HIPAA" ], "communicationSkills" : "Effective communication skills; open communication", "documentationSkills" : "Maintain strict client confidentiality", "continuousLearning" : "In-house CEU's and professional development opportunities. Annual CEU Stipend of $1,000. Commitment to learn and pursue professional development.", "innovationCreativity" : "Creative solutions to problems with the ability to quickly adapt.", "problemSolvingSkills" : "Creative solutions to problems; ability to quickly adapt", "specialRequirements" : "Must submit to a federal, state, and county background check. This position is NOT eligible for Visa sponsorship.", "outcomesObjectives" : "Deliver the highest quality therapy to help early learners reach their potential to communicate, improve social skills, and prepare for academic success. Facilitate collaboration of care and superior treatment outcomes.", "qualificationsBasic" : "Masters Degree from an accredited program in Speech Language Pathology. Current and active Speech Therapy licensure. Meet ASHA certification requirements. Experience with early intervention and working with children with autism. Ability to be on-site 8:30am-5:30pm Monday-Friday. Reliable transportation and valid driver's license. Must pass background check. Ability to sit on the floor, kneel, crawl, squat, run or stand for extended periods. Ability to reach and hold objects. Ability to lift 30 pounds.", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Ally Behavior is a full-time, center-based, early intervention Applied Behavior Analysis (ABA) therapy program, serving children with autism ranging from 18 months to 6 years of age. Our mission is to deliver the highest quality therapy to help our early learners reach their potential to communicate, improve social skills, and prepare for academic success. The children we serve are at the heart of everything we do and we are passionate about our commitment to having a meaningful impact in the lives of our children and their families. What Makes Us Unique: Full-time center-based work with a compensation potential of up to $100,000+ Monthly billable hour bonus eligibility In-house CEU's and professional development opportunities Loan forgiveness and tuition assistance up to $21,000 Guaranteed semi-monthly paycheck, regardless of client cancellations Interdisciplinary teams with Occupational Therapists & Board Certified Behavior Analysts Annual CEU Stipend of $1,000 Job Summary: To facilitate collaboration of care and superior treatment outcomes for our young learners, we currently have an opening for a Speech-Language Pathologist (SLP). Our center-based program delivers intensive early intervention for young children with autism. Each child receives 1-on-1 ABA therapy delivered by a technician and overseen by a Board Certified Behavior Analyst (BCBA) through the day. Most of our learners require Speech Therapy in addition to ABA and Occupational Therapy. We are looking for an energetic, motivated individual to provide high quality Speech Therapy, collaborate with our clinicians on case management, and help our learners maximize their potential. Ally Behavior is a dynamic, fun, and rewarding place to work that offers superior growth and leadership opportunities in a supportive, engaging environment. We have a unique and collaborative culture that is driven by our diverse team of professionals and our core values of Serving Others, Treatment Excellence, All One Ally, Resourceful in Finding Solutions, and Striving to Grow. Our comprehensive onboarding and training approach will support and prepare you to provide the best possible therapy to our clients! Your Day-to-Day Responsibilities: Carry a client caseload of up to 23 clients Complete parent training with each client on their caseload once per quarter Complete a parent training following an evaluation or reevaluation within one month. Meet the billable hour expectations of 40 thirty-minute sessions (20 billable hours) per week Collaborate with Occupational Therapists and Board Certified Behavior Analysts to coordinate the therapy of shared clients Attend team meetings as scheduled Maintain strict client confidentiality following HIPAA protocol Maintain open communication with families and clinical teams to ensure the most effective treatment and goals Due to the nature of working with young children, all clinical staff are required to change diapers, assist with toileting, and be able to physically work on the floor with children Experiential & Certification Requirements: Masters Degree required from a program in Speech Language Pathology which is accredited by the Education Standards Board or whose practice meets ASHA certification requirements Current and active Speech Therapy licensure in the state(s) of hire Meet the education and experience requirements for Certification of Clinical Competence in Speech Language Pathology or Audiology granted by ASHA Current Basic Life Support (BLS) certification Experience with early intervention and working with children with autism Ability to be on-site from 8:30am-5:30pm Monday through Friday required Reliable transportation and a valid driver's license Must submit to a federal, state, and county background check Physical Requirements: Ability to sit on the floor, kneel, crawl, squat, run or stand for extended periods of time Ability to reach and hold objects Ability to lift 30 pounds What You Will Bring: Enthusiasm to make a difference working with young children and their families Ability to maintain a caseload with a weekly billable hour requirement Exceptional ability in building trusting relationships and maintaining confidentiality Commitment to learn and pursue professional development Strong knowledge of SLP principles Strong leadership qualities Demonstration of professionalism and adherence to Ally policy to team members Effective communication skills Multi-tasking & time management Creative solutions to problems with the ability to quickly adapt Patience and calm demeanor in stressful situations Strong performance in team settings & collaboration with others What We Offer When Joining Our Team: Salaried, full-time position Monthly bonus eligibility (on top of base salary) Guaranteed semi-monthly paycheck (24) Company-sponsored DashPass 18 days of paid time off 9 paid holidays (5 set days + 4 \"floating\" holidays) CEU assistance and professional development opportunities Medical +HSA, Dental, and Vision coverage through Cigna Up to $9,000 in post-maternity childcare assistance 401(k) plan with company match. Employee Assistance Program Short Term Disability, Term-Life/AD&D Insurance, Critical Illness with Cancer Insurance, Accident Insurance, Hospital Confinement Insurance, and Pet Insurance Tuition Assistance eligibility at 6-month benchmark Pay Range $80,000—$100,000 USD Note: This position is NOT eligible for Visa sponsorship. Ally Behavior is an equal opportunity employer. In compliance with Federal and State Equal Opportunity Laws, qualified applicants are considered for all positions applied for without regard to race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, veteran status or any other legally protected status. Your personal information will be used for recruitment purposes only and handled in accordance with applicable privacy laws.", "summaryDescription" : "Speech-Language Pathologist at Ally Behavior Centers. Skills: Speech Therapy, ABA therapy, client caseload management, parent training, collaboration. Carry a client caseload of up to 23 clients, complete parent training, meet billable hour expectations, collaborate with OTs and BCBAs, attend team meetings, maintain client confidentiality, and communicate with families and clinical teams.", "postedDate" : "2026-06-14T19:22:46.520", "createdAt" : "2026-06-14T19:22:46.520", "lastUpdated" : "2026-06-15T08:40:20.570", "ingestTimestamp" : "2026-06-14T19:22:46.520", "mongoId" : "6a2c953374d8ee00a098c912", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "hasSalary" : false, "allSkills" : [ "Speech Therapy", "parent training", "client caseload management", "diaper changing", "toileting assistance", "energetic, motivated, enthusiasm, patience, calm demeanor", "Speech Therapy, ABA therapy, client caseload management, parent training, collaboration", "Applied Behavior Analysis (ABA) therapy, early intervention for children with autism, HIPAA protocol.", "ASHA certification", "BLS", "Speech Therapy licensure", "HIPAA" ], "skillCount" : 12, "jobCategory" : "healthcare", "jobSubcategory" : "support", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Healthcare", "llmIndustryConfidence" : 0.98 }, { "id" : "68e0a7e5ce260f92cbf8ec16", "title" : "Senior Applied Scientist - GenAI, Trust and Store Integrity Science", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, selling partner services", "salary" : { "min" : 150400.0, "max" : 260000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-16T00:41:41.871", "fingerprint" : "812fce6710143171a0237eb03108a566e76a586fbccb519340df96fdd2c8bfd0", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3099226/apply", "externalId" : "a7bfded4-fb11-4afe-b58d-9a1baf7e128f", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 6, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, Java, SQL, Machine Learning, Data Modeling, AWS, Distributed Computing, Deep Learning, Large Language Models, GenAI", "professionalSkills" : [ "Data Science", "Data Engineering", "ML/AI", "Business Intelligence", "Analytics Engineering", "Quantitative Analysis" ], "hardSkillsList" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills" ], "hardSkills" : [ { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "ML frameworks", "level" : "intermediate" }, { "name" : "BI platforms", "level" : "intermediate" }, { "name" : "Cloud data stacks", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" } ], "majorSkills" : "GenAI, Machine Learning, Data Science", "majorSkillsList" : [ "GenAI", "Machine Learning", "Data Science" ], "coreResponsibilities" : "Design and implement machine learning models, Develop and deploy scalable ML solutions, Conduct research on GenAI, Analyze large datasets, Build data pipelines, Collaborate with engineering teams, Communicate findings to stakeholders", "teamCollaboration" : "Cross-functional teams; Engineering teams; Stakeholders", "domainKnowledge" : "Trust and Store Integrity", "domainList" : [ "trust-and-store-integrity" ], "domainSpecificKnowledge" : [ "Trust and Store Integrity" ], "qualificationsBasic" : "Master's degree, 6+ years of experience, Proficiency in SQL, Experience with large-scale data analysis, Experience with machine learning, Experience with data modeling, Experience with Python or Java", "qualificationsPreferred" : "PhD in a quantitative field, Experience with AWS, Experience with distributed computing, Experience with deep learning frameworks, Experience with large language models", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Amazon has built a reputation for excellence with recent examples of being named the #1 most trusted company for customers. To deliver on this reputation for trust, Selling Partner Abuse Prevention team is tasked with identifying and preventing abuse for our customers and brand owners worldwide. Selling Partner Fraud and Abuse Prevention is hiring an Applied Scientist who will research and develop innovative machine learning based approaches to predict the near-term future. We are working on advanced research and we support Patent and publishing papers. The Scientist must understand deeply about Machine Learning methods and love extracting, nurturing and transforming high volume of data into actionable business information and making it readily accessible to stakeholders. Key job responsibilities • Lead the research, design, and implementation of innovative AI solutions for selling partner risk assessment and management • Drive the technical vision for applying AI to transform workforce operations in Trust and Store Integrity organization • Develop novel approaches to automate and enhance risk analysis processes using state-of-the-art language models •Partner with business stakeholders to identify high-impact opportunities for AI-driven transformation • Mentor and guide junior scientists while fostering a culture of innovation • Design and implement evaluation frameworks to measure the impact of AI solutions • Ensure responsible AI development with focus on fairness, transparency, and ethical considerations About the team Trust and Store Integrity Science is a new org established in 2024. We are missioned to leverage the fast evolving AI advancements to transform how we prevent bad actors in our stores, across science, engineering, product and program management, and operations. Basic Qualifications: - PhD in computer science, machine learning, engineering, or related fields, or Master's degree - 6+ years of building machine learning models or developing algorithms for business application experience - PhD, or a Master's degree and experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms - Experience building large-scale machine learning and AI solutions at Internet scale - Experience in practical work applying ML to solve complex problems for large scale applications - Experience scripting in modern programming languages, or experience with training and deploying machine learning systems to solve large-scale optimizations Preferred Qualifications: - Experience developing, deploying and managing AI products at scale - PhD, or a Master's degree and experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience working closely with development and business teams to communicate problem impacts and to understand business requirements - Experience across the domain of risk management & fraud Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Senior Applied Scientist - GenAI, Trust and Store Integrity Science at Amazon.com Services LLC. Skills: GenAI, Machine Learning, Data Science. Design and implement machine learning models. Develop and deploy scalable ML solutions", "postedDate" : "2026-06-14T20:30:17.937", "createdAt" : "2026-06-14T20:30:17.937", "lastUpdated" : "2026-06-16T00:41:41.871", "ingestTimestamp" : "2026-06-14T20:30:17.937", "mongoId" : "68e0a7e5ce260f92cbf8ec16", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3099226/apply", "salaryAnnualMin" : 150400, "salaryAnnualMax" : 260000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "GenAI", "Machine Learning", "Data Science", "Data Engineering", "ML/AI", "Business Intelligence", "Analytics Engineering", "Quantitative Analysis", "Trust and Store Integrity" ], "skillCount" : 14, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "69d5e4962beec4dd3d931913", "title" : "Applied Science Manager, Sponsored Products and Brands", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, Advertising", "salary" : { "min" : 183800.0, "max" : 248700.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T02:12:32.742", "fingerprint" : "2813b7088bf9ddc16d6ae80d87886ea77ec3e51c99e1e27ea13f6612f026c856", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10385329/apply", "externalId" : "c8e636df-eba0-4a67-be18-2f67f6c85473", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 4, "experienceLevel" : "Manager", "technicalSkills" : "ML, NLP, Information Retrieval, Java, C++, Python, Deep learning, Machine learning, Computer vision, GenAI, Large language models", "professionalSkills" : [ "Applied research", "Science roadmap", "Product strategy", "Business impact" ], "hardSkillsList" : [ "Prompt generation", "Quality frameworks", "Coverage expansion", "Prompt effectiveness", "CTR improvement", "Helpfulness improvement" ], "hardSkills" : [ { "name" : "Prompt generation", "level" : "intermediate" }, { "name" : "Quality frameworks", "level" : "intermediate" }, { "name" : "Coverage expansion", "level" : "intermediate" }, { "name" : "Prompt effectiveness", "level" : "intermediate" }, { "name" : "CTR improvement", "level" : "intermediate" }, { "name" : "Helpfulness improvement", "level" : "intermediate" } ], "majorSkills" : "NLP, LLMs, Information Retrieval, Applied Science Management", "majorSkillsList" : [ "NLP", "LLMs", "Information Retrieval", "Applied Science Management" ], "coreResponsibilities" : "Lead team of scientists and engineers, Build and scale prompt generation pipeline, Develop new prompt themes, Develop quality frameworks, Drive coverage expansion, Own science roadmap, Define metrics for prompt effectiveness, Drive experimentation to improve CTR, Drive experimentation to improve helpfulness, Drive experimentation to improve advertiser outcomes, Manage and grow science team, Set research direction, Influence product strategy, Translate science investments into business impact", "teamCollaboration" : "Across organizational boundaries; With engineering teams; With product teams; With business teams", "domainKnowledge" : "Conversational Discovery Experiences; Sponsored Prompts; Large language models", "domainList" : [ "conversational-discovery-experiences", "sponsored-prompts", "large-language-models" ], "domainSpecificKnowledge" : [ "Conversational Discovery Experiences", "Sponsored Prompts", "Large language models" ], "innovationCreativity" : "Re-imagining advertising landscape; Generative AI technologies; Re-inventing advertising experiences; Bridging human creativity with AI; Transforming advertising lifecycle; Developing responsible AI technologies", "problemSolvingSkills" : "Solving complex challenges", "outcomesObjectives" : "Improve CTR; Improve helpfulness; Improve advertiser outcomes", "qualificationsBasic" : "4+ years applied research, 3+ years management experience, 3+ years ML models business application, Master's degree and 6+ years research, Knowledge of ML, NLP, IR, Programming in Java, C++, Python", "qualificationsPreferred" : "Experience building complex software systems, Experience with deep learning, Experience with machine learning, Experience with computer vision, Experience with Data & AI technologies, Experience with GenAI, Experience with Analytics, Experience with Database, Experience with Storage", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities We are looking for an Applied Science Manager to lead the Insights & Prompt Generation vertical within the Conversational Discovery Experiences (CAX) team in Sponsored Products and Brands (SPB). This team owns prompt generation, quality, personalization, and coverage for Sponsored Prompts, a new conversational ad format powered by large language models (LLMs) that helps shoppers discover products across Amazon.com. As an Applied Science Manager, you will lead a team of applied scientists and engineers to build and scale the prompt generation pipeline, develop new prompt themes and quality frameworks, and drive coverage expansion across all surfaces. You will own the science roadmap for prompt generation and personalization. You will define the metrics that measure prompt effectiveness and drive experimentation to improve CTR, helpfulness, and advertiser outcomes. This role requires strong technical depth in NLP, LLMs, and information retrieval, combined with the ability to manage and grow a science team, set research direction, and influence product strategy. You will work across organizational boundaries with engineering, product, and business teams to translate science investments into measurable business impact. Basic Qualifications: - 4+ years of applied research experience - 3+ years of scientists or machine learning engineers management experience - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Knowledge of ML, NLP, Information Retrieval and Analytics - Experience programming in Java, C++, Python or related language Preferred Qualifications: - Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers - Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, SEATTLE - 183,800.00 - 248,700.00 USD annually", "summaryDescription" : "Applied Science Manager, Sponsored Products and Brands at Amazon.com Services LLC. Skills: NLP, LLMs, Information Retrieval, Applied Science Management. Lead team of scientists and engineers. Build and scale prompt generation pipeline", "postedDate" : "2026-06-13T17:16:57.553", "createdAt" : "2026-06-13T17:16:57.553", "lastUpdated" : "2026-06-15T02:12:32.742", "ingestTimestamp" : "2026-06-13T17:16:57.553", "mongoId" : "69d5e4962beec4dd3d931913", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10385329/apply", "salaryAnnualMin" : 183800, "salaryAnnualMax" : 248700, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Prompt generation", "Quality frameworks", "Coverage expansion", "Prompt effectiveness", "CTR improvement", "Helpfulness improvement", "NLP", "LLMs", "Information Retrieval", "Applied Science Management", "Applied research", "Science roadmap", "Product strategy", "Business impact", "Conversational Discovery Experiences", "Sponsored Prompts", "Large language models" ], "skillCount" : 17, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "69c94a849bc74574cbbb4dcc", "title" : "Applied Scientist II, Amazon Stores Economics and Science (SEAS)", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, core ai", "salary" : { "min" : 171600.0, "max" : 222200.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Mountain View, California, USA", "locations" : [ "Mountain View, California, USA" ], "timestamp" : "2026-06-15T23:56:48.641", "fingerprint" : "d058b8f5b250fbe85f89433e27f58a9a312caea99bec462f92b80f376879f522", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3197793/apply", "externalId" : "5095914b-9088-44b9-92d6-e91cbe566ace", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Mountain View", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.3893889,-122.0832101" } ], "locationText" : "Mountain View, California, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Master's", "experienceMinYears" : 3, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Python, Java, C++, SQL, Data structures, Algorithms, Object-oriented design, Machine learning, Data mining, Statistical modeling, AWS, GCP, Azure, Spark, Hadoop, Kafka, Airflow, TensorFlow, PyTorch, Scikit-learn, Tableau, Power BI, Looker", "professionalSkills" : [ "Software development", "Data engineering", "ML modeling" ], "hardSkillsList" : [ "Data analysis", "Statistical analysis", "Machine learning algorithms", "Data modeling", "Algorithm design" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "Machine learning algorithms", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Algorithm design", "level" : "intermediate" } ], "majorSkills" : "Machine Learning, Data Science, Data Engineering", "majorSkillsList" : [ "Machine Learning", "Data Science", "Data Engineering" ], "coreResponsibilities" : "Design, develop, and deploy machine learning models, Build and maintain data pipelines, Analyze large datasets to extract insights, Collaborate with product managers and engineers, Develop and implement A/B tests, Communicate findings to stakeholders", "teamCollaboration" : "Product managers; Engineers; Stakeholders", "domainKnowledge" : "E-commerce analytics; Retail science", "domainList" : [ "e-commerce-analytics", "retail-science" ], "domainSpecificKnowledge" : [ "E-commerce analytics", "Retail science" ], "toolProficiency" : [ "Spark", "Hadoop", "Kafka", "Airflow", "TensorFlow", "PyTorch", "Scikit-learn", "Tableau", "Power BI", "Looker" ], "communicationSkills" : "Communicate findings", "problemSolvingSkills" : "Data analysis; Troubleshooting", "qualificationsBasic" : "Master's degree or equivalent practical experience, 3+ years of experience in software development, Experience with data structures, algorithms, and object-oriented design, Experience with at least one general-purpose programming language (e.g., Python, Java, C++), Experience with SQL", "qualificationsPreferred" : "PhD in Computer Science, Machine Learning, or related field, Experience with large-scale distributed systems, Experience with machine learning, data mining, or statistical modeling, Experience with cloud platforms (AWS, GCP, Azure), Experience with data engineering tools and platforms (e.g., Spark, Hadoop, Kafka, Airflow), Experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), Experience with BI tools (e.g., Tableau, Power BI, Looker)", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2024, we are focused on economics and science in areas related to (1) improving delivery speed and lowering cost-to-serve, (2) seller fees and incentives, and (3) emerging machine learning. We also have some ongoing and highly-leveraged collaborations that help partner teams inside Amazon short-circuit months of R&D or otherwise look around corners. We are looking for an Applied Scientist to build and deliver state-of-the-art science and engineering solutions to improve our Stores business. In this role, you will work in a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing and maintaining the scientific models, benchmarks, and services. Graduate education or hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a big plus. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity. Basic Qualifications: - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications: - Experience using Unix/Linux - Experience in professional software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, Mountain View - 171,600.00 - 222,200.00 USD annually USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually", "summaryDescription" : "Applied Scientist II, Amazon Stores Economics and Science (SEAS) at Amazon.com Services LLC. Skills: Machine Learning, Data Science, Data Engineering. Design, develop, and deploy machine learning models. Build and maintain data pipelines", "postedDate" : "2026-06-14T19:21:37.883", "createdAt" : "2026-06-14T19:21:37.883", "lastUpdated" : "2026-06-15T23:56:48.641", "ingestTimestamp" : "2026-06-14T19:21:37.883", "mongoId" : "69c94a849bc74574cbbb4dcc", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3197793/apply", "salaryAnnualMin" : 171600, "salaryAnnualMax" : 222200, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data analysis", "Statistical analysis", "Machine learning algorithms", "Data modeling", "Algorithm design", "Machine Learning", "Data Science", "Data Engineering", "Software development", "Data engineering", "ML modeling", "E-commerce analytics", "Retail science", "Spark", "Hadoop", "Kafka", "Airflow", "TensorFlow", "PyTorch", "Scikit-learn", "Tableau", "Power BI", "Looker" ], "skillCount" : 23, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a307d6ff292fd229c04d3a1", "title" : "Environmental Science Teacher", "company" : "IOTA Community Schools", "industry" : "Primary/Secondary Education", "salary" : { "min" : 53000.0, "max" : 75250.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Memphis, TN, United States", "locations" : [ "Memphis", "TN", "United States" ], "certifications" : [ "Tennessee teaching license", "Out of state license", "Practitioner license" ], "timestamp" : "2026-06-16T13:10:59.094", "fingerprint" : "722e1ef889f740e8cf6db2f968b967b1b9f8cfc933e9c84a12418296f8eeab4d", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/IOTACommunitySchools/3743990013627226-environmental-science-teacher", "externalId" : "3743990013627226", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Memphis", "state" : "Tennessee", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "35.1460260,-90.0517786" } ], "locationText" : "Memphis, Tennessee, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "not-applicable", "professionalSkills" : [ "Curriculum alignment", "Data evaluation" ], "hardSkillsList" : [ "Lesson planning", "Grading", "Student intervention" ], "hardSkills" : [ { "name" : "Lesson planning", "level" : "intermediate" }, { "name" : "Grading", "level" : "intermediate" }, { "name" : "Student intervention", "level" : "intermediate" } ], "majorSkills" : "Environmental Science, Curriculum development, Student engagement", "majorSkillsList" : [ "Environmental Science", "Curriculum development", "Student engagement" ], "coreResponsibilities" : "Attend professional meetings, Attend educational conferences, Attend teacher training workshops, Attend staff meetings, Serve on committees, Instruct students in content area, Demonstrate content knowledge, Use audio-visual aids, Use materials to supplement presentations, Engage student learning, Work as part of interdisciplinary team, Plan curricula, Align curricula, Ensure instruction follows guidelines, Set short-term goals, Set long-term goals, Develop weekly lesson plans, Develop long range lesson plans, Submit weekly lesson plans, Submit long range lesson plans, Assign lessons, Review homework, Evaluate pupil progress, Record pupil progress, Issue reports to parents, Create student intervention plans, Implement student intervention plans, Maintain student management policies, Maintain student management procedures, Report to school administrators, Maintain supervision in classroom, Maintain discipline in classroom, Address student needs, Resolve student needs, Provide accommodations for students, Provide modifications for students, Lead student activities, Participate in student activities, Sponsor student activities, Sponsor student organizations, Coach a sports team, Work with parents, Work with community, Provide morning supervision, Provide after school supervision, Chaperon student activities, Report sexual abuse, Report physical abuse, Report neglect, Perform other duties as assigned", "teamCollaboration" : "Interdisciplinary team; Work with teachers; Work with administrators", "domainKnowledge" : "Environmental Science; Academic content standards; State school requirements", "domainList" : [ "environmental-science", "academic-content-standards", "state-school-requirements" ], "domainSpecificKnowledge" : [ "Environmental Science", "Academic content standards", "State school requirements" ], "communicationSkills" : "Issue reports to parents", "documentationSkills" : "Lesson plan submission; Grade submission", "continuousLearning" : "Teacher training workshops; Professional development", "problemSolvingSkills" : "Student intervention plans", "specialRequirements" : "Abide by state mandates, Abide by federal mandates", "outcomesObjectives" : "Ensure quality education; Engage student learning; Drive instruction; Evaluate pupil progress; Inform parents of progress; Ensure success of all students", "qualificationsBasic" : "Bachelor's degree, Valid Tennessee teaching license, Valid out of state license, On track for Tennessee certification, Practitioner license enrollment, Ability to meet deadlines", "qualificationsPreferred" : "Enrollment in EPP program", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "IOTA Community Schools is a network of four public charter schools in Memphis, Tennessee. We operate both \"fresh start\" schools and \"zoned-enrollment\" turnaround schools. From 6th through 12th grades, our schools serve predominantly minority and low-income populations likely to be first-generation college attendees. IOTA Community Schools is seeking an Environmental Science teacher in the Memphis area for the 2026-2027 school year! We truly believe that every student, whatever their circumstances, holds the innate potential to achieve their goals and succeed in college, leadership, and life. Our staff is committed to continuing their own learning and refining their practice to stay current in the field ensuring a quality education for all. IOTA offers specialized professional development, bi-weekly observations, and opportunities to grow and develop to enable strong teaching and learning in every classroom. We are looking for teachers that are passionate about ensuring that all students have access to a high-quality education regardless of their zip code or socio-economic status. Position Responsibilities: * Attend professional meetings, educational conferences, and teacher training workshops to maintain and improve professional competence. Attend staff meetings, and serve on committees as required. The approximate school day for staff runs from 7:30 a.m. to 3:30-4:30 p.m. * Effectively instruct students in assigned content area(s) as prescribed by IOTA’s academic content standards through direct instruction, demonstrating, and using audio-visual aids and other materials to supplement presentations with the overall goal of engaging student learning. * Work as part of an interdisciplinary team and within content areas planning and aligning curricula to ensure that instruction follows curriculum guidelines or requirements of state and school. * Set clear short-term and long-term goals to drive instruction. * Develop and submit weekly and long range lesson plans containing standards, objectives, essential questions, assessments and lesson plans; assign lessons and review homework. * Consistently use data to evaluate pupil progress, record results, and issue meaningful reports to inform parents of progress. * Create and implement student intervention plans when necessary for students. * Maintain the school’s student management policies and procedures (i.e. attendance records, dress code, etc.) and report to the school administrators when necessary. * Maintain effective supervision and discipline in the classroom. * Work with other teachers and administrators to address and resolve student needs. * Provide necessary accommodations and modifications for growth and success of all students. * Participate in faculty and professional meetings, educational conferences, and teacher training workshops. * Lead and participate in student activities such as: sponsoring student activities or student organizations, * coaching a sports team, working with parents and the community as part of a committee or group, provide morning or after school supervision, and chaperoning student activities. * Abide by all state and federal mandates in reporting sexual or physical abuse and neglect. * Other duties as assigned. ## Qualifications * Bachelor’s degree required * Candidates must have either (a) valid Tennessee teaching license with the appropriate content endorsement to teach or (b) a valid out of state license that can successfully be transferred to Tennessee within 90 days of employment, or (c) demonstrate you are on track to complete the necessary steps towards certification in Tennessee. If you do not hold a teaching license, you may qualify for a Practitioner license while you complete graduate coursework, but you must enroll in an EPP program. Please review here: https://www.tn.gov/education/licensing/educator-preparation/educator-preparation-programs-providers.html * Belief in the IOTA mission * Ability to meet deadlines related to lesson plan submission, grades, and other requirements * Humility, sense of humor, and rock-solid commitment to IOTA’s mission and the communities we serve ## Additional Information Our teacher salary is based on years of certified experience and ranges from $53,000-$75,250. We also offer comprehensive benefits plan as well as the opportunity to impact a growing, mission-driven organization that is committed to the success of all students. This employer strives for a balanced, productive workforce, which is diverse in terms of age, gender, and cultural identity. We do not base hiring or promotional decisions on factors other than performance and professional growth potential. Please note that we are unable to sponsor H1 VISA applicants.", "summaryDescription" : "Environmental Science Teacher at IOTA Community Schools. Skills: Environmental Science, Curriculum development, Student engagement. Attend professional meetings. Attend educational conferences", "postedDate" : "2026-06-15T19:02:41.000", "createdAt" : "2026-06-16T01:32:29.952", "lastUpdated" : "2026-06-16T13:10:59.094", "ingestTimestamp" : "2026-06-16T01:32:29.952", "mongoId" : "6a307d6ff292fd229c04d3a1", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 53000, "salaryAnnualMax" : 75250, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "Lesson planning", "Grading", "Student intervention", "Environmental Science", "Curriculum development", "Student engagement", "Curriculum alignment", "Data evaluation", "Academic content standards", "State school requirements", "Tennessee teaching license", "Out of state license", "Practitioner license" ], "skillCount" : 13, "jobCategory" : "education", "jobSubcategory" : "support", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Education", "llmIndustryConfidence" : 0.98 }, { "id" : "6a307d6ff292fd229c04d3a2", "title" : "Computer Science Teacher", "company" : "IOTA Community Schools", "industry" : "Primary/Secondary Education", "salary" : { "min" : 53000.0, "max" : 75250.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Memphis, TN, United States", "locations" : [ "Memphis", "TN", "United States" ], "certifications" : [ "Tennessee teaching license", "Out of state license", "Practitioner license" ], "timestamp" : "2026-06-16T10:43:56.971", "fingerprint" : "39149a9b7ffb60d17002409144cbf6b74806858b775bf33c243292c807d0c368", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/IOTACommunitySchools/3743990013626876-computer-science-teacher-", "externalId" : "3743990013626876", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Memphis", "state" : "Tennessee", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "35.1460260,-90.0517786" } ], "locationText" : "Memphis, Tennessee, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "not-applicable", "coreResponsibilities" : "Attend professional meetings, Attend educational conferences, Attend teacher training workshops, Attend staff meetings, Serve on committees, Instruct students in content area, Demonstrate content knowledge, Use audio-visual aids, Use materials to supplement presentations, Engage student learning, Work as part of interdisciplinary team, Plan curricula, Align curricula, Ensure instruction follows guidelines, Set short-term goals, Set long-term goals, Develop weekly lesson plans, Develop long range lesson plans, Submit weekly lesson plans, Submit long range lesson plans, Review homework, Evaluate pupil progress using data, Record pupil progress results, Issue reports to parents, Create student intervention plans, Implement student intervention plans, Maintain student management policies, Maintain student management procedures, Report to school administrators, Maintain supervision in classroom, Maintain discipline in classroom, Address student needs, Resolve student needs, Provide necessary accommodations, Provide necessary modifications, Participate in faculty meetings, Participate in professional meetings, Lead student activities, Participate in student activities, Sponsor student activities, Sponsor student organizations, Coach a sports team, Work with parents, Work with community, Provide morning supervision, Provide after school supervision, Chaperon student activities, Abide by state mandates, Abide by federal mandates, Report sexual abuse, Report physical abuse, Report neglect, Perform other duties as assigned", "teamCollaboration" : "Interdisciplinary team; Work with teachers; Work with administrators", "domainKnowledge" : "Computer Science; CTE", "domainList" : [ "computer-science", "cte" ], "domainSpecificKnowledge" : [ "Computer Science", "CTE" ], "documentationSkills" : "Lesson plans; Grades; Reports", "continuousLearning" : "Professional development; Teacher training workshops; Educational conferences", "problemSolvingSkills" : "Student intervention plans", "qualificationsBasic" : "Bachelor's degree required, Valid Tennessee teaching license, Valid out of state license, On track for Tennessee certification, Practitioner license enrollment, Belief in the IOTA mission, Ability to meet deadlines", "qualificationsPreferred" : "Graduate coursework completion", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "IOTA Community Schools is a network of four public charter schools in Memphis, Tennessee. We operate both \"fresh start\" schools and \"zoned-enrollment\" turnaround schools. From 6th through 12th grades, our schools serve predominantly minority and low-income populations likely to be first-generation college attendees. IOTA Community Schools seeks a High School Computer Science (CTE) teacher in the Memphis area for the upcoming school year. We truly believe that every student, whatever their circumstances, holds the innate potential to achieve their goals and succeed. Our staff is committed to continuing their own learning and refining their practice to stay current in the field ensuring a quality education for all. IOTA offers specialized professional development, bi-weekly observations, and opportunities to grow and develop to enable strong teaching and learning in every classroom. We are looking for teachers that are passionate about ensuring that all students have access to a high-quality education regardless of their zip code or socio-economic status. Position Responsibilities: * Attend professional meetings, educational conferences, and teacher training workshops to maintain and improve professional competence. Attend staff meetings, and serve on committees as required. The approximate school day for staff runs from 7:30 a.m. to 3:30-4:30 p.m. * Effectively instruct students in assigned content area(s) as prescribed by IOTA's academic content standards through direct instruction, demonstrating, and using audio-visual aids and other materials to supplement presentations with the overall goal of engaging student learning. * Work as part of an interdisciplinary team and within content areas planning and aligning curricula to ensure that instruction follows curriculum guidelines or requirements of state and school. * Set clear short-term and long-term goals to drive instruction. * Develop and submit weekly and long range lesson plans containing standards, objectives, essential questions, assessments and lesson plans; assign lessons and review homework. * Consistently use data to evaluate pupil progress, record results, and issue meaningful reports to inform parents of progress. * Create and implement student intervention plans when necessary for students. * Maintain the school's student management policies and procedures (i.e. attendance records, dress code, etc.) and report to the school administrators when necessary. * Maintain effective supervision and discipline in the classroom. * Work with other teachers and administrators to address and resolve student needs. * Provide necessary accommodations and modifications for growth and success of all students. * Participate in faculty and professional meetings, educational conferences, and teacher training workshops. * Lead and participate in student activities such as: sponsoring student activities or student organizations, coaching a sports team, working with parents and the community as part of a committee or group, provide morning or after school supervision, and chaperoning student activities. * Abide by all state and federal mandates in reporting sexual or physical abuse and neglect. * Other duties as assigned. ## Qualifications * Bachelor’s degree required * Candidates must have either (a) valid Tennessee teaching license with the appropriate content endorsement to teach or (b) a valid out of state license that can successfully be transferred to Tennessee within 90 days of employment, or (c) demonstrate you are on track to complete the necessary steps towards certification in Tennessee. If you do not hold a teaching license, you may qualify for a Practitioner license while you complete graduate coursework, but you must enroll in an EPP program. Please review here: https://www.tn.gov/education/licensing/educator-preparation/educator-preparation-programs-providers.html * Belief in the IOTA mission * Ability to meet deadlines related to lesson plan submission, grades, and other requirements * Humility, sense of humor, and rock-solid commitment to IOTA’s mission and the communities we serve ## Additional Information Our teacher salary is based on years of certified experience and ranges from $53,000-$75,250. We also offer comprehensive benefits plan as well as the opportunity to impact a growing, mission-driven organization that is committed to the success of all students. This employer strives for a balanced, productive workforce, which is diverse in terms of age, gender, and cultural identity. We do not base hiring or promotional decisions on factors other than performance and professional growth potential. Please note that we are unable to sponsor H1 VISA applicants.", "summaryDescription" : "Computer Science Teacher at IOTA Community Schools. Attend professional meetings. Attend educational conferences", "postedDate" : "2026-06-15T18:52:14.000", "createdAt" : "2026-06-16T01:38:37.414", "lastUpdated" : "2026-06-16T10:43:56.971", "ingestTimestamp" : "2026-06-16T01:38:37.414", "mongoId" : "6a307d6ff292fd229c04d3a2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 53000, "salaryAnnualMax" : 75250, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "Computer Science", "CTE", "Tennessee teaching license", "Out of state license", "Practitioner license" ], "skillCount" : 5, "jobCategory" : "education", "jobSubcategory" : "support", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Education", "llmIndustryConfidence" : 0.98 }, { "id" : "68c2e42bf8b1b0376634c6c2", "title" : "Applied Scientist, SSG Science", "company" : "ADCI", "industry" : "Hardware Development, Applied Science, alexa and amazon devices", "salary" : { "min" : 2250000.0, "max" : 3500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Technology industry in Bengaluru, India, adjusted for mid-seniority level and full-time employment." }, "location" : "Bengaluru, Karnataka, IND", "locations" : [ "Bengaluru, Karnataka, IND" ], "timestamp" : "2026-06-14T22:27:11.314", "fingerprint" : "86c34428ed68523e7c76c170bc6d6619023cfa3cab20f2bc8c56f6c88d6394bb", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3076341/apply", "externalId" : "c2240b65-b43a-4da7-8537-3d32543f3a07", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bengaluru", "state" : "Karnataka", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "12.9767936,77.5900820" } ], "locationText" : "Bengaluru, Karnataka, India", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 2, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Gen AI, Deep Learning, Machine Learning, Java, C++, Python", "professionalSkills" : [ "Scientific Computing", "Deep Learning Theory", "Non Equilibrium Thermodynamics", "Information Theory" ], "hardSkillsList" : [ "Model quantization", "Model pruning", "Model distillation", "Model finetuning", "Neural network optimization", "Linear algebra", "Calculus" ], "hardSkills" : [ { "name" : "Model quantization", "level" : "intermediate" }, { "name" : "Model pruning", "level" : "intermediate" }, { "name" : "Model distillation", "level" : "intermediate" }, { "name" : "Model finetuning", "level" : "intermediate" }, { "name" : "Neural network optimization", "level" : "intermediate" }, { "name" : "Linear algebra", "level" : "intermediate" }, { "name" : "Calculus", "level" : "intermediate" } ], "majorSkills" : "Gen AI, Edge AI, ML HW optimization", "majorSkillsList" : [ "Gen AI", "Edge AI", "ML HW optimization" ], "coreResponsibilities" : "Quantize Gen AI models, Prune Gen AI models, Distill Gen AI models, Finetune Gen AI models, Optimize models for edge platforms, Understand Neural Edge Engine, Invent optimization techniques, Analyze deep learning workloads, Provide guidance to map workloads, Train custom Gen AI models, Publish in open source, Present at ML conferences", "teamCollaboration" : "Compiler engineers; Applied Scientists; Hardware Architects; Product teams", "domainKnowledge" : "Neural Edge Engine; Information Theory; Scientific Computing; Deep Learning Theory; Non Equilibrium Thermodynamics", "domainList" : [ "neural-edge-engine", "information-theory", "scientific-computing", "deep-learning-theory", "non-equilibrium-thermodynamics" ], "domainSpecificKnowledge" : [ "Neural Edge Engine", "Information Theory", "Scientific Computing", "Deep Learning Theory", "Non Equilibrium Thermodynamics" ], "innovationCreativity" : "Develop next generation edge models; Invent optimization techniques; Co-designed with custom ML HW", "problemSolvingSkills" : "Analyze deep learning workloads; Optimize models for edge platforms", "outcomesObjectives" : "Develop next generation edge models; Optimize models for edge platforms; Beat SOTA models; Pave path for production models", "qualificationsBasic" : "2+ years building models, PhD or Master's degree and 4+ years experience, Experience in patents or publications, Experience programming in Java, C++, Python, Experience in algorithms and data structures, Experience in parsing, Experience in numerical optimization, Experience in data mining, Experience in parallel and distributed computing, Experience in high-performance computing, Foundation in mathematical concepts", "qualificationsPreferred" : "Experience in professional software development, Prior experience in productionizing ML models, Managing ML model lifecycle", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History. Key job responsibilities What will you do? - Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms - Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques - Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine - Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics - Train custom Gen AI models that beat SOTA and paves path for developing production models - Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices - Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys. Basic Qualifications: - 2+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - Strong foundation in relevant mathematical concepts (linear algebra, calculus, etc.) Preferred Qualifications: - Experience in professional software development - Prior experience in productionizing ML models and managing their full lifecycle from development to deployment 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" : "Applied Scientist, SSG Science at ADCI. Skills: Gen AI, Edge AI, ML HW optimization. Quantize Gen AI models. Prune Gen AI models", "postedDate" : "2026-06-13T03:51:07.442", "createdAt" : "2026-06-13T03:51:07.442", "lastUpdated" : "2026-06-14T22:27:11.314", "ingestTimestamp" : "2026-06-13T03:51:07.442", "mongoId" : "68c2e42bf8b1b0376634c6c2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3076341/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Model quantization", "Model pruning", "Model distillation", "Model finetuning", "Neural network optimization", "Linear algebra", "Calculus", "Gen AI", "Edge AI", "ML HW optimization", "Scientific Computing", "Deep Learning Theory", "Non Equilibrium Thermodynamics", "Information Theory", "Neural Edge Engine" ], "skillCount" : 15, "jobCategory" : "other", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "69fda4e24c40e2acd1b995f1", "title" : "Sr. Mgr, Applied Science, Personalization", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, consumer engagement", "salary" : { "min" : 218000.0, "max" : 295900.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T02:11:32.828", "fingerprint" : "6503ada1ff2c9d63a2256512de012b0b2f96161a49209741d25ab4b225eb0374", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10414050/apply", "externalId" : "abbcba3a-2b83-4623-a714-19c3b5c74ae2", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "Python, Java, SQL, Machine Learning, Data Science, AWS", "professionalSkills" : [ "Applied Science", "Data Analysis", "Modeling" ], "hardSkillsList" : [ "Large-scale data analysis", "Machine learning modeling" ], "hardSkills" : [ { "name" : "Large-scale data analysis", "level" : "intermediate" }, { "name" : "Machine learning modeling", "level" : "intermediate" } ], "majorSkills" : "Applied Science, Machine Learning, Data Science", "majorSkillsList" : [ "Applied Science", "Machine Learning", "Data Science" ], "coreResponsibilities" : "Lead and execute scientific research and development projects, Design, implement, and evaluate machine learning models, Develop and deploy scalable data science solutions, Collaborate with engineering and product teams, Mentor junior scientists and engineers, Communicate complex findings to stakeholders", "teamCollaboration" : "Engineering teams; Product teams", "domainKnowledge" : "Personalization; Recommendation systems; Search", "domainList" : [ "personalization", "recommendation-systems", "search" ], "domainSpecificKnowledge" : [ "Personalization", "Recommendation systems", "Search" ], "qualificationsBasic" : "5+ years of experience in applied science, data science, or machine learning, Bachelor's degree in Computer Science, Statistics, Mathematics, or related quantitative field, Experience with large-scale data analysis and modeling, Proficiency in at least one programming language such as Python or Java", "qualificationsPreferred" : "PhD in a relevant field, Experience with personalization, recommendation systems, or search, Experience with AWS services", "remoteFriendly" : false, "workSiteFlexibility" : "onsite", "rawDescription" : "We are building the next generation of personalized shopping experiences at Amazon through deep understanding of our customer's intent and our product catalog. We aim to create an experience akin to that of a talented personal shopping assistant — a partner that is knowledgeable, understands your preferences, and helps you find the right solution for your needs. As a Sr. Mgr of Applied Science on the team, you will help lead a large multidisciplinary team. You will have a breadth of problems to work on, ranging from developing state of the art LLM-based techniques to reason about customers and products, developing deep learned transformer-based models to understand and abstract customer intent signals and representations, building large-scale real-time multi-task ranking systems, and more. You will build AI primative systems to empower teams across the company to build recommendations experiences, while also having a direct connection to millions of customers through our own customer facing features every day. Come join us in the journey! Key job responsibilities * Own and drive the science and engineering vision and roadmap across multiple teams, setting a cohesive technical agenda that connects research investments to production systems and measurable customer outcomes * Lead a combined organization of applied scientists and software engineers, building a culture of scientific rigor, engineering excellence, and rapid experimentation * Architect and deliver end-to-end ML systems at Amazon scale — from model research and training through real-time serving infrastructure — for ranking, intent understanding, and personalization across all customers and countries * Drive engineering best practices across the org, ensuring production systems meet Amazon's bar for reliability, latency, and operational excellence * Advance the state of the art in applied ML/AI, contributing to the broader scientific community * Mentor and grow applied scientists and engineers at all levels, developing the next generation of technical leaders in the org * Represent the organization in leadership forums, influencing cross-org strategy and investment decisions across both science and engineering About the team Our mission is to delight every Amazon customer with a personalized shopping experience tailed to their intent. We achieve our mission through investments in UX, Science, and Systems with the purpose of delivering the future of shopping on Amazon. We are seeking a Principal Applied Scientist to lead the science charter across the recommendations and intent identification space. About our organization: Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as \"Keep shopping for ...\", “Customers who bought this item also bought”, and “Frequently bought together”. Amazon’s internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow. Basic Qualifications: - 8+ years of science or engineering team management experience - Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent) - Knowledge of data structures, algorithm design, statistics, and system design - Experience building large-scale machine learning and AI solutions at Internet scale - Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives Preferred Qualifications: - PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent) - 10+ years of building large-scale machine learning and AI solutions at Internet scale experience - Deep expertise in one or more of: LLMs, transformer architectures, recommendation systems, real-time ranking, or representation learning Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Seattle - 218,800.00 - 295,900.00 USD annually", "summaryDescription" : "Sr. Mgr, Applied Science, Personalization at Amazon.com Services LLC. Skills: Applied Science, Machine Learning, Data Science. Lead and execute scientific research and development projects. Design, implement, and evaluate machine learning models", "postedDate" : "2026-06-13T18:32:29.897", "createdAt" : "2026-06-13T18:32:29.897", "lastUpdated" : "2026-06-15T02:11:32.828", "ingestTimestamp" : "2026-06-13T18:32:29.897", "mongoId" : "69fda4e24c40e2acd1b995f1", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10414050/apply", "salaryAnnualMin" : 218000, "salaryAnnualMax" : 295900, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Large-scale data analysis", "Machine learning modeling", "Applied Science", "Machine Learning", "Data Science", "Data Analysis", "Modeling", "Personalization", "Recommendation systems", "Search" ], "skillCount" : 10, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Manager", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "68ed10a570f0b99d58e7b5d7", "title" : "Sr. Applied Scientist, AMX Science", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, no business category", "salary" : { "min" : 150400.0, "max" : 260000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "timestamp" : "2026-06-15T02:06:59.464", "fingerprint" : "9f7d57925e02f97734d9610bee30cbe23afae7fe95813645f0562f81ea8dfaaa", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3105392/apply", "externalId" : "ce90d8d6-627c-473f-94ff-94df6191ac13", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "Java, C++, Python, Neural deep learning, Machine learning, NLP, Recommendation systems, Machine learning graphs, Reinforcement learning, Algorithmic fairness, GenAI, R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Hadoop, Spark", "professionalSkills" : [ "Talent management", "Talent development", "Applied research", "Data-driven culture", "AI applications", "ML systems" ], "hardSkillsList" : [ "Machine learning models", "Deep learning methods", "ML solutions", "Science roadmaps" ], "softSkillsList" : [ "Leadership", "Innovation", "Ambiguity" ], "hardSkills" : [ { "name" : "Machine learning models", "level" : "intermediate" }, { "name" : "Deep learning methods", "level" : "intermediate" }, { "name" : "ML solutions", "level" : "intermediate" }, { "name" : "Science roadmaps", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Innovation" }, { "name" : "Ambiguity" } ], "majorSkills" : "Applied Science, Machine Learning, GenAI, Talent Management", "majorSkillsList" : [ "Applied Science", "Machine Learning", "GenAI", "Talent Management" ], "coreResponsibilities" : "Lead teams building AI/ML solutions, Build AI/ML solutions, Address talent management needs, Address development product needs, Drive innovation, Foster data-driven culture, Lead through ambiguity, Deliver measurable impact, Innovate in AI applications, Build AI agents, Build GenAI systems, Build traditional ML systems, Apply results in products, Work with customers, Work with product managers, Work with program managers, Work with engineering managers, Work with tech leads, Understand needs, Guide teams, Build solutions, Develop science roadmaps, Communicate vision, Communicate milestones, Design science models, Support experiments, Measure impact", "teamCollaboration" : "Product teams; Customers; Program managers; Engineering managers; Tech leads; Cross-functional teams", "projectManagementSkills" : [ "Roadmaps" ], "domainKnowledge" : "Talent management; Talent development; Human behavior; GenAI; ML systems", "domainList" : [ "talent-management", "talent-development", "human-behavior", "genai", "ml-systems" ], "domainSpecificKnowledge" : [ "Talent management", "Talent development", "Human behavior", "GenAI", "ML systems" ], "toolProficiency" : [ "R", "scikit-learn", "Spark MLLib", "MxNet", "Tensorflow", "numpy", "scipy", "Hadoop", "Spark" ], "communicationSkills" : "Communicate vision; Communicate milestones", "innovationCreativity" : "Innovation", "problemSolvingSkills" : "Root cause analysis; Problem solving", "outcomesObjectives" : "Deliver measurable impact", "qualificationsBasic" : "3+ years building ML models, PhD or Master's degree, 6+ years applied research experience, Experience programming Java, C++, Python, Experience neural deep learning methods, Experience machine learning", "qualificationsPreferred" : "Experience modeling tools R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Experience large scale distributed systems Hadoop, Spark", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "AMX Science's mission is to develop science that shapes human behavior in managing Amazon’s talent. We develop the core science for all Amazon-wide talent management and development experiences. Our multidisciplinary science team comprises of applied scientists, data scientists, economists and research scientists. We partner closely with product teams to build scalable science solutions that work backwards from internal customer problems for all of Amazon's businesses and locations around the world. Some of our work includes GenAI-powered writing assistance and insights, talent development and matching recommendations, experimentation and north star metrics, predictive and root cause models for talent events, voice of the customer qualitative analyses frameworks, and talent evaluation framework research. We are looking for an experienced AI/ML Applied Science Manager who has experience leading teams that build, apply and customize GenAI and traditional ML solutions to solve customer problems in production settings. Techniques we use on the team include NLP, supervised and unsupervised learning, recommendation systems, machine learning on graphs, reinforcement learning, algorithmic fairness and others on rich and novel datasets. As a science manager on the team, you will lead a team of ML scientists to build AI/ML solutions to address talent management and development product needs. You will be a hands-on technical leader who excels at driving innovation, fostering a data-driven culture, and leading through ambiguity to deliver measurable impact. You will innovate in the fastest-moving fields of current AI applications, including AI agents and intersection of GenAI and traditional ML systems, such as recommendations, and get to immediately apply your results in highly visible internal Amazon products that have a significant impact on employees’ lives. You will work closely with customers, product and program managers, other engineering managers, and tech leads to understand and guide your teams to build the right solutions. You will develop science roadmaps, communicate your vision and milestones to leadership and to your collaborators in the People Experience and Technology space. If this kind of work excites you, reach out to us to find out more! About the team AMX Science is an experienced central interdisciplinary organization of scientists spanning machine learning, economics and research that builds science models for Amazon's worldwide employee-facing talent management products, designs and supports experiments for product features, and measures impact of product and program initiatives across the broader organization. Examples of our work include GenAI-powered summarization and writing assistants, content and people recommendation systems, scalable experimentation products and measuring organizational north star metrics. Basic Qualifications: - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning Preferred Qualifications: - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Sr. Applied Scientist, AMX Science at Amazon.com Services LLC. Skills: Applied Science, Machine Learning, GenAI, Talent Management. Lead teams building AI/ML solutions. Build AI/ML solutions", "postedDate" : "2026-06-13T17:02:27.652", "createdAt" : "2026-06-13T17:02:27.652", "lastUpdated" : "2026-06-15T02:06:59.464", "ingestTimestamp" : "2026-06-13T17:02:27.652", "mongoId" : "68ed10a570f0b99d58e7b5d7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3105392/apply", "salaryAnnualMin" : 150400, "salaryAnnualMax" : 260000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Machine learning models", "Deep learning methods", "ML solutions", "Science roadmaps", "Leadership", "Innovation", "Ambiguity", "Applied Science", "Machine Learning", "GenAI", "Talent Management", "Talent management", "Talent development", "Applied research", "Data-driven culture", "AI applications", "ML systems", "Roadmaps", "Human behavior", "R", "scikit-learn", "Spark MLLib", "MxNet", "Tensorflow", "numpy", "scipy", "Hadoop", "Spark" ], "skillCount" : 28, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a191e7758b93c861e39f745", "title" : "Internship Student", "company" : "Mercedes-Benz", "industry" : "Manufacturing", "salary" : { "min" : 120000.0, "max" : 240000.0, "currency" : "THB", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Internship Student in Bangkok, Thailand, adjusted for the automotive industry and entry-level seniority." }, "location" : "Thailand-Bangkok-Bangkok", "locations" : [ "Thailand-Bangkok-Bangkok", "11/1, South Sathorn Road, 20th Floor, Yannawa, Sathon, Bangkok" ], "timestamp" : "2026-06-16T01:08:32.159", "fingerprint" : "1da27d2a7102ae7e2fee2704e5ad1f56d565b66dcfa31fe124b4c8993e88715a", "source" : "taleo", "language" : "en", "applyUrl" : "https://tas-daimler.taleo.net/careersection/ex/jobdetail.ftl?job=896134", "externalId" : "896134", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bangkok", "country" : "Thailand", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "13.7524938,100.4935089" } ], "locationText" : "Bangkok, Thailand", "employmentType" : "INTERNSHIP", "minimumEducation" : "Bachelor's", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "coreResponsibilities" : "Gain exposure to business environment, Gain insight into career interests, Thrive in diverse teams, Draw out strengths and capabilities, Build soft skills, Learn job proficiencies, Understand career fit, Grow networking community", "teamCollaboration" : "Diverse, interdisciplinary teams; Diverse workforce environment", "continuousLearning" : "On the job learning", "specialRequirements" : "Open for both Thai and oversea student, Open for Thai student", "qualificationsBasic" : "Bachelor’s degree, Master’s degree, Stay up to 5-6 months, Maximum 12 months", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Internship program at Mercedes-Benz Thailand offers students an immersive experience to have with exposure to the real business environment internationally, and providing insight into possible future career interest of students in the world class and multi-cultural organization to work with Mercedes-Benz (Thailand) Limited, Mercedes-Benz Manufacturing (Thailand) Limited, and Mercedes-Benz Mobility (Thailand) Co., Limited. The Mercedes-Benz Thailand offers many exciting internship opportunities in various business functions, which will provide you opportunities in taking initial steps toward your career such as Marketing & Sales, Customer Services, Finance and Accounting, Business Development, Human Resources, IT, Engineering, etc. Furthermore, our internship program will provide you with on the job learning. You will have the opportunity to thrive in diverse, interdisciplinary teams that allows you to draw out your strengths and capability. This program will provide an exploratory, informational, or job shadowing opportunity to students seeking real life work experience. You will have the opportunity to build soft skills, learn required job proficiencies, better understand what fields may or may not be the best fit for them, and grow your networking community in a diverse workforce environment. Department: 1) Sales Operations, Pricing & Product Management Number of vacant: 1 (open for both Thai and oversea student) 2) Sales Performance Number of vacant: 1 (open for Thai student) 3) Business Network Development Number of vacant: 1 (open for Thai student) 4) Compliance & Legal Number of vacant: 1 (open for Thai student) Location: AIA Sathorn Tower, Bangkok, Thailand We are pleased to offer opportunities for internship program to the students who are currently in the academic program either Bachelor’s degree or Master’s degree , able to stay up to 5-6 months (maximum 12 months) . Mercedes-Benz (Thailand) Limited", "summaryDescription" : "Internship Student at Mercedes-Benz. Gain exposure to business environment. Gain insight into career interests", "createdAt" : "2026-06-14T19:11:29.940", "lastUpdated" : "2026-06-16T01:08:32.159", "ingestTimestamp" : "2026-06-14T19:11:29.940", "mongoId" : "6a191e7758b93c861e39f745", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "general", "jobSubcategory" : "general", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Automotive", "llmIndustryConfidence" : 0.85 }, { "id" : "6a305382f292fd229cf132de", "title" : "Materials Science Division Undergraduate Intern - Fall 2026", "company" : "LLNL", "industry" : "Research", "salary" : { "min" : 24000.0, "max" : 36000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level internship in the United States, adjusted for the high cost of living in the Livermore, CA area and the specific industry." }, "location" : "Livermore, CA, United States", "locations" : [ "Livermore", "CA", "United States" ], "timestamp" : "2026-06-16T07:45:43.293", "fingerprint" : "bcc0f8d04806e9b5078b47561a7b3a61fab7e21e1556aab0147e257e5d402fd3", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/LLNL/3743990013626030-materials-science-division-undergraduate-intern-fall-2026", "externalId" : "3743990013626030", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Livermore", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.6820583,-121.7680530" } ], "locationText" : "Livermore, California, United States", "employmentType" : "INTERNSHIP", "minimumEducation" : "Bachelor's", "experienceLevel" : "internship", "remoteFriendly" : false, "rawDescription" : "Join us and make YOUR mark on the World! Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact. We have multiple openings for undergraduate students to engage in practical research experience to further their educational goals. Opportunities include conducting research in the following scientific fields: organic/inorganic synthesis, analytical, computational, materials characterization, actinide materials, optical materials science; electrochemistry; materials chemistry and physics; computational chemistry and materials science; nanoscale materials synthesis and characterization and metallurgy. These positions are in the Materials Science Division and part of the Materials and Chemistry Institute. You will * Work with scientists on projects involving hands-on work in a laboratory, computation, or data analysis. * Participate in research under close supervision in assigned area. * Gather and analyze the data or information in support of scientific research. * Presenting work through presentations. * Perform other duties as assigned. ## Qualifications * Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA). See Additional Information section below for details. * Must be a continuing college or university student in good standing at an accredited institution pursuing an undergraduate degree in chemistry, materials sciences, computational chemistry, or related field. * Ability to apply basic engineering, scientific, or physics principles to solve technical problems. * Demonstrated effective communication skills. * Ability to present and communicate concepts and ideas. * Experience working with personal computers and familiarity with Word, Excel and PowerPoint. * Ability to work in a team environment. Qualifications We Desire * Knowledge of chemistry and materials. * GPA of 3.0 or above. ## Additional Information All your information will be kept confidential according to EEO guidelines. Why Lawrence Livermore National Laboratory? * Included in 2026 Best Places to Work by Glassdoor! * Holiday Pay * Sick leave accrual * Individual 401(k) contributions * Our values - visit [https://www.llnl.gov/inclusion/our-values](https://www.llnl.gov/diversity/our-values) Security Clearance None required. However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check. National Defense Authorization Act (NDAA) The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities. The restrictions of NDAA Section 3112 apply to this position. To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112. Pre-Employment Drug Test External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor. Wireless and Medical Devices Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices. If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings. How to identify fake job advertisements Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond. To learn more about recruitment scams: Equal Employment Opportunity We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws. Reasonable Accommodation Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please use our [online form](https://www.llnl.gov/join-our-team/careers/accessibility) to submit a request. California Privacy Notice The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed [here](https://www.llnl.gov/join-our-team/careers/privacy-statement).", "summaryDescription" : "Materials Science Division Undergraduate Intern - Fall 2026 at LLNL", "postedDate" : "2026-06-15T18:27:29.000", "createdAt" : "2026-06-15T21:56:41.142", "lastUpdated" : "2026-06-16T07:45:43.293", "ingestTimestamp" : "2026-06-15T21:56:41.142", "mongoId" : "6a305382f292fd229cf132de", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 24000, "salaryAnnualMax" : 36000, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Government", "llmIndustryConfidence" : 0.95 }, { "id" : "6a305342f292fd229cf11fc7", "title" : "Materials Science Division Undergraduate Intern - Fall 2026", "company" : "LLNL", "industry" : "Research", "salary" : { "min" : 20000.0, "max" : 30000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an entry-level internship in the United States, adjusted for the specific location and industry." }, "location" : "Livermore, CA, United States", "locations" : [ "Livermore", "CA", "United States" ], "timestamp" : "2026-06-16T06:40:29.816", "fingerprint" : "8c8c3c32f76c7769a213ebb994db47c21d17104a0f995b8cec686f7011326efd", "source" : "smartrecruiters", "language" : "en", "applyUrl" : "https://jobs.smartrecruiters.com/LLNL/3743990013626030-materials-science-division-undergraduate-intern-fall-2026", "externalId" : "3743990013626030", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Livermore", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.6820583,-121.7680530" } ], "locationText" : "Livermore, California, United States", "employmentType" : "INTERNSHIP", "minimumEducation" : "Bachelor's", "experienceLevel" : "internship", "remoteFriendly" : false, "rawDescription" : "Join us and make YOUR mark on the World! Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact. We have multiple openings for undergraduate students to engage in practical research experience to further their educational goals. Opportunities include conducting research in the following scientific fields: organic/inorganic synthesis, analytical, computational, materials characterization, actinide materials, optical materials science; electrochemistry; materials chemistry and physics; computational chemistry and materials science; nanoscale materials synthesis and characterization and metallurgy. These positions are in the Materials Science Division and part of the Materials and Chemistry Institute. You will * Work with scientists on projects involving hands-on work in a laboratory, computation, or data analysis. * Participate in research under close supervision in assigned area. * Gather and analyze the data or information in support of scientific research. * Presenting work through presentations. * Perform other duties as assigned. ## Qualifications * Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA). See Additional Information section below for details. * Must be a continuing college or university student in good standing at an accredited institution pursuing an undergraduate degree in chemistry, materials sciences, computational chemistry, or related field. * Ability to apply basic engineering, scientific, or physics principles to solve technical problems. * Demonstrated effective communication skills. * Ability to present and communicate concepts and ideas. * Experience working with personal computers and familiarity with Word, Excel and PowerPoint. * Ability to work in a team environment. Qualifications We Desire * Knowledge of chemistry and materials. * GPA of 3.0 or above. ## Additional Information All your information will be kept confidential according to EEO guidelines. Why Lawrence Livermore National Laboratory? * Included in 2026 Best Places to Work by Glassdoor! * Holiday Pay * Sick leave accrual * Individual 401(k) contributions * Our values - visit [https://www.llnl.gov/inclusion/our-values](https://www.llnl.gov/diversity/our-values) Security Clearance None required. However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check. National Defense Authorization Act (NDAA) The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities. The restrictions of NDAA Section 3112 apply to this position. To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112. Pre-Employment Drug Test External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor. Wireless and Medical Devices Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices. If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings. How to identify fake job advertisements Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond. To learn more about recruitment scams: Equal Employment Opportunity We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws. Reasonable Accommodation Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please use our [online form](https://www.llnl.gov/join-our-team/careers/accessibility) to submit a request. California Privacy Notice The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed [here](https://www.llnl.gov/join-our-team/careers/privacy-statement).", "summaryDescription" : "Materials Science Division Undergraduate Intern - Fall 2026 at LLNL", "postedDate" : "2026-06-15T18:27:29.000", "createdAt" : "2026-06-15T21:56:29.848", "lastUpdated" : "2026-06-16T06:40:29.816", "ingestTimestamp" : "2026-06-15T21:56:29.848", "mongoId" : "6a305342f292fd229cf11fc7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 20000, "salaryAnnualMax" : 30000, "salaryBand" : "<30k", "hasSalary" : true, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 0.8888889, "daysOld" : 0, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Government", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2176d474d8ee00a0c1b02d", "title" : "Applied Science Manager, Alexa International", "company" : "Amazon Development Centre (London) Limited", "industry" : "Applied Science, alexa and amazon devices", "salary" : { "min" : 135000.0, "max" : 195000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Manager in the Technology industry in London, UK, adjusted for Amazon's company size and the specific role of Applied Science Manager." }, "location" : "London, England, GBR", "locations" : [ "London, England, GBR" ], "timestamp" : "2026-06-15T06:38:37.509", "fingerprint" : "44053bf5b32e6e73ebedbbf025ba0081359e1e6bcf2442b342b04c0f9f4113de", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10438452/apply", "externalId" : "8456624d-54bd-41ce-926e-2fb31df25013", "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", "experienceLevel" : "Manager", "technicalSkills" : "Machine Learning, NLP, Information Retrieval, Analytics, Deep Learning, Speech Synthesis, Generative AI, LLMs, Speech-to-speech models, Multilingual systems, Text-to-speech synthesis, Phonetics", "professionalSkills" : [ "Scientific strategy", "Scientific rigor", "Experimental methodology", "Publication quality", "Product launch timelines", "Research investments", "Launch commitments", "AI/ML", "Voice personality", "Voice quality", "Pronunciation accuracy" ], "hardSkillsList" : [ "Speech models", "Multilingual phonetics", "Model architectures", "Evaluation methodology", "Low-resource language settings", "Speech quality improvements", "Success metrics", "Evaluation frameworks", "Human preferences" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Speech models", "level" : "intermediate" }, { "name" : "Multilingual phonetics", "level" : "intermediate" }, { "name" : "Model architectures", "level" : "intermediate" }, { "name" : "Evaluation methodology", "level" : "intermediate" }, { "name" : "Low-resource language settings", "level" : "intermediate" }, { "name" : "Speech quality improvements", "level" : "intermediate" }, { "name" : "Success metrics", "level" : "intermediate" }, { "name" : "Evaluation frameworks", "level" : "intermediate" }, { "name" : "Human preferences", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Speech models, Generative AI, Machine Learning, Multilingual systems", "majorSkillsList" : [ "Speech models", "Generative AI", "Machine Learning", "Multilingual systems" ], "coreResponsibilities" : "Lead and manage applied scientists, Build and develop high-performing science teams, Set technical direction, Raise the bar on scientific rigor, Hire, mentor, and grow scientists, Partner with cross org stakeholders, Align goals, Accelerate delivery, Establish clear communication channels, Drive alignment between science roadmaps, Own end-to-end delivery, Define success metrics, Define evaluation frameworks, Balance long-term research investments, Lead and manage a team, Build and enhance capabilities, Collaborate with cross-functional teams, Build methods to align LLMs, Identify and prioritize research opportunities, Mentor and guide team members, Communicate research findings, Experiment rapidly, Drive productisation, Deliver customer impact, Drive academic partnership, Participate in science publications", "teamCollaboration" : "Cross-functional group; Cross-functional teams; Organizational boundaries; Senior leadership; Stakeholders", "projectManagementSkills" : [ "Program management" ], "domainKnowledge" : "Speech synthesis; Multilingual speech generation; Voice quality; Pronunciation accuracy; Low-resource language settings; Generative AI; Speech-to-speech models; Text-to-speech synthesis; Multilingual phonetics; Model architectures; Evaluation methodology; International locales; Heterogeneous data sources; Large-scale computing resources", "domainList" : [ "speech-synthesis", "multilingual-speech-generation", "voice-quality", "pronunciation-accuracy", "low-resource-language-settings", "generative-ai", "speech-to-speech-models", "text-to-speech-synthesis", "multilingual-phonetics", "model-architectures", "evaluation-methodology", "international-locales", "heterogeneous-data-sources", "large-scale-computing-resources" ], "domainSpecificKnowledge" : [ "Speech synthesis", "Multilingual speech generation", "Voice quality", "Pronunciation accuracy", "Low-resource language settings", "Generative AI", "Speech-to-speech models", "Text-to-speech synthesis", "Multilingual phonetics", "Model architectures", "Evaluation methodology", "International locales", "Heterogeneous data sources", "Large-scale computing resources" ], "communicationSkills" : "Communicate research findings; Communicate progress", "innovationCreativity" : "Inventive", "problemSolvingSkills" : "Tackle complex challenges", "outcomesObjectives" : "Deliver solutions with broad impact; Advance the state of the art; Impact customers across 20+ languages; Accelerate advances in speech synthesis; Deliver customer impact", "qualificationsBasic" : "Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or PhD, Knowledge of ML, NLP, Information Retrieval and Analytics, Experience building complex highly-scalable systems that involve predictive models or applications of machine learning, Experience directly managing scientists or machine learning engineers", "qualificationsPreferred" : "PhD preferred, Experience building machine learning models or developing algorithms for business application, Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Alexa International Science team is looking for a passionate, talented, and inventive Applied Science Manager with a strong background in speech models (understanding and generation) and deep learning, to lead a team building industry-leading Generative AI technology with speech-to-speech models and multilingual systems. You will lead a team of Applied Scientists, drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions with broad impact across Alexa's global products. You will own programs with global visibility and interact with a cross-functional group of Science, Product, and Engineering leaders. Your team's work will advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models, directly impacting customers across 20+ languages with natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, and are able to influence and align multiple teams around a shared scientific vision. Core Leadership and Team Management - Lead and manage applied scientists focused on multilingual speech generation and voice personality - Build and develop high-performing science teams focused on speech synthesis, pronunciation, evaluation, and multilingual model adaptation - Set technical direction and raise the bar on scientific rigor, experimental methodology, and publication quality - Hire, mentor, and grow scientists at multiple levels Cross-Organizational Collaboration - Partner with cross org stakeholders to align goals and accelerate delivery - Establish clear communication channels and workflows across organizational boundaries - Drive alignment between science roadmaps and product launch timelines across 20+ locales Delivery and Execution - Own end-to-end delivery of speech quality improvements from research through production deployment - Define success metrics and evaluation frameworks for multilingual speech quality - Balance long-term research investments with near-term launch commitments Key job responsibilities * Lead and manage a team of Applied and Data scientists responsible for building and enhancing capabilities for Alexa+ * Collaborate with cross-functional teams to build methods to align Amazon’s LLMs with human preferences. * Identify and prioritize research opportunities that have the potential to significantly impact our AI systems. * Mentor and guide team members to achieve their career goals and objectives. * Communicate research findings and progress to senior leadership and stakeholders. * Rapidly experiment and drive productisation to deliver customer impact. * Drive academic partnership with top tier Indian university as part of the org’s AI/ML Center initiative. * Participate in and drive science publications in peer-reviewed venues of repute. About the team The Alexa International Science team drives multilingual AI quality for Alexa+, ensuring customers across all supported languages receive a natural, accurate, and culturally appropriate voice experience. We work at the intersection of speech science, LLMs, and international product launches. Basic Qualifications: - Experience directly managing scientists or machine learning engineers - Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or PhD - Knowledge of ML, NLP, Information Retrieval and Analytics - Experience building complex highly-scalable systems that involve predictive models or applications of machine learning Preferred Qualifications: - Experience building machine learning models or developing algorithms for business application - Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers 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" : "Applied Science Manager, Alexa International at Amazon Development Centre (London) Limited. Skills: Speech models, Generative AI, Machine Learning, Multilingual systems. Lead and manage applied scientists. 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Woodlawn", "67220" ], "certifications" : [ "Kansas State License in Science", "KS Certification - Secondary" ], "timestamp" : "2026-06-15T10:28:25.701", "fingerprint" : "b372e6b68f36d8013b5006b4a17ad2e0af4fd2b3c14106567bd260f35e590982", "source" : "taleo", "applyUrl" : "https://aa308.taleo.net/careersection/ex/jobdetail.ftl?job=88553", "externalId" : "88553", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Wichita", "state" : "Kansas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite" } ], "locationText" : "Wichita, Kansas, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor", "experienceMinYears" : 2, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "SMART boards, iPads, computers, copiers, scanners, fax machine, computer network system", "professionalSkills" : [ "middle school curriculum and concepts, including all subject matters taught" ], "hardSkillsList" : [ "Develops and administers middle school curriculum", "Develops lesson plans and instructional materials", "Conducts ongoing assessment of student learning", "Instructs students in the principles of responsible citizenship", "Organizes and maintains a system for accurate and complete record-keeping", "Supervises students in activities that take place out of the classroom", "Administers standardized tests" ], "softSkillsList" : [ "Communication, Teamwork" ], "hardSkills" : [ { "name" : "Develops and administers middle school curriculum", "level" : "intermediate" }, { "name" : "Develops lesson plans and instructional materials", "level" : "intermediate" }, { "name" : "Conducts ongoing assessment of student learning", "level" : "intermediate" }, { "name" : "Instructs students in the principles of responsible citizenship", "level" : "intermediate" }, { "name" : "Organizes and maintains a system for accurate and complete record-keeping", "level" : "intermediate" }, { "name" : "Supervises students in activities that take place out of the classroom", "level" : "intermediate" }, { "name" : "Administers standardized tests", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Communication, Teamwork" } ], "majorSkills" : "Curriculum Development, Instructional Design, Student Assessment, Classroom Management, Parent Communication", "majorSkillsList" : [ "Curriculum Development, Instructional Design, Student Assessment, Classroom Management, Parent Communication" ], "coreResponsibilities" : "Facilitate student success and growth in academic and interpersonal skills through implementing district approved documenting teaching and student progress/activities/outcomes; addressing specific educational needs of individual students and by creating a flexible, safe and optimal learning and providing feedback to students, parents and administration regarding student progress, expectations, goals, etc.", "teamCollaboration" : "Coordinates with other middle school professional staff members, especially within grade level and specific subjects, to evaluate and assess curriculum, and participates in faculty meetings and committees", "projectManagementSkills" : [ "coordinate work" ], "toolProficiency" : [ "Microsoft Office" ], "communicationSkills" : "communicate effectively with students and parents; effective communication with students and parents; respond rapidly in emergency situations; handle all situations with tact and diplomacy; maintain a positive attitude; provide quick, responsive customer service; interact with all internal and external customers in a friendly, professional manner", "documentationSkills" : "documenting teaching and student progress/activities/outcomes; record-keeping; grading; reporting", "continuousLearning" : "Continues to acquire professional knowledge and learn of current developments in the educational field by attending seminars, workshops or professional meetings, or by conducting research", "problemSolvingSkills" : "formulation of action plans", "specialRequirements" : "Must always comply with USD 259's guidelines for equipment use. Limited travel between schools and central offices may be required. Ability to work outdoors during outdoor student activities. Additional demands upon request of Principal, Superintendent. Must be able to respond rapidly in emergency situations.", "outcomesObjectives" : "Ensure that student conduct conforms with the school's standards and school district policies, and establish and maintain standards of pupil behavior needed to achieve a functional learning atmosphere in the classroom", "qualificationsBasic" : "Bachelor's Degree from an accredited college or university in education discipline applicable to teaching assignment", "qualificationsPreferred" : "Master's Degree preferred, Successful prior teaching experience for the appropriate grade level preferred", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Job Title: Science-Middle Position Function: Under the general supervision of the School Principal, to facilitate student success and growth in academic and interpersonal skills through implementing district approved curriculum; documenting teaching and student progress/activities/outcomes; addressing specific educational needs of individual students and by creating a flexible, safe and optimal learning environment; and providing feedback to students, parents and administration regarding student progress, expectations, goals, etc. Essential Performance Responsibilities: Develops and administers middle school curriculum consistent with school district goals and objectives Promotes a classroom environment that is safe and conducive to individualized and small group instruction, and student learning Develops lesson plans and instructional materials and translates lesson plans into learning experiences so as to best utilize the available time for instruction Conducts ongoing assessment of student learning, and modifies instructional methods to fit individual student's needs, including students with special needs; conducts individual small group instruction as needed Instructs students in the principles of responsible citizenship and other subject matters specified in applicable laws, as well as administrative regulations and procedures of the Wichita Public Schools Continues to acquire professional knowledge and learn of current developments in the educational field by attending seminars, workshops or professional meetings, or by conducting research Organizes and maintains a system for accurate and complete record-keeping, grading, and reporting for all student activities, achievement and attendance as required by district procedures and applicable laws Encourages parental involvement in students' education and ensures effective communication with students and parents Ensures that student conduct conforms with the school's standards and school district policies, and establishes and maintains standards of pupil behavior needed to achieve a functional learning atmosphere in the classroom Coordinates with other middle school professional staff members, especially within grade level and specific subjects, to evaluate and assess curriculum, and participates in faculty meetings and committees Selects and requisitions appropriate books, instructional aids and other supplies and equipment and maintains inventory records Supervises students in activities that take place out of the classroom during the school day, including activities involving school transportation Administers standardized tests in accordance with district testing programs Additional Duties: Assists with additional duties as assigned by supervisor. Equipment: This position may require the ability to use SMART boards and iPads in addition to basic office equipment such as computers, copiers, scanners, and fax machine. Must always comply with USD 259's guidelines for equipment use. Travel: Limited travel between schools and central offices may be required. Physical and Mental Demands: Works in standard office and school building environments Ability to work outdoors during outdoor student activities Additional demands upon request of Principal, Superintendent Must be able to respond rapidly in emergency situations Knowledge, Skills, and Abilities: Knowledge of current teaching methods and educational pedagogy, as well as differentiated instruction based upon student learning styles Knowledge of middle school curriculum and concepts, including all subject matters taught Knowledge of data information systems, data analysis and the formulation of action plans Knowledge of applicable federal and state laws regarding education and students Ability to use computer network system and software applications as needed Ability to organize and coordinate work Ability to communicate effectively with students and parents Ability to engage in self-evaluation with regard to performance and professional growth Ability to establish and maintain cooperative working relationships with others contacted in the course of work Interrelations: Contact with personnel within the district and with customers and vendors Will be working under the direct supervision of the department supervisor in order to complete day to day tasks Will be working with a diverse population requiring the ability to handle all situations with tact and diplomacy Must understand and respond appropriately to customer needs and maintain a positive attitude with all customers and colleagues Expected to interact with all internal and external customers in a friendly, professional manner and provide quick, responsive customer service Employee Punctuality and Appearance: In order for schools to operate effectively, employees are expected to perform all assigned duties and work all scheduled hours during each designated workday, unless the employee has received approved leave Any deviation from assigned hours must have prior approval from the employee's supervisor or building administrator All employees are required to report to work dressed in a manner that reflects a positive image of USD 259 and is appropriate for their position Qualification Profile: Kansas State License in Science KS Certification - Secondary Bachelor's Degree from an accredited college or university in education discipline applicable to teaching assignment Master's Degree preferred Successful prior teaching experience for the appropriate grade level preferred. FLSA Status: Exempt", "summaryDescription" : "Science-Middle at Isely Traditional Magnet. Skills: Curriculum Development, Instructional Design, Student Assessment, Classroom Management, Parent Communication. Facilitate student success and growth in academic and interpersonal skills through implementing district approved documenting teaching and student progress/activities/outcomes; addressing specific educational needs of individual students and by creating a flexible, safe and optimal learning and providing feedback to students, parents an", "createdAt" : "2026-06-14T20:41:12.897", "lastUpdated" : "2026-06-15T10:28:25.701", "ingestTimestamp" : "2026-06-14T20:41:12.897", "mongoId" : "696082060937eae70e9c77db", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "hasSalary" : false, "allSkills" : [ "Develops and administers middle school curriculum", "Develops lesson plans and instructional materials", "Conducts ongoing assessment of student learning", "Instructs students in the principles of responsible citizenship", "Organizes and maintains a system for accurate and complete record-keeping", "Supervises students in activities that take place out of the classroom", "Administers standardized tests", "Communication, Teamwork", "Curriculum Development, Instructional Design, Student Assessment, Classroom Management, Parent Communication", "middle school curriculum and concepts, including all subject matters taught", "coordinate work", "Kansas State License in Science", "KS Certification - Secondary", "Microsoft Office" ], "skillCount" : 14, "jobCategory" : "general", "jobSubcategory" : "general", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Education", "llmIndustryConfidence" : 0.98 }, { "id" : "69f46f044c40e2acd1b368e3", "title" : "Applied Science Manager, Sponsored Products", "company" : "Amazon.com Services LLC", "industry" : "Applied Science, Advertising", "salary" : { "min" : 202000.0, "max" : 273600.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "timestamp" : "2026-06-15T05:54:33.373", "fingerprint" : "793c5f8bace94bf0f02270c70b2cfddbec28bf501b8cdadcf6b44c8321d2a7c7", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10408559/apply", "externalId" : "e4047a27-a873-4b2c-a6e4-c8ee5f023878", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "ML, NLP, Information Retrieval, Analytics, Java, C++, Python, Machine Learning, Predictive modeling, Reinforcement learning, Bandits, Adaptive experimentation, Causal inference, Data engineering", "professionalSkills" : [ "Technical leadership", "Econometrics", "User experience" ], "hardSkillsList" : [ "Machine learning", "Data science", "Data engineering", "ML model development", "Model validation", "Model serving", "Statistical analysis", "A/B testing", "Causal inference" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "Data science", "level" : "intermediate" }, { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "ML model development", "level" : "intermediate" }, { "name" : "Model validation", "level" : "intermediate" }, { "name" : "Model serving", "level" : "intermediate" }, { "name" : "Statistical analysis", "level" : "intermediate" }, { "name" : "A/B testing", "level" : "intermediate" }, { "name" : "Causal inference", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Machine Learning, Data Science, Applied Science Management", "majorSkillsList" : [ "Machine Learning", "Data Science", "Applied Science Management" ], "coreResponsibilities" : "Lead multi-disciplinary team, Act as technical leader, Drive ML projects, Lead technical efforts, Build machine learning models, Perform proof-of-concept, Experiment with models, Optimize models, Deploy models, Run A/B experiments, Gather data, Perform statistical analysis, Establish scalable processes, Establish efficient processes, Establish automated processes, Assist in productionizing ML models, Research new ML approaches, Recruit Applied Scientists, Act as mentor", "teamCollaboration" : "Multi-disciplinary team; Across other teams", "domainKnowledge" : "Sponsored Products; Advertising landscape; Generative AI; Advertising lifecycle; Search advertising; Detail pages; Pay-per-click model; Online properties; Mobile properties", "domainList" : [ "sponsored-products", "advertising-landscape", "generative-ai", "advertising-lifecycle", "search-advertising", "detail-pages", "pay-per-click-model", "online-properties", "mobile-properties" ], "domainSpecificKnowledge" : [ "Sponsored Products", "Advertising landscape", "Generative AI", "Advertising lifecycle", "Search advertising", "Detail pages", "Pay-per-click model", "Online properties", "Mobile properties" ], "innovationCreativity" : "Re-imagining advertising; Re-inventing advertising experiences; Bridging human creativity with AI; Developing responsible AI; Developing intelligent AI; Shaping the future of advertising; Creating new ads experience; Innovating on behalf of customers", "problemSolvingSkills" : "Solving complex challenges", "qualificationsBasic" : "4+ years applied research, 3+ years management experience, 3+ years building ML models, PhD or Master's degree, 6+ years applied research, Knowledge of ML, Knowledge of NLP, Knowledge of Information Retrieval, Knowledge of Analytics, Experience programming in Java, Experience programming in C++, Experience programming in Python", "qualificationsPreferred" : "PhD preferred, Master's degree preferred, Experience building deep learning systems, Experience building ML systems, Experience building computer vision systems, Experience with cloud platform certs", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. We are seeking a technical leader for our Search Thematic Advertising Experiences team to lead a multi-disciplinary team of science and engineering. This team is within the Sponsored Product team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant product ads on Amazon search and detail pages world-wide. The team operates with the dual objective of enhancing the experience of Amazon shoppers and enabling the monetization of our online and mobile page properties. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference, data engineering. Key job responsibilities Search Thematic Advertising Experiences , within Sponsored Products, is seeking an Applied Science Manager to join a fast growing team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. As an Applied Science Manager on this team you will: --Lead a multi-disciplinary team of applied scientists and engineers. --Act as the technical leader in Machine Learning and drive full life-cycle Machine Learning projects. --Lead technical efforts within this team and across other teams. --Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production. --Run A/B experiments, gather data, and perform statistical analysis. --Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. --Work closely with software engineers to assist in productionizing your ML models. --Research new machine learning approaches. --Recruit Applied Scientists to the team and act as a mentor to other scientists on the team. A day in the life The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the direction is a must. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon Basic Qualifications: - 4+ years of applied research experience - 3+ years of scientists or machine learning engineers management experience - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Knowledge of ML, NLP, Information Retrieval and Analytics - Experience programming in Java, C++, Python or related language Preferred Qualifications: - Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, NY, New York - 202,200.00 - 273,600.00 USD annually USA, WA, SEATTLE - 183,800.00 - 248,700.00 USD annually", "summaryDescription" : "Applied Science Manager, Sponsored Products at Amazon.com Services LLC. Skills: Machine Learning, Data Science, Applied Science Management. Lead multi-disciplinary team. Act as technical leader", "postedDate" : "2026-06-13T15:46:53.935", "createdAt" : "2026-06-13T15:46:53.935", "lastUpdated" : "2026-06-15T05:54:33.373", "ingestTimestamp" : "2026-06-13T15:46:53.935", "mongoId" : "69f46f044c40e2acd1b368e3", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10408559/apply", "salaryAnnualMin" : 202000, "salaryAnnualMax" : 273600, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Machine learning", "Data science", "Data engineering", "ML model development", "Model validation", "Model serving", "Statistical analysis", "A/B testing", "Causal inference", "Leadership", "Mentoring", "Machine Learning", "Data Science", "Applied Science Management", "Technical leadership", "Econometrics", "User experience", "Sponsored Products", "Advertising landscape", "Generative AI", "Advertising lifecycle", "Search advertising", "Detail pages", "Pay-per-click model", "Online properties", "Mobile properties" ], "skillCount" : 26, "jobCategory" : "other", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Advertising Technology" }, { "id" : "69fd04b64c40e2acd1ae6158", "title" : "Internship Student", "company" : "Mercedes-Benz", "industry" : "Manufacturing", "salary" : { "min" : 120000.0, "max" : 240000.0, "currency" : "THB", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for an Internship Student in Bangkok, Thailand, adjusted for the automotive industry and entry-level seniority." }, "location" : "Thailand-Bangkok-Bangkok", "locations" : [ "Thailand-Bangkok-Bangkok", "11/1, South Sathorn Road, 20th Floor, Yannawa, Sathon, Bangkok" ], "timestamp" : "2026-06-15T23:38:41.862", "fingerprint" : "3e08d31777d50217911de6f7e3e9f6c2058893d652828501bfa53a1b085dd252", "source" : "taleo", "language" : "en", "applyUrl" : "https://daimler.taleo.net/careersection/ex/jobdetail.ftl?job=896134", "externalId" : "896134", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bangkok", "country" : "Thailand", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "13.7524938,100.4935089" } ], "locationText" : "Bangkok, Thailand", "employmentType" : "INTERNSHIP", "minimumEducation" : "Bachelor's", "experienceMinYears" : 0, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "coreResponsibilities" : "Gain exposure to business environment, Gain insight into career interests, Work in a multi-cultural organization, Thrive in diverse teams, Draw out strengths and capabilities, Gain exploratory opportunity, Gain informational opportunity, Gain job shadowing opportunity, Build soft skills, Learn job proficiencies, Understand career field fit, Grow networking community", "teamCollaboration" : "Diverse, interdisciplinary teams", "continuousLearning" : "On the job learning", "qualificationsBasic" : "Bachelor’s degree, Master’s degree, 5-6 months internship duration, Maximum 12 months internship duration", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Internship program at Mercedes-Benz Thailand offers students an immersive experience to have with exposure to the real business environment internationally, and providing insight into possible future career interest of students in the world class and multi-cultural organization to work with Mercedes-Benz (Thailand) Limited, Mercedes-Benz Manufacturing (Thailand) Limited, and Mercedes-Benz Mobility (Thailand) Co., Limited. The Mercedes-Benz Thailand offers many exciting internship opportunities in various business functions, which will provide you opportunities in taking initial steps toward your career such as Marketing & Sales, Customer Services, Finance and Accounting, Business Development, Human Resources, IT, Engineering, etc. Furthermore, our internship program will provide you with on the job learning. You will have the opportunity to thrive in diverse, interdisciplinary teams that allows you to draw out your strengths and capability. This program will provide an exploratory, informational, or job shadowing opportunity to students seeking real life work experience. You will have the opportunity to build soft skills, learn required job proficiencies, better understand what fields may or may not be the best fit for them, and grow your networking community in a diverse workforce environment. Department: 1) Sales Operations, Pricing & Product Management Number of vacant: 1 (open for both Thai and oversea student) 2) Sales Performance Number of vacant: 1 (open for Thai student) 3) Business Network Development Number of vacant: 1 (open for Thai student) 4) Compliance & Legal Number of vacant: 1 (open for Thai student) Location: AIA Sathorn Tower, Bangkok, Thailand We are pleased to offer opportunities for internship program to the students who are currently in the academic program either Bachelor’s degree or Master’s degree , able to stay up to 5-6 months (maximum 12 months) . Mercedes-Benz (Thailand) Limited", "summaryDescription" : "Internship Student at Mercedes-Benz. Gain exposure to business environment. Gain insight into career interests", "createdAt" : "2026-06-14T17:38:30.360", "lastUpdated" : "2026-06-15T23:38:41.862", "ingestTimestamp" : "2026-06-14T17:38:30.360", "mongoId" : "69fd04b64c40e2acd1ae6158", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "general", "jobSubcategory" : "general", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Automotive", "llmIndustryConfidence" : 0.85 }, { "id" : "6a2cc20674d8ee00a0a053d4", "title" : "Data Science", "company" : "Axle Energy", "industry" : "Engineering", "salary" : { "min" : 65000.0, "max" : 95000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Data Science roles in London, adjusted for mid-seniority and the climate tech industry." }, "location" : "London", "locations" : [ "London" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T00:55:19.789", "fingerprint" : "4c6287b90e27f00f5f6dd53bb43aae9c7eed60805ce0df7518100fe4784982bd", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/axle-careers/71afed8b-6f22-4c24-9a5a-7a4ab34f449f/application", "externalId" : "71afed8b-6f22-4c24-9a5a-7a4ab34f449f", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, Docker, GCP, React", "professionalSkills" : [ "Commercial value instinct", "Production deployment", "System design" ], "hardSkillsList" : [ "Data exploration", "Model building", "Model optimization", "Data production", "Production code writing", "Scalable systems development" ], "hardSkills" : [ { "name" : "Data exploration", "level" : "intermediate" }, { "name" : "Model building", "level" : "intermediate" }, { "name" : "Model optimization", "level" : "intermediate" }, { "name" : "Data production", "level" : "intermediate" }, { "name" : "Production code writing", "level" : "intermediate" }, { "name" : "Scalable systems development", "level" : "intermediate" } ], "majorSkills" : "Data Science, Machine Learning, Productionization", "majorSkillsList" : [ "Data Science", "Machine Learning", "Productionization" ], "coreResponsibilities" : "Build models, Optimize models, Deploy models, Develop understanding of energy markets, Develop understanding of grid dynamics, Develop understanding of trading strategies, Own work lifecycle, Research work, Prototype work, Write production code, Contribute to systems, Turn ideas into solutions, Productionize solutions", "teamCollaboration" : "Cross-functional teams; Client communication", "domainKnowledge" : "Energy markets; Grid dynamics; Trading strategies; Electricity system; Power trading", "domainList" : [ "energy-markets", "grid-dynamics", "trading-strategies", "electricity-system", "power-trading" ], "domainSpecificKnowledge" : [ "Energy markets", "Grid dynamics", "Trading strategies", "Electricity system", "Power trading" ], "toolProficiency" : [ "Docker", "Claude Code" ], "communicationSkills" : "Client speaking", "continuousLearning" : "AI workflow exploration", "innovationCreativity" : "Prototype development", "problemSolvingSkills" : "Data exploration; Root cause analysis", "qualificationsBasic" : "5+ years Python, SQL proficiency, 5+ years data science experience", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified, Dbt Certified, Knowledge of electricity system, Familiarity with time-series data", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT US At Axle Energy, we’re building the infrastructure that will underpin the decarbonised energy system. Our software moves energy usage to times when electricity is cheap and green, by controlling vehicle charging, heating systems, and home batteries. We control hundreds of thousands of energy assets. We’re building in a legacy industry and moving gigawatt-hours of electrons in the real world, but we operate at lightning speed, and we’re growing the team to meet customer demand. We’re proud to be supported by world-leading investors, including Accel. Read more about what we’re building here https://www.axle.energy/blog/analysis/power-of-the-home. ABOUT THE ROLE We're hiring full stack data scientists who love to get into the nitty gritty of the domain, have an instinct for commercial value, and own the entire process from data exploration to production. - Building, optimising, and deploying models that operate reliably at scale - Developing a deep understanding of energy markets, grid dynamics, and trading strategies - Taking ownership of the full lifecycle of your work, from research and prototyping through to production - Writing clean, production-quality code and contributing to robust, scalable systems - Working beyond notebooks, turning ideas into real-world, productionised solutions IT’D BE NICE IF YOU COULD BRING: - Knowledge of the electricity system, specifically power trading - Comfort speaking to clients (we’re a small team and wear many hats) - Familiarity with time-series data TECH STACK \uD83D\uDC0D We build in Python + React for the frontend (less relevant for this role) \uD83D\uDC0B Everything we build lives in Docker, for minimal cross-platform faff and maximal reproducibility. \uD83E\uDD16 Unlimited Claude Code tokens - we are aggressive users and explorers of AI, and encourage everybody to reconsider their workflows regularly ☁️ We deploy on GCP WHAT'S IN IT FOR YOU A meaningful slice of equity in Axle, alongside a competitive salary. We operate with a deliberately flat structure. We aim to keep pay equitable across the company, with a 1:1 median ratio between founder and team compensation. The opportunity to directly shape the future of energy markets and accelerate the transition to a low-carbon world. Bi-annual retreats to strengthen team connection & shared purpose. Hybrid working - We have a dog-friendly office around Farringdon. To maximize collaboration, we ask that you spend 2-3 days a week in the office. We are extremely keen to build a diverse company, and we’re particularly eager to hear from candidates who don't fit the traditional role stereotypes. If you’re motivated by our mission, please do reach out, even if you feel you might not ‘check all the boxes’. INTERVIEW PROCESS 1. Initial interview 2. Take-home exercise 3. Final interview (in-person) 4. Offer, references, and welcome to the team!", "summaryDescription" : "Data Science at Axle Energy. Skills: Data Science, Machine Learning, Productionization. Build models. 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We create solutions which measure the comprehensive impact of advertiser's ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We also own the science solutions for AI tools that unlock new insights and automate high-effort customer workflows, such as custom query and report generation based on natural language user requests. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As an Applied Scientist on the team, you will lead measurement solutions end-to-end from inception to production. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. Key job responsibilities - Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems - Disambiguate problems to propose clear evaluation frameworks and success criteria - Work autonomously and write high quality technical documents - Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production - Partner closely with other scientists to deliver large, multi-faceted technical projects - Share and publish works with the broader scientific community through meetings and conferences - Communicate clearly to both technical and non-technical audiences - Contribute new ideas that shape the direction of the team's work - Mentor more junior scientists and participate in the hiring process About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions. Basic Qualifications: - 2+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience programming in Java, C++, Python or related language - Experience building machine learning models or developing algorithms for business application Preferred Qualifications: - Experience with popular deep learning frameworks such as MxNet and Tensor Flow - Experience in professional software development - Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects) - Experience in designing experiments and statistical analysis of results - Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning - Experience in patents or publications at top-tier peer-reviewed conferences or journals Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Applied Scientist, Ads Measurement Science at Amazon.com Services LLC. Skills: Machine Learning, Data Science, Statistical Modeling. Design and implement machine learning models. 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Autonomous agent behavior; Personalization systems; Recommendation engines; Dynamic content generation; AI agent architecture; Decision-making frameworks; Behavioral modeling; Multi-modal AI systems; Cloud platform", "domainList" : [ "applied-ai", "autonomous-agent-behavior", "personalization-systems", "recommendation-engines", "dynamic-content-generation", "ai-agent-architecture", "decision-making-frameworks", "behavioral-modeling", "multi-modal-ai-systems", "cloud-platform" ], "domainSpecificKnowledge" : [ "Applied AI", "Autonomous agent behavior", "Personalization systems", "Recommendation engines", "Dynamic content generation", "AI agent architecture", "Decision-making frameworks", "Behavioral modeling", "Multi-modal AI systems", "Cloud platform" ], "communicationSkills" : "Translate concepts", "innovationCreativity" : "Innovation culture", "problemSolvingSkills" : "Root cause analysis", "qualificationsBasic" : "PhD in Computer Science, 7+ years applied research, 3+ years people management, Track record leading research projects, Publication record top-tier conferences, Experience managing technical teams, Translate complex technical concepts", "qualificationsPreferred" : "Experience AI agent architecture design, Knowledge of multi-modal AI systems, Experience professional software development", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Applied AI means AI that is put to work to solve real-world problems and attain practical goals within the constraints of running a business. Our team leverages Amazon’s expertise to build applied AI solutions that businesses love and trust for their day-to-day success. We're creating the products and tools that people will need to do great work with their AI workforce in future. We're a 2 pizza team moving fast to build a new agentic product from the ground up. If you are scrappy and bias for action is your favorite LP, you will fit right in. You will lead a team of applied scientists and software developers, driving the technical vision while fostering a culture of innovation and scientific excellence. You must be excellent at balancing business needs and strategic thinking with hands-on technical depth. We're prioritizing the following experience: - Experience implementing reinforcement learning for autonomous agent behavior - Managing project portfolios and resource allocation across multiple high priority programs - Knowledge of personalization systems, recommendation engines, or dynamic content generation - Production operational experience Want to learn more? Send me an email (Slack is noisy and I will probably miss your message!) About the team 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. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, 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. 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. 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 and 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. Basic Qualifications: - PhD in Computer Science, Machine Learning, or related field - 7+ years in applied research, with 3+ years of people management experience - Track record of leading successful research projects and delivering business impact - Strong publication record in top-tier conferences/journals (CVPR, NeurIPS, ICML, etc.) - Experience managing technical teams in ML or AI - Demonstrated ability to translate complex technical concepts to various audiences Preferred Qualifications: - Demonstrated experience in AI agent architecture design, including decision-making frameworks and behavioral modeling - Knowledge of multi-modal AI systems - Experience in professional software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $196,900/year in our lowest geographic market up to $340,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Sr Manager, Applied Science, Applied AI Solutions at Amazon Development Center U.S., Inc.. Skills: Applied AI, Agent architecture, Team leadership. Lead team of scientists. 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Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities Develop ML models for various recommendation & search systems using deep learning, online learning, and optimization methods Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps Stay up-to-date with advancements and the latest modeling techniques in the field Publish your research findings in top conferences and journals A day in the life We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences. Basic Qualifications: - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications: - Experience using Unix/Linux - Experience in professional software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Applied Scientist II, Prime Video - Personalization and Discovery Science, Personalization and Discovery Science at Amazon.com LLC. Skills: Machine learning, Recommendation systems, Search systems. Develop ML models for recommendation & search systems. 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In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: [LinkedIn](https://www.linkedin.com/company/nielseniq/mycompany/) | [Instagram](https://www.instagram.com/nielseniq/) | [Twitter](https://twitter.com/nielseniq) | [Facebook](https://www.facebook.com/NielsenIQ.global/) Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. The Product Design and Enhancement (PDE) team is responsible for all design-related activities of the Data Science unit at NIQ, setting up the base for Retail Index reporting. The key responsibilities of PDE associate assigned to given market include: * Sample Design, Universe Estimation and other design-related projects for the Retail Index * Identification of quality risks and follow up on solutions * Engagement with stakeholders on scope, execution, data exchange and outcomes for assigned projects * Expert-level analysis of results and presentations with insights * Teamwork in virtual multi-country environment requiring effective communication with colleagues located in various countries * Usage of dedicated software supported by ad hoc programming and data mining * Identification of opportunities for innovations and tools development in the dynamic work environment * Analysis of processes within the area of responsibilities with recommendations on improvements ## Qualifications * Master’s degree in mathematics, Statistics, Operations Research or related fields * Knowledge of Microsoft Office applications * Competency in at least one programming language (Python or R) * Organizational skills to manage projects (time management, prioritization, deadlines) * Ability to engage and communicate effectively * Strong analytical and problem-solving skills * Good command of English, Knowledge of local Chinese (Mandarin) * Eagerness to continuously learn and adapt to changing technologies and tools * 0 to 1 years of work experience * Master's Degree is Mandatory ( M.Sc Stats/ Big Data Analyst can apply) Preferable: * Work experience in FMCG, Market research, consumer research or similar industries * Knowledge of statistical inference and survey-based research ## Additional Information It's a contract-based role for 6 months Our Benefits * Flexible working environment * Volunteer time off * LinkedIn Learning * Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://www.nielseniq.com/global/en/ai-safety-policies. About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: [LinkedIn](https://www.linkedin.com/company/nielseniq/mycompany/) | [Instagram](https://www.instagram.com/nielseniq/) | [Twitter](https://twitter.com/nielseniq) | [Facebook](https://www.facebook.com/NielsenIQ.global/) Our commitment to Diversity, Equity, and Inclusion At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. 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Stakeholders", "domainKnowledge" : "Cloud data stacks; ML frameworks; BI platforms; Statistical methods", "domainList" : [ "cloud-data-stacks", "ml-frameworks", "bi-platforms", "statistical-methods" ], "domainSpecificKnowledge" : [ "Cloud data stacks", "ML frameworks", "BI platforms", "Statistical methods" ], "toolProficiency" : [ "SQL", "Python", "R", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Snowflake", "BigQuery", "Redshift", "Databricks", "Scikit-learn", "TensorFlow", "PyTorch", "MLflow", "AWS", "GCP", "Azure" ], "problemSolvingSkills" : "Analytical skills", "qualificationsBasic" : "Bachelor's degree in a quantitative field, Proficiency in SQL, Experience with Python or R", "qualificationsPreferred" : "Master's degree or PhD, Experience with cloud platforms (AWS, GCP, Azure), Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch), Experience with BI tools (Tableau, Power BI, Looker), Experience with data warehousing (Snowflake, BigQuery, Redshift), Experience with MLOps tools (MLflow, Kubeflow)", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: [LinkedIn](https://www.linkedin.com/company/nielseniq/mycompany/) | [Instagram](https://www.instagram.com/nielseniq/) | [Twitter](https://twitter.com/nielseniq) | [Facebook](https://www.facebook.com/NielsenIQ.global/) Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. The Product Design and Enhancement (PDE) team is responsible for all design-related activities of the Data Science unit at NIQ, setting up the base for Retail Index reporting. The key responsibilities of PDE associate assigned to given market include: * Sample Design, Universe Estimation and other design-related projects for the Retail Index * Identification of quality risks and follow up on solutions * Engagement with stakeholders on scope, execution, data exchange and outcomes for assigned projects * Expert-level analysis of results and presentations with insights * Teamwork in virtual multi-country environment requiring effective communication with colleagues located in various countries * Usage of dedicated software supported by ad hoc programming and data mining * Identification of opportunities for innovations and tools development in the dynamic work environment * Analysis of processes within the area of responsibilities with recommendations on improvements ## Qualifications * Master’s degree in mathematics, Statistics, Operations Research or related fields * Knowledge of Microsoft Office applications * Competency in at least one programming language (Python or R) * Organizational skills to manage projects (time management, prioritization, deadlines) * Ability to engage and communicate effectively * Strong analytical and problem-solving skills * Good command of English, Knowledge of local Chinese (Mandarin) * Eagerness to continuously learn and adapt to changing technologies and tools * 0 to 1 years of work experience * Master's Degree is Mandatory ( M.Sc Stats/ Big Data Analyst can apply) Preferable: * Work experience in FMCG, Market research, consumer research or similar industries * Knowledge of statistical inference and survey-based research ## Additional Information It's a contract-based role for 6 months Our Benefits * Flexible working environment * Volunteer time off * LinkedIn Learning * Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://www.nielseniq.com/global/en/ai-safety-policies. About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: [LinkedIn](https://www.linkedin.com/company/nielseniq/mycompany/) | [Instagram](https://www.instagram.com/nielseniq/) | [Twitter](https://twitter.com/nielseniq) | [Facebook](https://www.facebook.com/NielsenIQ.global/) Our commitment to Diversity, Equity, and Inclusion At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. 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Discovery; Prime Video", "domainList" : [ "personalization", "discovery", "prime-video" ], "domainSpecificKnowledge" : [ "Personalization", "Discovery", "Prime Video" ], "toolProficiency" : [ "SQL", "Python", "R", "Scala", "Spark", "Dbt", "Tableau", "Power BI", "Looker", "Snowflake", "BigQuery", "Redshift", "Databricks", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "SageMaker", "Athena", "GCP", "Vertex AI", "Azure", "Synapse", "ML Studio" ], "qualificationsBasic" : "Bachelor's degree or equivalent experience, 5+ years of experience in data science or related field, Experience with large-scale data analysis, Experience with machine learning, Experience with data engineering, Experience with business intelligence, Experience with analytics engineering, Experience with quantitative analysis, Experience with SQL, Experience with Python", "qualificationsPreferred" : "Master's degree or PhD in a quantitative field, Experience with AWS, Experience with GCP, Experience with Azure, Experience with Snowflake, Experience with BigQuery, Experience with Redshift, Experience with Databricks, Experience with dbt, Experience with Fivetran, Experience with Airflow, Experience with Tableau, Experience with Power BI, Experience with Looker, Experience with scikit-learn, Experience with TensorFlow, Experience with PyTorch, Experience with XGBoost, Experience with LightGBM, Experience with Hugging Face, Experience with MLflow, Experience with regression, Experience with classification, Experience with clustering, Experience with time-series analysis, Experience with A/B testing, Experience with causal inference", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for a self-motivated, passionate and resourceful Applied Science Manager to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will lead a strong science team and work closely with other science and engineering leaders, product and business partners together to build the best personalized customer experience for Prime Video. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Lead to develop AI solutions for various Prime Video recommendation and personalization systems using Deep learning, GenAI, Reinforcement Learning, recommendation system and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Hire and grow a science team working in this exciting video personalization domain. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various devices. We work closely with the engineering teams to launch our solutions in production. Basic Qualifications: - PhD, or Master's degree and 6+ years of applied research experience - 4+ years of applied research experience - 3+ years of scientists or machine learning engineers management experience - 3+ years of building machine learning models for business application experience - Knowledge of ML, NLP, Information Retrieval and Analytics - Experience programming in Java, C++, Python or related language - Strong strategic thinkings, strong communication and cross-team collaboration skills Preferred Qualifications: - Hands-on experience with large-scale online recommendation systems. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $165,500/year in our lowest geographic market up to $286,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Applied Science Manager, Prime Video Personalization & Discovery at Amazon.com Services LLC. Skills: Data science, Machine learning, Data engineering. Develop and deploy machine learning models. 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Preference for working in teams", "domainKnowledge" : "Electric vehicle batteries; Battery management; Electronics development; Lithium-ion battery behavior; Dynamical systems; State estimation methods", "domainList" : [ "electric-vehicle-batteries", "battery-management", "electronics-development", "lithium-ion-battery-behavior", "dynamical-systems", "state-estimation-methods" ], "domainSpecificKnowledge" : [ "Electric vehicle batteries", "Battery management", "Electronics development", "Lithium-ion battery behavior", "Dynamical systems", "State estimation methods" ], "toolProficiency" : [ "Git", "Docker", "AWS" ], "communicationSkills" : "English; German", "documentationSkills" : "Document proof of concepts", "innovationCreativity" : "Innovate quickly; Anticipate future needs; Take smart risks", "problemSolvingSkills" : "Analyze results; Evaluate algorithms; Evaluate data analysis tools", "qualificationsBasic" : "Student in electrical engineering, physics, mathematics, computer science, software engineering, or similar, Confident working in high-level programming language for data analysis, Basic understanding of general electronics, embedded systems, and IoT devices, Willingness to take responsibility for a project, Not discouraged by setbacks", "qualificationsPreferred" : "Comfortable with data analysis in Python, Comfortable with databases (SQL / time-series), Comfortable with cloud/infrastructure tooling, Knowledge of dynamical systems (ODEs), Knowledge of state estimation methods, Initial insights into modeling lithium-ion battery behavior", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "About Munich Electrification Munich Electrification is an innovative company founded with the aim of accelerating the transition to electric and connected mobility. We develop innovative electronic control units for electric vehicles and stationary storage systems for our global customers. Our international team is composed of highly motivated and exceptional engineers. As a small and specialized team we are well-aware of the importance of each individual colleague and support and promote each employee according to their abilities and needs. Our office with adjacent prototype and testing lab is located in the heart of Munich at the Heimeranplatz. This is what we stand for: - Technological Leadership: We challenge norms, innovate quickly, and anticipate future needs. We take smart risks and learn from outcomes to stay ahead. - Sustainability: We actively drive change for a sustainable future, aware of our impact and inspiring others to build a better world. - Team Culture: We believe work should be enjoyable, fostering a spirit of inspiration, celebration, and teamwork across the globe. - Entrepreneurial Spirit: We embrace change, think big, and push limits with passion. Your Role We are looking for a working student to join our Battery Science and Data team. You will work directly with our engineers to gain hands-on experience in physics-based modeling, data analysis, and cloud-based simulation. This is your chance to deepen your knowledge of electric vehicle batteries and the simulation frameworks used to model their real-world behavior. We are hiring several working students for different areas in our team. You will focus on one of them, so you do not need to bring the full list below. Just show us where your strengths are. Your future tasks at a glance - Support the development and validation of battery cell models and high-level algorithms (e.g., SOx estimation) by running simulations and analyzing results. - Assist in maintaining our data pipeline infrastructure, including data cleansing, structuring raw logs from IoT devices, and preparing datasets for analysis. - Support the team with deployments in test cars and monitor OTA (Over-the-Air) updates to ensure data integrity. - Evaluate, implement, and document proof of concepts for future algorithms or new data analysis tools. What you bring with you - Student in electrical engineering, physics, mathematics, computer science, software engineering, or a similar field. - Confident working in a high-level programming language (Python preferred) for data analysis. - Basic understanding of general electronics, embedded systems, and IoT devices. - Willingness to take responsibility for a project and not to be discouraged by setbacks. - Preference for working in teams and strong communication skills (English and German preferred). Ideally, you also have - Comfortable with at least one of: data analysis in Python, or databases (SQL / time-series) and cloud/infrastructure tooling (AWS, Docker, Git). - Knowledge of dynamical systems (ODEs) or state estimation methods (e.g., Kalman filters). - Initial insights into modeling lithium-ion battery behavior. Our Offer & Benefits The chance to be part of a highly innovative, agile, and unique team with prestigious customers in the automotive and battery storage sector. You will gain a deeper knowledge around connected & electric vehicle batteries, battery management and electronics development and strive in an exciting work environment Benefits (Full-time Employees): - Trust-based working hours and hybrid work - Adequate and competitive compensation - Pension Plan/Bonus - Free access to the fitness center right next to us or subsidized EGYM Wellpass - Free snacks, coffee, drinks and lunch (freshly cooked by our chef) every day - Public transport ticket - Bike-Leasing via Business Bike - Experience various inspiring and fun team events - ME-branded clothing - Option to \"work from anywhere\" (6 weeks/year)", "summaryDescription" : "Working Student – Battery Science and Data (f/m/d) at Munich Electrification. Skills: Battery science, Data analysis, Cloud simulation. Support development and validation of battery cell models. Support development and validation of high-level algorithms", "createdAt" : "2026-06-14T19:28:27.528", "lastUpdated" : "2026-06-16T02:03:41.673", "ingestTimestamp" : "2026-06-14T19:28:27.528", "mongoId" : "6a2c68c874d8ee00a0904bdd", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "30k-50k", "hasSalary" : false, "allSkills" : [ "Physics-based modeling", "Time-series databases", "Kalman filters", "Battery science", "Data analysis", "Cloud simulation", "Algorithm development", "Data cleansing", "Data structuring", "Dataset preparation", "Proof of concepts", "Electric vehicle batteries", "Battery management", "Electronics development", "Lithium-ion battery behavior", "Dynamical systems", "State estimation methods", "Git", "Docker", "AWS" ], "skillCount" : 20, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Entry", "dataQualityScore" : 0.7777778, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Automotive", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ac774d8ee00a090de2c", "title" : "Senior Data Scientist, Applied Science", "company" : "Future Secure AI", "salary" : { "min" : 165000.0, "max" : 245000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior Data Scientist in the US Technology industry, adjusted for seniority and company size." }, "location" : "USA", "locations" : [ "USA" ], "timestamp" : "2026-06-15T08:18:26.512", "fingerprint" : "80720f44e588ec2a682745b7fbad4d52e7bd24623eaeb0bbc50d16edb2df3755", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.anz.greenhouse.io/futuresecureai/jobs/4001536201", "externalId" : "4001536201", "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "onsite" } ], "locationText" : "United States", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, NLP, LSTMs, CNNs, Transformers, Topic modelling, LLM, LangChain, LlamaIndex, RAG pipelines, GPT", "professionalSkills" : [ "Machine learning systems", "MLOps", "Data strategy", "Ethical AI", "Scalable frameworks" ], "hardSkillsList" : [ "Data analysis", "Machine learning", "LLM deployment", "Model performance tracking", "Benchmark design", "Quality assurance", "Compliance" ], "softSkillsList" : [ "Curiosity", "Courage", "Rigor", "Empathy", "Humility", "Growth mindset" ], "hardSkills" : [ { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Machine learning", "level" : "intermediate" }, { "name" : "LLM deployment", "level" : "intermediate" }, { "name" : "Model performance tracking", "level" : "intermediate" }, { "name" : "Benchmark design", "level" : "intermediate" }, { "name" : "Quality assurance", "level" : "intermediate" }, { "name" : "Compliance", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Curiosity" }, { "name" : "Courage" }, { "name" : "Rigor" }, { "name" : "Empathy" }, { "name" : "Humility" }, { "name" : "Growth mindset" } ], "majorSkills" : "Machine learning, LLM, Applied science, AI strategy", "majorSkillsList" : [ "Machine learning", "LLM", "Applied science", "AI strategy" ], "coreResponsibilities" : "Deploy machine learning models, Deploy LLM systems, Analyse structured datasets, Analyse unstructured datasets, Enhance LLM output quality, Optimise reasoning chains, Lead MLOps initiatives, Track model performance, Design benchmark, Ensure quality assurance, Ensure compliance, Influence data strategy, Influence AI strategy, Govern ethical AI, Develop scalable frameworks, Collaborate with engineering, Collaborate with product, Collaborate with stakeholders, Deliver production-ready solutions, Mentor junior data scientists, Set standards for excellence", "teamCollaboration" : "Cross-functional teams; Executive stakeholders", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "Agentic AI; NLP techniques; LLM ecosystems; RAG pipelines; Multi-agent frameworks", "domainList" : [ "agentic-ai", "nlp-techniques", "llm-ecosystems", "rag-pipelines", "multi-agent-frameworks" ], "domainSpecificKnowledge" : [ "Agentic AI", "NLP techniques", "LLM ecosystems", "RAG pipelines", "Multi-agent frameworks" ], "toolProficiency" : [ "LangChain", "LlamaIndex" ], "communicationSkills" : "Translate technical concepts; Actionable insights", "innovationCreativity" : "Creativity", "problemSolvingSkills" : "Problem solving", "qualificationsBasic" : "5+ years experience, Master's or Doctorate degree, AI sector experience, Python experience, SQL proficiency", "qualificationsPreferred" : "Doctorate preferred, Agentic AI experience, NLP techniques experience, Commercial LLM ecosystems experience, Other software languages knowledge", "workSiteFlexibility" : "Flexible", "rawDescription" : "About the Company At Future Secure AI, we're building something genuinely new — and we're looking for people bold enough to build it with us. We work at the frontier of AI, tackling big, real-world problems for global enterprises across multiple industries, armed with state-of-the-art technology and a culture that prizes courage, rigor, and relentless curiosity. Our BRAVER values aren't just words on a wall — they describe the kind of people we are and the standard we hold ourselves to every day. Our leadership team is entrepreneurial, experienced, and accessible, with an open-door policy that means you'll never be just a number here. We invest seriously in your growth because we know our success depends on yours. If you're ready to work alongside some of the brightest minds in the industry, push into uncharted territory, and do work that genuinely matters, Future Secure AI is the place for you. The Opportunity As a Sr. Data Scientist - Applied Science, you will be a key technical leader within our advanced analytics and AI group. You will design, build, and deploy sophisticated machine learning systems—particularly LLM‑driven solutions—that solve high‑value, real‑world problems for enterprise clients. You’ll be part of a culture that prizes technical excellence, creativity, and continuous learning. Beyond technical depth, you will influence strategy, mentor emerging talent, and help shape our approach to responsible and scalable AI. Your work will directly contribute to AI systems that have the potential to transform industries—and society. What You’ll Do Deploy machine learning models and LLM systems that drive meaningful impact for our products and users Analyse complex, large‑scale structured and unstructured datasets to uncover insights and opportunities Enhance LLM output quality across diverse use cases, including optimisation of multi‑step reasoning chains Lead MLOps initiatives including model performance tracking, benchmark design, quality assurance, and compliance Influence long‑term data and AI strategy, including governance, ethical AI, and scalable frameworks Collaborate closely with engineering, product, and executive stakeholders to deliver innovative, production‑ready solutions Mentor and uplift junior data scientists, setting standards for excellence About You You are a seasoned Data Scientist (5+ years) with deep hands‑on experience and a track record of delivering impactful ML and AI outcomes. You thrive in ambiguity, communicate exceptionally well, and enjoy partnering with cross‑functional teams to deliver measurable results. You balance scientific rigour with practical execution, and you bring a curiosity that keeps you constantly exploring new research—especially in the fast‑moving LLM space. You’ll be successful if you have: A Master’s or Doctorate in Data Science, Mathematics, Statistics, Computer Science or a related discipline Experience from within AI sector, ideally agentic AI Strong experience with NLP techniques: LSTMs, CNNs, transformers, topic modelling, supervised NLP Commercial experience with modern LLM ecosystems (e.g., LangChain, LlamaIndex, RAG pipelines, multi‑agent frameworks, GPT‑based systems) Python experience focused on machine learning and NLP. Knowledge of other software languages is highly beneficial Ability to translate complex technical concepts into clear, actionable insights for non‑technical stakeholders Empathy, humility, and a growth mindset—open to feedback and committed to collaboration Comfort working in an agile, fast‑evolving environment Why Join Us? A high-performance culture State-of-the-art technology Experience world-class leadership Scale of impact and purpose A competitive salary and a huge growth trajectory Work with the best in the industry Flexible work environment Diversity and creativity Disclaimer: We do not wish to be contacted by recruitment agencies. Our hiring process is managed in-house and the best way for candidates to express interest is by applying with your resume through our company website. Future Secure AI Privacy Policy At Future Secure AI, we are committed to protecting your privacy and adhering to the principles of the General Data Protection Regulation (GDPR) and the Australian Privacy Principles (APPs) under the Privacy Act 1988 (Cth). Our Privacy Policy outlines how we collect, use, share, and protect your personal data when you visit our website at www.futuresecure.ai (the \"Website\") and use our services.", "summaryDescription" : "Senior Data Scientist, Applied Science at Future Secure AI. Skills: Machine learning, LLM, Applied science, AI strategy. Deploy machine learning models. 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TGH Crystal River (TGHCR)
6201 N Suncoast Boulevard

Crystal River, 34428

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Essential Functions Perform detailed assessments to evaluate speech, language, communication, and swallowing disorders, gathering relevant patient information and history to inform treatment planning. Create tailored therapy plans based on the assessment results, clearly defining short- and long-term goals, and applying evidence-based strategies to promote patient progress. Appropriately administer therapies, exercises, and techniques that address the patient’s specific needs, ensuring the treatment process is safe, effective, and in line with the established plan of care. Regularly re-assess patients' progress and adjust treatment strategies or goals as necessary, ensuring continuous improvement and response to therapy. Ensure safe and competent operation of all equipment necessary for treatment, including any specialized tools, devices, or technologies used in speech therapy sessions. Show proficiency in the basic operation of all speech therapy equipment and follow facility protocols to ensure equipment is used correctly and safely. Maintain precise and complete documentation of all therapy sessions, including services rendered, progress made, and any adjustments to the treatment plan, to ensure proper billing and compliance with healthcare regulations. Coordinate patient schedules for therapy sessions, ensuring timely and efficient treatment delivery while managing any cancellations, rescheduling, or follow-up needs. Verbalize and accurately document any incidents, accidents, or concerns that arise during therapy sessions, following proper procedures to file incident reports and notify appropriate parties. Regularly meet with physicians, nurses, and other healthcare professionals to discuss patient progress, share information about treatment goals, and collaborate on care plans to ensure the holistic treatment of the patient. Education Master's Degree Speech and Language Pathology License/Registration - Issued by Florida or Compact State Speech-Language Pathologist Certification Basic Life Support (BLS) from American Red Cross (ARC) or American Heart Association (AHA) Work Experience and Additional Information One (1) year experience in a clinical setting. Certificate of Clinical Competency (CCC) Speech Pathology from the American Speech-Language and Hearing Association or eligibility for certification pending professional experience or equivalent within one year. Crystal River", "summaryDescription" : "Speech Language Pathologist. Skills: Speech therapy, Patient assessment, Treatment planning, Documentation. Perform detailed assessments. 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Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve. Our Commitment As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day. Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees. United States-Virginia-Arlington", "summaryDescription" : "Education and Science Principal at HDR. Skills: Project management, Team leadership. Lead a team on projects. Make client presentations", "createdAt" : "2026-06-14T02:13:41.900", "lastUpdated" : "2026-06-15T07:26:47.129", "ingestTimestamp" : "2026-06-14T02:13:41.900", "mongoId" : "6a16291c58b93c861e95a14e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 175000, "salaryAnnualMax" : 250000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Microsoft Office", "Excel", "Word", "Project", "Mentoring", "Motivational", "Organizational", "People skills", "Project management", "Team leadership", "Client presentations", "Local market", "Regional market", "Registered Architect" ], "skillCount" : 14, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Architecture", "llmIndustryConfidence" : 0.92 }, { "id" : "6949b14570f0b99d58827186", "title" : "Life and Physical Science (2026-2027 School Year)", "industry" : "Education", "salary" : { "min" : 55000.0, "max" : 75000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Life and Physical Science teacher in the Southeast High School area, adjusted for the education industry and full-time employment." }, "location" : "Southeast High School", "locations" : [ "Southeast High School", "2641 S. 127th Street East", "67207" ], "certifications" : [ "Kansas State License in Science", "KS Certification - Secondary" ], "timestamp" : "2026-06-16T03:07:22.859", "fingerprint" : "6b96d03d479f2f889e757ee58f8eb5e3161c082f4eeb914b54ed29ccf6dc5abe", "source" : "taleo", "language" : "en", "applyUrl" : "https://aa308.taleo.net/careersection/ex/jobdetail.ftl?job=80651", "externalId" : "80651", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "onsite" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "coreResponsibilities" : "Develop and administer curriculum, Promote a safe classroom environment, Develop lesson plans, Create instructional materials, Conduct ongoing assessment of student learning, Modify instructional methods, Conduct individual small group instruction, Instruct students in responsible citizenship, Acquire professional knowledge, Learn current developments, Organize record-keeping system, Maintain grading system, Maintain reporting system, Encourage parental involvement, Ensure effective communication with students, Ensure effective communication with parents, Ensure student conduct conforms to standards, Establish standards of pupil behavior, Coordinate with professional staff, Evaluate curriculum, Assess curriculum, Participate in faculty meetings, Participate in committees, Select books, Select instructional aids, Select equipment, Requisition supplies, Requisition equipment, Maintain inventory records, Supervise students in activities, Administer standardized tests", "teamCollaboration" : "Coordinate with professional staff; Participate in faculty meetings; Participate in committees", "domainKnowledge" : "High school curriculum; Teaching methods; Educational pedagogy; Differentiated instruction; Student learning styles; Federal laws regarding education; State laws regarding education; Wichita Public Schools procedures", "domainList" : [ "high-school-curriculum", "teaching-methods", "educational-pedagogy", "differentiated-instruction", "student-learning-styles", "federal-laws-regarding-education", "state-laws-regarding-education", "wichita-public-schools-procedures" ], "domainSpecificKnowledge" : [ "High school curriculum", "Teaching methods", "Educational pedagogy", "Differentiated instruction", "Student learning styles", "Federal laws regarding education", "State laws regarding education", "Wichita Public Schools procedures" ], "toolProficiency" : [ "SMART boards", "IPads", "Computers", "Copiers", "Scanners", "Fax machine" ], "communicationSkills" : "Feedback to students; Feedback to parents; Feedback to administration; Communication with students; Communication with parents", "documentationSkills" : "Documenting teaching; Documenting student progress; Documenting student activities; Documenting student outcomes; Record-keeping; Grading; Reporting", "continuousLearning" : "Attending seminars; Attending workshops; Attending professional meetings; Conducting research", "specialRequirements" : "Respond rapidly in emergency situations, Travel between schools, Travel to central offices", "qualificationsBasic" : "Kansas State License in Science, KS Certification - Secondary, Bachelor's Degree in education discipline", "qualificationsPreferred" : "Master's Degree, Successful prior teaching experience", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Job Title: Science-Sr High Position Function: Under the general supervision of the School Principal, to facilitate student success and growth in academic and interpersonal skills through implementing district approved curriculum; documenting teaching and student progress/activities/outcomes; addressing specific educational needs of individual students and by creating a flexible, safe and optimal learning environment; and providing feedback to students, parents and administration regarding student progress, expectations, goals, etc. Essential Performance Responsibilities: Develops and administers school high school curriculum consistent with school district goals and objectives Promotes a classroom environment that is safe and conducive to individualized and small group instruction, and student learning Develops lesson plans and instructional materials and translates lesson plans into learning experiences so as to best utilize the available time for instruction Conducts ongoing assessment of student learning, and modifies instructional methods to fit individual student's needs, including students with special needs; conducts individual small group instruction as needed Instructs students in the principles of responsible citizenship and other subject matters specified in applicable laws, as well as administrative regulations and procedures of the Wichita Public Schools Continues to acquire professional knowledge and learn of current developments in the educational field by attending seminars, workshops or professional meetings, or by conducting research Organizes and maintains a system for accurate and complete record-keeping, grading, and reporting for all student activities, achievement and attendance as required by district procedures and applicable laws Encourages parental involvement in students' education and ensures effective communication with students and parents Ensures that student conduct conforms with the school's standards and school district policies, and establishes and maintains standards of pupil behavior needed to achieve a functional learning atmosphere in the classroom Coordinates with other high school professional staff members, especially within grade level and specific subjects, to evaluate and assess curriculum, and participates in faculty meetings and committees Selects and requisitions appropriate books, instructional aids and other supplies and equipment and maintains inventory records Supervises students in activities that take place out of the classroom during the school day, including activities involving school transportation Administers standardized tests in accordance with district testing programs Additional Duties: Assists with additional duties as assigned by supervisor. Equipment: This position may require the ability to use SMART boards and iPads in addition to basic office equipment such as computers, copiers, scanners, and fax machine. Must always comply with WPS guidelines for equipment use. Travel: Limited travel between schools and central offices may be required. Physical and Mental Demands: Works in standard office and school building environments Ability to work outdoors during outdoor student activities Additional demands upon request of Principal, Superintendent Must be able to respond rapidly in emergency situations Knowledge, Skills, and Abilities: Knowledge of current teaching methods and educational pedagogy, as well as differentiated instruction based upon student learning styles Knowledge of high school curriculum and concepts, including all subject matters taught Knowledge of data information systems, data analysis and the formulation of action plans Knowledge of applicable federal and state laws regarding education and students Ability to use computer network system and software applications as needed Ability to organize and coordinate work Ability to organize and coordinate work Ability to engage in self-evaluation with regard to performance and professional growth Ability to establish and maintain cooperative working relationships with others contacted in the course of work Interrelations: Contact with personnel within the district and with customers and vendors Will be working under the direct supervision of the department supervisor in order to complete day to day tasks Will be working with a diverse population requiring the ability to handle all situations with tact and diplomacy Must understand and respond appropriately to customer needs and maintain a positive attitude with all customers and colleagues Expected to interact with all internal and external customers in a friendly, professional manner and provide quick, responsive customer service Employee Punctuality and Appearance: In order for schools to operate effectively, employees are expected to perform all assigned duties and work all scheduled hours during each designated workday, unless the employee has received approved leave Any deviation from assigned hours must have prior approval from the employee's supervisor or building administrator All employees are required to report to work dressed in a manner that reflects a positive image of USD 259 and is appropriate for their position Qualification Profile: Kansas State License in Science KS Certification - Secondary Bachelor's Degree from an accredited college or university in education discipline applicable to teaching assignment Master's Degree preferred Successful prior teaching experience for the appropriate grade level preferred. FLSA Status: Exempt", "summaryDescription" : "Life and Physical Science (2026-2027 School Year). Develop and administer curriculum. Promote a safe classroom environment", "createdAt" : "2026-06-14T18:50:24.445", "lastUpdated" : "2026-06-16T03:07:22.859", "ingestTimestamp" : "2026-06-14T18:50:24.445", "mongoId" : "6949b14570f0b99d58827186", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 55000, "salaryAnnualMax" : 75000, "salaryBand" : "50k-75k", "hasSalary" : true, "allSkills" : [ "High school curriculum", "Teaching methods", "Educational pedagogy", "Differentiated instruction", "Student learning styles", "Federal laws regarding education", "State laws regarding education", "Wichita Public Schools procedures", "Kansas State License in Science", "KS Certification - Secondary", "SMART boards", "IPads", "Computers", "Copiers", "Scanners", "Fax machine" ], "skillCount" : 16, "jobCategory" : "general", "jobSubcategory" : "general", "seniorityLevel" : "Mid", "dataQualityScore" : 0.6666667, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Education", "llmIndustryConfidence" : 0.98 }, { "id" : "69ce5e5f9bc74574cb67a511", "title" : "Pathologist Speech Language", "industry" : "Education", "salary" : { "min" : 75000.0, "max" : 110000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Pathologist Speech Language in Sugar Land, United States, adjusted for the Education industry." }, "location" : "TEXAS-SUGAR LAND-TECHNICAL EDUCATION CENTER", "locations" : [ "TEXAS-SUGAR LAND-TECHNICAL EDUCATION CENTER", "
TECHNICAL EDUCATION CENTER (3)
540 DULLES AVENUE
SUGAR LAND, 77478

" ], "certifications" : [ "ASHA Certification", "TEA certification" ], "timestamp" : "2026-06-16T03:28:16.643", "fingerprint" : "4102728f37c8f29825e8926b707c871d2a12ce4473c2bbaa978de3759645df50", "source" : "taleo", "language" : "en", "applyUrl" : "https://aa210.taleo.net/careersection/ex/jobdetail.ftl?job=187632", "externalId" : "187632", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Sugar Land", "state" : "Texas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "29.6196787,-95.6349463" } ], "locationText" : "Sugar Land, Texas, United States", "technicalSkills" : "Windows Operating System, Microsoft Office, Microsoft Word, Microsoft Excel, Microsoft PowerPoint", "professionalSkills" : [ "Speech evaluation", "Therapeutic intervention", "Medicaid billing", "Report writing", "Treatment plan development" ], "hardSkillsList" : [ "Speech assessment", "Data interpretation", "Data-based decision making", "Student outcomes monitoring" ], "hardSkills" : [ { "name" : "Speech assessment", "level" : "intermediate" }, { "name" : "Data interpretation", "level" : "intermediate" }, { "name" : "Data-based decision making", "level" : "intermediate" }, { "name" : "Student outcomes monitoring", "level" : "intermediate" } ], "majorSkills" : "Speech Language Pathology, Individualized Education Plans, ARD meetings", "majorSkillsList" : [ "Speech Language Pathology", "Individualized Education Plans", "ARD meetings" ], "coreResponsibilities" : "Conduct evaluations to determine speech/language disability, Determine educational need for specialized instruction, Provide recommendations to support communication, Develop individualized education plans, Conduct ARD meetings, Ensure appropriate programming for students, Provide therapeutic intervention, Provide classroom support, Eliminate or reduce communication problems/impairments, Maintain compliance of all federal / local timelines, Maintain individual records, Maintain Medicaid billing, Maintain state performance plan indicators 7, 11, &, Provide services consistent with speech goals, Develop functional individualized education plans, Gather and interpret data, Conduct assessments to identify communication disorders, Establish eligibility for services, Inform instruction and intervention, Plan ARD committee meetings, Conduct ARD committee meetings, Participate in ARD committee meetings, Plan staffings, Conduct staffings, Participate in staffings, Plan parent meetings, Conduct parent meetings, Participate in parent meetings, Develop individualized education program (IEP), Develop treatment plan/therapy log, Support student services, Collaborate with other professionals, Collaborate with classroom teachers, Offer assistance in addressing linguistic foundations, Offer assistance in addressing metalinguistic foundations, Compile reports, Maintain reports, File reports, Submit reports, Compile records, Maintain records, File records, Submit records, Compile documents, Maintain documents, File documents, Submit documents, Engage in continuing education experiences, Engage in professional development, Supervise licensed assistants, Supervise clinical fellowship year interns, Supervise students", "teamCollaboration" : "Collaborate with other professionals; Collaborate with classroom teachers", "domainKnowledge" : "Speech Language Pathology; Communication disorders; Educational program; Least restrictive environment; Evidence based practices; Federal mandates; State mandates; Local board policy; Curriculum learning; Students with disabilities; Bodily fluids; De-escalation techniques; Restraint techniques", "domainList" : [ "speech-language-pathology", "communication-disorders", "educational-program", "least-restrictive-environment", "evidence-based-practices", "federal-mandates", "state-mandates", "local-board-policy", "curriculum-learning", "students-with-disabilities", "bodily-fluids", "de-escalation-techniques", "restraint-techniques" ], "domainSpecificKnowledge" : [ "Speech Language Pathology", "Communication disorders", "Educational program", "Least restrictive environment", "Evidence based practices", "Federal mandates", "State mandates", "Local board policy", "Curriculum learning", "Students with disabilities", "Bodily fluids", "De-escalation techniques", "Restraint techniques" ], "toolProficiency" : [ "Windows", "Microsoft Office", "Microsoft Word", "Microsoft Excel", "Microsoft PowerPoint" ], "communicationSkills" : "Verbal communication; Written communication", "documentationSkills" : "Medicaid billing; Report writing; Treatment plan development; Therapy log development", "continuousLearning" : "Continuing education experiences; Professional development", "problemSolvingSkills" : "Solve complex problems", "specialRequirements" : "Occasional walking, Occasional standing, Occasional sitting, Occasional bending, Occasional stooping, Occasional kneeling, Occasional crouching, Occasional crawling, Lifting less than 40 pounds, Use hands to finger, Handle objects, Feel objects, Use tools, Reach with hands, Talk or hear, Close vision, Color vision, Adjust focus, Attendance at conferences, Attendance at professional development, Normal safety precautions, Prolonged hours, Irregular hours, Maintain emotional control, Exposure to bodily fluids, Physically restraining students, Travel to various campuses, Travel to district meeting sites, Work some overtime", "outcomesObjectives" : "Support communication; Monitor student outcomes", "qualificationsBasic" : "Master's Degree Speech Language Pathology or related field, Bachelor's Degree with TEA certification in Speech and Language Therapy or Speech and Hearing Therapy, ASHA Certification Clinical Fellowship Year and/or Master's degree with TX license, Valid Texas license as a Speech Pathologist granted by Texas Board of Examiners for Speech-Language Pathology or Audiology, Proficient in using Windows Operating System, Proficient in Microsoft Office applications, Must be able to effectively communicate information and ideas both verbally and in writing, Must have organizational skills, Must have communication skills, Must have interpersonal skills, Must be able to solve complex problems, Must be able to handle stressful situations, Must be able to administer, score, and interpret standardized speech assessment instruments for children", "qualificationsPreferred" : "Minimum of 1 year experience as a Speech Language Pathologist in public schools", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Job Overview The Pathologist Speech Language will conduct evaluations to determine a speech/language disability condition, an educational need for specialized instruction, and provide recommendations to support communication. The incumbent will develop individualized education plans and conduct ARD meetings to ensure appropriate programming for students within the least restrictive environment. The Pathologist Speech Language will provide therapeutic intervention and classroom support to eliminate or reduce communication problems/impairments that interfere with the students' ability to derive full benefit from the educational program. The incumbent will maintain compliance of all federal / local timelines, individual records, Medicaid billing, and state performance plan indicators 7, 11, & 12. Position Description Essential Duties and Responsibilities Service Delivery Plan and provide services that are appropriate and consistent with speech goals contained in the individual education plan (IEP) Develop functional individualized education plans based on the communication needs of the student Provide intervention that is appropriate to the age and learning needs of each individual student Gather and interpret data with individual students, as well as, overall program evaluation to support data-based decision making and monitor student outcomes Compliance Comply with and meet federal and state mandates and local board policy Conduct assessments in collaboration with others that help to identify students with communication disorders as well as to establish eligibility and inform instruction and intervention, consistent with evidence based practices Plan, conduct, and/or participate in ARD committee meetings, staffings, parent meetings, etc. Comply with and meet federal and state mandates and local board policy (i.e. activities may include individualized education program (IEP) development, Medicaid billing, report writing, and treatment plan/therapy log development Administrative/ Campus Support Support student services provided by the speech language therapist Collaborate with other professional/classroom teachers and offer assistance in addressing the linguistic and metalinguistic foundations of curriculum learning for students with disabilities Compile, maintain, and file/submit all reports, records, and other documents required Engage in continuing education experiences and professional development to enhance the skills / knowledge necessary to serve a diverse student body Supervisory Responsibilities ASHA CCC/SLP's: Supervise licensed assistants in speech-language pathology, clinical fellowship year interns, and students as needed Qualification Requirements To perform this job successfully, an individual must be able to perform each of the above essential duties satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or abilities, required unless otherwise stated as preferred. Reasonable accommodations may be made to enable individuals with disabilities to perform the essentials functions. Master's Degree Speech Language Pathology or related field Bachelor's Degree with TEA certification in Speech and Language Therapy or Speech and Hearing Therapy also acceptable ASHA Certification Clinical Fellowship Year and/or Master's degree with TX license accepted Valid Texas license as a Speech Pathologist granted by Texas Board of Examiners for Speech-Language Pathology or Audiology Minimum of 1 year experience as a Speech Language Pathologist in public schools preferred Must be proficient in using Windows Operating System as well as Microsoft Office applications (Microsoft Word, Excel, and PowerPoint) Must be able to effectively communicate information and ideas both verbally and in writing Must have strong organizational, communication and interpersonal skills Must be able to solve complex problems and handle stressful situations Must be able to administer, score, and interpret standardized speech assessment instruments for children Physical Requirements/Working Conditions The work environment characteristics and physical demands described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Work is performed in classrooms, offices, work stations and meeting rooms. The position requires occasional walking, standing, sitting, bending, stooping, kneeling, crouching, crawling, and lifting/carrying work related items weighing less than 40 pounds, such as books, papers and presentation materials. The employee is regularly required to use hands to finger, handle, or feel objects, tools, or controls; reach with hands and arms; and talk or hear. Specific vision abilities required by this job include close vision, color vision, and the ability to adjust focus. Attendance at conferences and professional development is required. Work involves everyday risks and discomforts which require normal safety precautions when operating equipment or performing job duties. May work prolonged or irregular hours and must be able to maintain emotional control under stress. Additional Information This position may have exposure to bodily fluids and the employee must be capable of physically restraining students when necessary following the approved de-escalation/restraint techniques. This position requires travel to various campuses and district meeting sites. This position may be required to work some overtime as defined by the needs of the department. This position is funded by grant funds. This position may be discontinued if grant funds are no longer available. TEXAS-SUGAR LAND", "summaryDescription" : "Pathologist Speech Language. Skills: Speech Language Pathology, Individualized Education Plans, ARD meetings. Conduct evaluations to determine speech/language disability. Determine educational need for specialized instruction", "createdAt" : "2026-06-14T19:47:29.489", "lastUpdated" : "2026-06-16T03:28:16.643", "ingestTimestamp" : "2026-06-14T19:47:29.489", "mongoId" : "69ce5e5f9bc74574cb67a511", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 75000, "salaryAnnualMax" : 110000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Speech assessment", "Data interpretation", "Data-based decision making", "Student outcomes monitoring", "Speech Language Pathology", "Individualized Education Plans", "ARD meetings", "Speech evaluation", "Therapeutic intervention", "Medicaid billing", "Report writing", "Treatment plan development", "Communication disorders", "Educational program", "Least restrictive environment", "Evidence based practices", "Federal mandates", "State mandates", "Local board policy", "Curriculum learning", "Students with disabilities", "Bodily fluids", "De-escalation techniques", "Restraint techniques", "ASHA Certification", "TEA certification", "Windows", "Microsoft Office", "Microsoft Word", "Microsoft Excel", "Microsoft PowerPoint" ], "skillCount" : 31, "jobCategory" : "general", "jobSubcategory" : "general", "seniorityLevel" : "Mid", "dataQualityScore" : 0.5555556, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Education", "llmIndustryConfidence" : 0.98 }, { "id" : "69fda4e64c40e2acd1b99af2", "title" : "Applied Science Manager, Sponsored Products and Brands", "company" : "Amazon.com Services LLC", "industry" : "Applied Science, Advertising", "salary" : { "min" : 202000.0, "max" : 273600.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "timestamp" : "2026-06-15T01:47:42.669", "fingerprint" : "d8a90b9d636b94a49694c17867b2218cf0e64f07a91af868d1a5132c7bd992a4", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10412277/apply", "externalId" : "1e929245-5acc-409b-a774-775f10dc2e73", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "ML, NLP, Information Retrieval, Analytics, Java, C++, Python, LLM, RAG", "professionalSkills" : [ "Scientific excellence", "Customer obsession", "Ownership", "Scientific vision", "Roadmap planning", "Model evaluation", "Prompt optimization", "A/B testing", "Drift monitoring" ], "hardSkillsList" : [ "Model evaluation", "Prompt engineering", "LLM fine-tuning", "Programmatic prompt optimization" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Model evaluation", "level" : "intermediate" }, { "name" : "Prompt engineering", "level" : "intermediate" }, { "name" : "LLM fine-tuning", "level" : "intermediate" }, { "name" : "Programmatic prompt optimization", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Generative AI, Applied Science, Model Evaluation, Machine Learning", "majorSkillsList" : [ "Generative AI", "Applied Science", "Model Evaluation", "Machine Learning" ], "coreResponsibilities" : "Lead talent team, Mentor talent team, Grow talent team, Foster culture scientific excellence, Foster culture customer obsession, Foster culture ownership, Own scientific vision, Own multi-quarter roadmap, Design evaluation frameworks, Deliver evaluation frameworks, Lead development optimization engine, Refine prompts programmatically, Generate synthetic training pairs, Compose agent decomposition strategies, Establish offline-to-online consistency, Establish A/B testing discipline, Establish drift monitoring, Communicate scientific vision, Communicate research breakthroughs, Communicate business outcomes, Drive alignment objectives", "teamCollaboration" : "Applied scientists; Machine learning engineers; Senior leadership; Broader Amazon Advertising", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Brand intelligence; Agentic systems; LLM-based agents; Orchestrator-worker patterns; Retrieval-augmented generation; Multi-agent orchestration; Sponsored products; Sponsored brands", "domainList" : [ "brand-intelligence", "agentic-systems", "llm-based-agents", "orchestrator-worker-patterns", "retrieval-augmented-generation", "multi-agent-orchestration", "sponsored-products", "sponsored-brands" ], "domainSpecificKnowledge" : [ "Brand intelligence", "Agentic systems", "LLM-based agents", "Orchestrator-worker patterns", "Retrieval-augmented generation", "Multi-agent orchestration", "Sponsored products", "Sponsored brands" ], "toolProficiency" : [ "LLM-as-Judge" ], "communicationSkills" : "Executive presentations", "innovationCreativity" : "Generative AI technologies", "problemSolvingSkills" : "Diagnose underperformance; Root cause analysis", "outcomesObjectives" : "Attains accuracy targets; Enables forward evaluation; Establishes autonomous loop; Scale quality across skills", "qualificationsBasic" : "4+ years applied research, 3+ years management experience, 3+ years ML models business application, PhD or Master's degree, 6+ years applied research, Knowledge of ML, Knowledge of NLP, Knowledge of Information Retrieval, Knowledge of Analytics, Experience programming Java, Experience programming C++, Experience programming Python", "qualificationsPreferred" : "Experience recommender systems, Experience personalization, Ph.D. computer science, Ph.D. machine learning, Ph.D. engineering, Master's degree quantitative field, 4+ years quantitative field, Publications top-tier conferences, Publications top-tier journals, 5+ years management experience, Hands-on LLM agentic systems, Experience LLM fine-tuning, Experience prompt engineering, Experience programmatic prompt optimization", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. As the Applied Science Manager for the Continuous Model Evaluation and Learning workstream, you will own the quality backbone for this agentic brand-intelligence system. You will lead a mix of applied scientists and engineers who define what \"good\" looks like for each brand skill, instrument the system to measure it, diagnose why skills underperform, and close the loop by generating, validating, and deploying improvements. You will deliver the evaluation and remediation framework that attains accuracy targets, enables forward evaluation for skills as they develop, and establishes the autonomous detect-diagnose-remediate loop that lets us scale quality across all brand skills and multiple advertiser-facing surfaces. This is a business-critical, greenfield initiative within SPB. You will set the scientific charter, grow the talent on your team, and ship the framework that every other brand-intelligence workstream depends on. Key job responsibilities - Lead, mentor, and grow the talent on a team composed of applied scientists and machine learning engineers, fostering a culture of scientific excellence, customer obsession, and ownership. - Own the scientific vision and multi-quarter roadmap for continuous model evaluation and learning across the brand-intelligence system. - Design and deliver evaluation frameworks for agentic brand-intelligence skills, including LLM-as-Judge rubrics, multi-model ensemble judging, gold-set construction, and calibration against human evaluators. - Lead development of the optimization engine that programmatically refines prompts, generates synthetic training pairs, and composes agent decomposition strategies (orchestrator-worker patterns) when single-agent skills hit complexity limits. - Establish rigorous offline-to-online consistency, A/B testing discipline, and drift monitoring so that quality improvements generalize to production traffic. - Communicate scientific vision, research breakthroughs, and business outcomes to senior leadership, and drive alignment with broader Amazon Advertising objectives. Basic Qualifications: - 4+ years of applied research experience - 3+ years of scientists or machine learning engineers management experience - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Knowledge of ML, NLP, Information Retrieval and Analytics - Experience programming in Java, C++, Python or related language Preferred Qualifications: - Experience working on recommender systems or personalization within search, e-commerce, shopping, advertising or other related fields - Ph.D. in computer science, machine learning, engineering, or related fields, or Master's degree and 4+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience - Have publications at top-tier peer-reviewed conferences or journals - 5+ years of scientists or machine learning engineers management experience - Hands-on experience designing, deploying, and evaluating LLM-based agentic systems, including tool use, multi-step planning and reasoning, retrieval-augmented generation (RAG), and multi-agent orchestration (orchestrator-worker, swarm, critic-actor patterns). - Experience with large-scale LLM fine-tuning (SFT, RLHF, DPO), prompt engineering, and programmatic prompt optimization frameworks. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, NY, New York - 202,200.00 - 273,600.00 USD annually USA, WA, SEATTLE - 183,800.00 - 248,700.00 USD annually", "summaryDescription" : "Applied Science Manager, Sponsored Products and Brands at Amazon.com Services LLC. Skills: Generative AI, Applied Science, Model Evaluation, Machine Learning. Lead talent team. Mentor talent team", "postedDate" : "2026-06-13T07:29:57.873", "createdAt" : "2026-06-13T07:29:57.873", "lastUpdated" : "2026-06-15T01:47:42.669", "ingestTimestamp" : "2026-06-13T07:29:57.873", "mongoId" : "69fda4e64c40e2acd1b99af2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10412277/apply", "salaryAnnualMin" : 202000, "salaryAnnualMax" : 273600, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Model evaluation", "Prompt engineering", "LLM fine-tuning", "Programmatic prompt optimization", "Leadership", "Mentoring", "Generative AI", "Applied Science", "Model Evaluation", "Machine Learning", "Scientific excellence", "Customer obsession", "Ownership", "Scientific vision", "Roadmap planning", "Prompt optimization", "A/B testing", "Drift monitoring", "Brand intelligence", "Agentic systems", "LLM-based agents", "Orchestrator-worker patterns", "Retrieval-augmented generation", "Multi-agent orchestration", "Sponsored products", "Sponsored brands", "LLM-as-Judge" ], "skillCount" : 27, "jobCategory" : "other", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Advertising" }, { "id" : "6a305118f292fd229cef9905", "title" : "Director, Clinical Science", "industry" : "Product", "salary" : { "min" : 206000.0, "max" : 268000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "US", "locations" : [ "US" ], "timestamp" : "2026-06-16T13:19:11.378", "fingerprint" : "de3f8f841882d55eea7acdf15d04cda73ae529129f88b4fdc0e4d2b1258bc8f7", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/671cb820-36a1-4180-b5d4-0f04cbd8e8bd/apply", "externalId" : "671cb820-36a1-4180-b5d4-0f04cbd8e8bd", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 6, "experienceMaxYears" : 8, "experienceLevel" : "Director", "professionalSkills" : [ "Project management" ], "hardSkillsList" : [ "Clinical trial design", "Clinical trial execution", "Clinical trial analysis", "Data interpretation", "Scientific data communication" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Clinical trial design", "level" : "intermediate" }, { "name" : "Clinical trial execution", "level" : "intermediate" }, { "name" : "Clinical trial analysis", "level" : "intermediate" }, { "name" : "Data interpretation", "level" : "intermediate" }, { "name" : "Scientific data communication", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "coreResponsibilities" : "Support design of clinical studies, Implement clinical studies, Contribute to analysis of data, Contribute to interpretation of data, Contribute to reporting of data, Lead preparation of clinical documents, Lead preparation of study reports, Lead preparation of regulatory submission components, Lead preparation of protocols, Lead preparation of SAPs, Lead preparation of briefing books, Lead preparation of clinical summaries, Ensure compliance with GCPs, Develop scientific materials, Present scientific materials, Build relationships with external collaborators, Maintain relationships with external collaborators", "teamCollaboration" : "Cross-functional teams; External collaborators; Investigators; Alliance partners; Key opinion leaders; Multidisciplinary teams; External stakeholders", "projectManagementSkills" : [ "Project management" ], "domainKnowledge" : "Human pharmacology; Nephrology; Rare disease; GCPs; INDs; NDAs; BLAs", "domainList" : [ "human-pharmacology", "nephrology", "rare-disease", "gcps", "inds", "ndas", "blas" ], "domainSpecificKnowledge" : [ "Human pharmacology", "Nephrology", "Rare disease", "GCPs", "INDs", "NDAs", "BLAs" ], "communicationSkills" : "Scientific data communication; Presenting at scientific forums; Presenting at medical forums", "documentationSkills" : "Clinical documentation", "specialRequirements" : "Willingness to travel domestically and internationally", "qualificationsBasic" : "Advanced degree required (PhD, PharmD, and/or MD), 6–8+ years of experience in pharmaceutical or biotechnology industry, Experience in academic or clinical research settings, Excellent ability to interpret, synthesize, and communicate complex clinical and scientific data, Organizational skills, Ability to manage multiple priorities, Exceptional written communication skills, Exceptional verbal communication skills, Interpersonal skills, High attention to detail, Adaptability, Flexibility", "qualificationsPreferred" : "Experience in nephrology, Experience in rare disease, Exposure to early-phase studies, Knowledge of regulatory processes, Prior involvement in INDs, Prior involvement in NDAs, Prior involvement in BLAs, Prior involvement in regulatory submissions", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "## Accountabilities Support the design and implementation of clinical studies, including human pharmacology studies, ensuring scientifically sound methodologies and alignment with development objectives. Contribute to the analysis, interpretation, and reporting of clinical trial data for safety, efficacy, and mechanism of action insights. Lead the preparation of clinical documents and deliverables, including study reports, regulatory submission components (INDs, NDAs, BLAs), protocols, SAPs, briefing books, and clinical summaries. Ensure compliance with Good Clinical Practices (GCPs) across study design, execution, and documentation activities. Collaborate with cross-functional teams including statistics, clinical operations, and regulatory affairs to support data analysis, interpretation, and submission readiness. Develop and present scientific materials such as conference presentations, manuscripts, and clinical trial registry summaries. Build and maintain strong relationships with external collaborators, including investigators, alliance partners, and key opinion leaders to support clinical development activities. Requirements: Advanced degree required (PhD, PharmD, and/or MD) in a relevant life sciences discipline; specialization or experience in nephrology or rare disease strongly preferred. 6–8+ years of experience in the pharmaceutical or biotechnology industry, or equivalent experience in academic or clinical research settings. Demonstrated experience in clinical trial design, execution, and analysis, including exposure to early-phase (human pharmacology) studies preferred. Strong knowledge of regulatory processes and prior involvement in INDs, NDAs, BLAs, and regulatory submissions highly desirable. Excellent ability to interpret, synthesize, and communicate complex clinical and scientific data. Strong organizational and project management skills with the ability to manage multiple priorities in a fast-paced, cross-functional environment. Exceptional written and verbal communication skills, including experience presenting at scientific and medical forums. Strong interpersonal skills with the ability to collaborate effectively across multidisciplinary teams and external stakeholders. High attention to detail, adaptability, and flexibility in response to evolving clinical and regulatory requirements. Willingness to travel domestically and internationally as needed (up to 15%). Benefits: Competitive base salary range of $206,000 – $268,000, plus short-term incentive and long-term equity compensation opportunities. Comprehensive health, dental, vision, life, and disability insurance for employees and eligible dependents. Retirement savings plan with employer matching contributions. Generous paid time off and holidays, supporting work-life balance and well-being. Access to employee wellness programs and support resources. Opportunity to contribute to cutting-edge clinical programs in rare disease and nephrology. High-impact scientific leadership role with strong visibility across clinical development and regulatory functions. Flexible work environment with collaboration across global teams and partners. ## 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" : "Director, Clinical Science. Support design of clinical studies. Implement clinical studies", "postedDate" : "2026-06-15T10:11:33.948", "createdAt" : "2026-06-15T10:11:33.948", "lastUpdated" : "2026-06-16T13:19:11.378", "ingestTimestamp" : "2026-06-16T03:20:03.228", "mongoId" : "6a305118f292fd229cef9905", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 206000, "salaryAnnualMax" : 268000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Clinical trial design", "Clinical trial execution", "Clinical trial analysis", "Data interpretation", "Scientific data communication", "Leadership", "Project management", "Human pharmacology", "Nephrology", "Rare disease", "GCPs", "INDs", "NDAs", "BLAs" ], "skillCount" : 14, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Director", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Biotech", "llmIndustryConfidence" : 0.98 }, { "id" : "69f519c94c40e2acd1eb1c2b", "title" : "Applied Scientist, Ads Science and Analysis Team", "company" : "Amazon.com Services LLC", "industry" : "Finance Accounting, Applied Science, finance", "salary" : { "min" : 172400.0, "max" : 223400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "timestamp" : "2026-06-15T05:15:14.267", "fingerprint" : "8b5ccd103231c5fe09ee2f06465028dbdbe8c1de405c30d2faa8023468d1b4e6", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10409013/apply", "externalId" : "4e9510d0-50d6-473f-a0f0-56ecab0d145c", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Java, C++, Python", "professionalSkills" : [ "Data analysis", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Data engineering", "Machine learning", "AI" ], "hardSkillsList" : [ "Data mining", "Numerical optimization", "Data structures", "Algorithms", "Distributed computing", "High-performance computing" ], "hardSkills" : [ { "name" : "Data mining", "level" : "intermediate" }, { "name" : "Numerical optimization", "level" : "intermediate" }, { "name" : "Data structures", "level" : "intermediate" }, { "name" : "Algorithms", "level" : "intermediate" }, { "name" : "Distributed computing", "level" : "intermediate" }, { "name" : "High-performance computing", "level" : "intermediate" } ], "majorSkills" : "Data science, Machine learning, Analytics", "majorSkillsList" : [ "Data science", "Machine learning", "Analytics" ], "coreResponsibilities" : "Analyze data trends, Present papers to senior leaders, Formalize analytics approach to Ads auctions, Identify, standardize, and operationalize KPIs, Partner with engineering teams to define data logging, Validate financial models through analysis, Develop and own ad revenue and supply intelligence, Analyze data and present papers and ongoing reports", "teamCollaboration" : "Partner with engineering teams; Work closely with business leaders; Work closely with engineers", "domainKnowledge" : "Advertising data; Bidding algorithms; Targeting systems; Relevance systems; Supply strategy; Ads auctions; Ad serving systems; Ad revenue", "domainList" : [ "advertising-data", "bidding-algorithms", "targeting-systems", "relevance-systems", "supply-strategy", "ads-auctions", "ad-serving-systems", "ad-revenue" ], "domainSpecificKnowledge" : [ "Advertising data", "Bidding algorithms", "Targeting systems", "Relevance systems", "Supply strategy", "Ads auctions", "Ad serving systems", "Ad revenue" ], "communicationSkills" : "Presentations", "problemSolvingSkills" : "Data analysis", "outcomesObjectives" : "Improve performance of bidding algorithms; Advance supply strategy; Evaluate adoption and impact of feature releases; Achieve advertiser goals; Improve fill rate; Inform business development roadmaps; Inform engineering roadmaps; Measure performance of systems; Inform business priorities; Optimize data logging; Allow data interoperability", "qualificationsBasic" : "Master's degree and 5+ years CS, CE, ML experience, 3+ years building models for business application, Experience programming in Java, C++, Python, Experience in algorithms and data structures, Experience in parsing, Experience in numerical optimization, Experience in data mining, Experience in parallel and distributed computing, Experience in high-performance computing", "qualificationsPreferred" : "PhD preferred, Experience using Unix/Linux, Experience in professional software development", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are seeking a scientist to further the development and application of analytics methods to examine the complex data flows of Amazon Ads and to translate deep-dives into actionable insights for our product teams. In this role you will develop new tools to analyze our advertising data to help improve the performance of our bidding algorithms, targeting and relevance systems, help advance our supply strategy, and evaluate the adoption and impact of feature releases. Key job responsibilities - Analyze data trends regarding supply, optimization, ad load, and advertising mix effects that affect advertiser performance and contribute to achieving advertiser goals - Present papers to senior leaders on issues like feature development impact on identity recognition rates, and changes of ad selection systems to improve fill rate highlighting insights that will inform our business development and engineering roadmaps - Formalize our analytics approach to Ads auctions by analyzing bid spreads, auction depth, and simulating impacts of potential auction structure changes - Identify, standardize, and operationalize KPIs to effectively measure the performance of all systems involved in ad serving, and use trend insights to inform business priorities - Partner with engineering teams to define data logging requirements and getting these prioritized in engineering roadmaps - Validate financial models through analysis - Develop and own ad revenue and supply intelligence analytics decks that provide ongoing deep-dives A day in the life The Ads Scientist will work closely with business leaders and engineers on developing common data architecture that will optimize our data logging at different grains, and will allow data interoperability from bid flow to optimization to campaign delivery. The scientist will then analyze the data and present papers and ongoing reports on actionable insights. About the team At Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future. Basic Qualifications: - PhD, or Master's degree and 5+ years of CS, CE, ML or related field experience - 3+ years of building models for business application experience - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications: - Experience using Unix/Linux - Experience in professional software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, Palo Alto - 171,600.00 - 222,200.00 USD annually USA, NY, New York - 172,400.00 - 223,400.00 USD annually USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually", "summaryDescription" : "Applied Scientist, Ads Science and Analysis Team at Amazon.com Services LLC. Skills: Data science, Machine learning, Analytics. Analyze data trends. Present papers to senior leaders", "postedDate" : "2026-06-13T09:49:27.371", "createdAt" : "2026-06-13T09:49:27.371", "lastUpdated" : "2026-06-15T05:15:14.267", "ingestTimestamp" : "2026-06-13T09:49:27.371", "mongoId" : "69f519c94c40e2acd1eb1c2b", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10409013/apply", "salaryAnnualMin" : 172400, "salaryAnnualMax" : 223400, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data mining", "Numerical optimization", "Data structures", "Algorithms", "Distributed computing", "High-performance computing", "Data science", "Machine learning", "Analytics", "Data analysis", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Data engineering", "AI", "Advertising data", "Bidding algorithms", "Targeting systems", "Relevance systems", "Supply strategy", "Ads auctions", "Ad serving systems", "Ad revenue" ], "skillCount" : 23, "jobCategory" : "sales", "dataQualityScore" : 0.8888889, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "69d5e4982beec4dd3d931b0e", "title" : "Applied Science Manager GenAI, CreativeX", "company" : "Amazon.com Services LLC", "industry" : "Machine Learning Science, Applied Science, Advertising", "salary" : { "min" : 183800.0, "max" : 248700.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T00:52:14.784", "fingerprint" : "352d020ee9e5b4b17cd9763460108745db82e9e725549d58c15c8fe992d87fca", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10384255/apply", "externalId" : "34fc8e8c-3c7a-4aeb-98ec-985f28e4a9e2", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "ML, NLP, Information Retrieval, Analytics, Agentic AI, Generative multi-modal models, LLMs, Computer vision, Latent diffusion, Foundational models", "professionalSkills" : [ "Science management", "Technical management" ], "hardSkillsList" : [ "AI product development", "AI product deployment", "AI product management" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "AI product development", "level" : "intermediate" }, { "name" : "AI product deployment", "level" : "intermediate" }, { "name" : "AI product management", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Generative AI, Applied Science Management, LLMs, Computer Vision", "majorSkillsList" : [ "Generative AI", "Applied Science Management", "LLMs", "Computer Vision" ], "coreResponsibilities" : "Manage and lead science and AI software talent, Deliver world-class innovative generative AI, Set the scientific agenda, Collaborate with org's leadership, Collaborate with product managers, Collaborate with engineering, Collaborate with relevant stakeholders, Mentor scientists, Contribute with patent submissions, Contribute with peer-reviewed research publications, Contribute with bar raising hiring, Establish mechanisms for science management, Establish mechanisms for brainstorming, Establish mechanisms for monitoring, Establish mechanisms for validation of outputs, Hire and develop technical talent, Write strategy and alignment documents, Present strategy, Present methods, Present results to senior leadership, Lead and mentor technical talent, Engage and align with product, Engage and align with engineering, Engage and align with other stakeholders, Dive deep on advertiser anecdotes, Define and deliver mechanisms for innovation, Engage with senior leadership on priorities, Engage with senior leadership on opportunities", "teamCollaboration" : "Close-knit team; Cross-functional teams; Senior leadership", "domainKnowledge" : "Generative AI for advertising; Latent-diffusion models; Large language models; Computer vision; Reinforced learning; Image synthesis; Video synthesis; Audio synthesis; Agentic AI; Multi-modal models; Foundational models", "domainList" : [ "generative-ai-for-advertising", "latent-diffusion-models", "large-language-models", "computer-vision", "reinforced-learning", "image-synthesis", "video-synthesis", "audio-synthesis", "agentic-ai", "multi-modal-models", "foundational-models" ], "domainSpecificKnowledge" : [ "Generative AI for advertising", "Latent-diffusion models", "Large language models", "Computer vision", "Reinforced learning", "Image synthesis", "Video synthesis", "Audio synthesis", "Agentic AI", "Multi-modal models", "Foundational models" ], "communicationSkills" : "Present strategy; Present methods; Present results", "documentationSkills" : "Write strategy documents", "innovationCreativity" : "Innovate on behalf of customers; Product and technical innovations; Experiment and innovate", "problemSolvingSkills" : "Dive deep on advertiser anecdotes", "outcomesObjectives" : "Grow incremental sales; Help shoppers discover products; Meet advertiser business objectives; Build sustainable business; Continuously innovate on behalf of customers; Drive long-term growth", "qualificationsBasic" : "3+ years scientists or ML engineers management experience, Knowledge of ML, NLP, Information Retrieval and Analytics, PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, Experience developing, deploying and managing AI products at scale", "qualificationsPreferred" : "Experience leading technical initiatives, Experience writing strategy documents for executive audiences, Background in Agentic AI, Machine Learning, Computer Science", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (images, videos) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), reinforced learning (RL), and image + video and audio synthesis. We are looking for a talented Applied Science Manager who can help set the scientific agenda and provide best in class mentoring within the scope of advancing advertiser-facing generative AI. You will help lead scientists within a close-knit team who is highly collaborative and at the top of their respective fields. Our science team is adept at a variety of skills, especially with agentic AI, generative multi-modal models, LLMs, computer vision, latent diffusion and related foundational models. As a Science Manager you will: * Help set the scientific agenda in collaboration with org's leadership, product managers, engineering and relevant stakeholders. * You will guide the team to be world-class at developing large scale generative AI for advertising. * Help mentor scientists towards also contributing with patent submissions, potential peer-reviewed research publications and bar raising hiring. * Contribute and help establish mechanisms for science management, brainstorming, monitoring and validation of outputs. * Hire and develop the best science talent at Amazon. * Present strategy, methods and results to senior leadership. Why you will love this opportunity Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Key job responsibilities *Manage and lead science and AI software (/MLE) engineering talent to deliver world-class innovative generative AI for advertising. * Help set the scientific agenda in collaboration with org's leadership, product managers, engineering and relevant stakeholders. * Help mentor scientists & AI software talent towards contributing with patent submissions, potential peer-reviewed research publications and bar raising mentoring and hiring. * Contribute and help establish mechanisms for science and technical management, brainstorming, monitoring and validation of outputs. * Hire and develop the best technical talent at Amazon. * Write strategy and alignment documents for partners within and outside the org. * Present strategy, methods and results to senior leadership. A day in the life On a day-to-day basis, you will lead and mentor technical talent, engage and align with product, engineering and other stakeholders, dive deep on advertiser anecdotes and make sure that what the team delivers and is working on aligns with those needs and best practices. You will define and deliver mechanisms to create innovation at scale and engage with senior leadership to align on priorities and opportunities. About the team The team consists of applied scientists and AI software/machine learning engineers. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads. Basic Qualifications: - 3+ years of scientists or machine learning engineers management experience - Knowledge of ML, NLP, Information Retrieval and Analytics - PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field - Experience developing, deploying and managing AI products at scale Preferred Qualifications: - Experience leading technical initiatives and key deliverables - Experience writing strategy documents for executive audiences with clear recommendations in the midst of ambiguity - Background in Agentic AI, Machine Learning, Computer Science. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, Seattle - 183,800.00 - 248,700.00 USD annually", "summaryDescription" : "Applied Science Manager GenAI, CreativeX at Amazon.com Services LLC. Skills: Generative AI, Applied Science Management, LLMs, Computer Vision. Manage and lead science and AI software talent. Deliver world-class innovative generative AI", "postedDate" : "2026-06-13T09:25:58.665", "createdAt" : "2026-06-13T09:25:58.665", "lastUpdated" : "2026-06-15T00:52:14.784", "ingestTimestamp" : "2026-06-13T09:25:58.665", "mongoId" : "69d5e4982beec4dd3d931b0e", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10384255/apply", "salaryAnnualMin" : 183800, "salaryAnnualMax" : 248700, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "AI product development", "AI product deployment", "AI product management", "Leadership", "Mentoring", "Generative AI", "Applied Science Management", "LLMs", "Computer Vision", "Science management", "Technical management", "Generative AI for advertising", "Latent-diffusion models", "Large language models", "Computer vision", "Reinforced learning", "Image synthesis", "Video synthesis", "Audio synthesis", "Agentic AI", "Multi-modal models", "Foundational models" ], "skillCount" : 22, "jobCategory" : "data", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Advertising" }, { "id" : "69fa31574c40e2acd15a91b7", "title" : "Applied Scientist, Ads Measurement Science", "company" : "Amazon.com Services LLC", "industry" : "Applied Science, Advertising", "salary" : { "min" : 172400.0, "max" : 223400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "timestamp" : "2026-06-15T02:46:01.804", "fingerprint" : "f1dccae36cdb50eca51c932868c3409e89c94546ba6454f6037ba3bed9141812", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10411632/apply", "externalId" : "3f560a8e-d6f0-4bfe-841a-23051de18a20", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "PhD", "experienceMinYears" : 3, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Generative AI, Machine Learning, Causal Inference, Natural Language Processing, Computer Vision, Java, C++, Python", "professionalSkills" : [ "Ads measurement", "Performance measurement", "Media optimization", "Data analysis", "Model productionization" ], "hardSkillsList" : [ "Model building", "Data modeling", "Algorithm design", "Data analysis", "Scientific research" ], "softSkillsList" : [ "Autonomy", "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Model building", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Algorithm design", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "Scientific research", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Autonomy" }, { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Machine Learning, Causal Inference, Natural Language Processing, Computer Vision", "majorSkillsList" : [ "Machine Learning", "Causal Inference", "Natural Language Processing", "Computer Vision" ], "coreResponsibilities" : "Lead measurement solutions, Propose models, Design models, Analyze models, Productionize models, Provide measurement insights, Invent solutions, Disambiguate problems, Propose evaluation frameworks, Propose success criteria, Write technical documents, Implement critical-path code, Partner with engineers, Carry solutions into production, Partner with scientists, Deliver technical projects, Share works, Publish works, Communicate clearly, Contribute new ideas, Mentor junior scientists, Participate in hiring process", "teamCollaboration" : "Partner closely with scientists; Work with engineers; Work with product managers; Work with sales leaders", "domainKnowledge" : "Ads measurement; Performance measurement; Media optimization; Generative AI; Classical ML; Causal Inference; Natural Language Processing; Computer Vision", "domainList" : [ "ads-measurement", "performance-measurement", "media-optimization", "generative-ai", "classical-ml", "causal-inference", "natural-language-processing", "computer-vision" ], "domainSpecificKnowledge" : [ "Ads measurement", "Performance measurement", "Media optimization", "Generative AI", "Classical ML", "Causal Inference", "Natural Language Processing", "Computer Vision" ], "communicationSkills" : "Communicate clearly; Technical documentation", "documentationSkills" : "Technical documentation", "innovationCreativity" : "Contribute new ideas", "problemSolvingSkills" : "Disambiguate problems; Invent solutions", "qualificationsBasic" : "3+ years building models, Master's degree and 4+ years experience, PhD and 3+ years experience, Experience programming in Java, Experience programming in C++, Experience programming in Python, Experience in algorithms, Experience in data structures, Experience in parsing, Experience in numerical optimization, Experience in data mining, Experience in parallel computing, Experience in distributed computing, Experience in high-performance computing", "qualificationsPreferred" : "Experience using Unix/Linux", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of advertiser's ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We also own the science solutions for AI tools that unlock new insights and automate high-effort customer workflows, such as custom query and report generation based on natural language user requests. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As an Applied Scientist on the team, you will lead measurement solutions end-to-end from inception to production. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. Key job responsibilities - Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems - Disambiguate problems to propose clear evaluation frameworks and success criteria - Work autonomously and write high quality technical documents - Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production - Partner closely with other scientists to deliver large, multi-faceted technical projects - Share and publish works with the broader scientific community through meetings and conferences - Communicate clearly to both technical and non-technical audiences - Contribute new ideas that shape the direction of the team's work - Mentor more junior scientists and participate in the hiring process About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions. Basic Qualifications: - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications: - Experience using Unix/Linux - Experience in professional software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, NY, New York - 172,400.00 - 223,400.00 USD annually", "summaryDescription" : "Applied Scientist, Ads Measurement Science at Amazon.com Services LLC. Skills: Machine Learning, Causal Inference, Natural Language Processing, Computer Vision. Lead measurement solutions. Propose models", "postedDate" : "2026-06-13T07:23:19.867", "createdAt" : "2026-06-13T07:23:19.867", "lastUpdated" : "2026-06-15T02:46:01.804", "ingestTimestamp" : "2026-06-13T07:23:19.867", "mongoId" : "69fa31574c40e2acd15a91b7", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.jobs/jobs/10411632/apply", "salaryAnnualMin" : 172400, "salaryAnnualMax" : 223400, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Model building", "Data modeling", "Algorithm design", "Data analysis", "Scientific research", "Autonomy", "Leadership", "Mentoring", "Machine Learning", "Causal Inference", "Natural Language Processing", "Computer Vision", "Ads measurement", "Performance measurement", "Media optimization", "Model productionization", "Generative AI", "Classical ML" ], "skillCount" : 18, "jobCategory" : "other", "dataQualityScore" : 1.0, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true } ], "status" : 200, "message" : "2026 applied science internship natural language processing and speech technologies united states phd student science jobs", "metadata" : { "title" : "2026 applied science internship natural language processing and speech technologies united states phd student science" }, "pagination" : { "page" : 0, "limit" : 50, "totalCount" : 39911, "totalPages" : 799, "hasNext" : true, "hasPrevious" : false } }

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