Careers

We are looking for a researcher in state-of-the-art LLM technologies for applications across Alexa, AWS, and other Amazon businesses. In this role, you will innovate in the fastest-moving fields of current AI research, in particular in how to integrate a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques), and get to immediately apply your results in highly visible Amazon products. If you are deeply familiar with LLMs, natural language processing and machine learning, 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 - Use Python and various internal and open source libraries to develop and/or improve LLMs for business applications - Collaborate with scientists and Engineers and pave the way towards bringing your solution into production systems. Participate in cross team projects and ensure technical blockers are resolved. - Communicate and document your research by writing and sharing internal documents with your team

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON WEB SERVICES, INC. Offered Position: Data Scientist II Job Location: Santa Clara, California Job Number: AMZ9674189 Position Responsibilities: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. 40 hours / week, 8:00am-5:00pm, Salary Range: $211,536/year to $212,800/year. 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, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

Are you excited to help the US Intelligence Community design, build, and implement artificial intelligence (AI) algorithms, including advanced Generative AI solutions, to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) and Generative AI (GenAI) methods. We build models and Machine Learning Operations pipelines for text, image, video, audio, and multi-modal use cases, leveraging both traditional ML approaches and state-of-the-art generative models including Large Language Models (LLMs). Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced Data Scientists with a background in both traditional and generative AI who understand the unique challenges of the Signals Intelligence (SIGINT) and Cyber Operations domains, with experience applying data science and machine learning to transform Intelligence Community production chains. In this role, you will work at the intersection of SIGINT, Cyber Operations, and cloud computing, helping customers understand the opportunities their data presents, applying the full suite of AWS's AI/ML services to transform missions, and building solutions that earn the customer trust needed for deployment to production systems. You will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position is expected to work within the Ft. Meade/CMD location, and requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed. 10040 Key job responsibilities As a Data Scientist, you will: - Collaborate with AI/ML Scientists and Architects to research, design, develop, and evaluate AI algorithms to address real world challenges. - Participate in the design and construction of Machine Learning Operations (MLOps) pipelines and architectures. - Interact with customers directly to understand the business problem, help and aid them in implementation of AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders. - Provide customer and market feedback to Product and Engineering teams to help define product direction. - This position may require up to 25% local travel. 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 AWS values diverse experiences. Even if you do not meet all of the 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. 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 (diversity) conferences, inspire us to never stop embracing our uniqueness. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 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.

Are you excited to help the US Intelligence Community design, build, and implement artificial intelligence (AI) algorithms, including advanced Generative AI solutions, to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) and Generative AI (GenAI) methods. We build models and Machine Learning Operations pipelines for text, image, video, audio, and multi-modal use cases, leveraging both traditional ML approaches and state-of-the-art generative models including Large Language Models (LLMs). Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced Data Scientists with a background in both traditional and generative AI who understand the unique challenges of the Signals Intelligence (SIGINT) and Cyber Operations domains, with experience applying data science and machine learning to transform Intelligence Community production chains. In this role, you will work at the intersection of SIGINT, Cyber Operations, and cloud computing, helping customers understand the opportunities their data presents, applying the full suite of AWS's AI/ML services to transform missions, and building solutions that earn the customer trust needed for deployment to production systems. You will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position is expected to work within the Ft. Meade/CMD location, and requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed. 10040 Key job responsibilities As a Data Scientist, you will: - Collaborate with AI/ML Scientists and Architects to research, design, develop, and evaluate AI algorithms to address real world challenges. - Participate in the design and construction of Machine Learning Operations (MLOps) pipelines and architectures. - Interact with customers directly to understand the business problem, help and aid them in implementation of AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders. - Provide customer and market feedback to Product and Engineering teams to help define product direction. - This position may require up to 25% local travel. 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 AWS values diverse experiences. Even if you do not meet all of the 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. 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 (diversity) conferences, inspire us to never stop embracing our uniqueness. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 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.

Employer: Amazon.com Services LLC Position: Applied Scientist II (multiple positions available) Location: Sunnyvale, CA Multiple Positions Available: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.

Are you interested in shaping the future of Advertising and B2B Sales? 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, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top science talent to build new, science-backed services to drive success for our customers. Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency. As a manager for our team, you will bring deep expertise in quantitative modeling (forecasting, recommender systems, reinforcement learning, causal inferencing 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 and customers. As a senior lead, you will have the excitement to take iterative approaches to tackle big, long-term problems. Why you will love this opportunity: Amazon has invested 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 ads impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences; this is your opportunity to work within the fastest growing businesses across all of Amazon! 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.

Unleash Your Potential as an AI Trailblazer At Amazon, we're on a mission to revolutionize the way people discover and access information. Our Applied Science team is at the forefront of this endeavor, pushing the boundaries of recommender systems and information retrieval. We're seeking brilliant minds to join us as interns and contribute to the development of cutting-edge AI solutions that will shape the future of personalized experiences. As an Applied Science Intern focused on Recommender Systems and Information Retrieval in Machine Learning, you'll have the opportunity to work alongside renowned scientists and engineers, tackling complex challenges in areas such as deep learning, natural language processing, and large-scale distributed systems. Your contributions will directly impact the products and services used by millions of Amazon customers worldwide. Imagine a role where you immerse yourself in groundbreaking research, exploring novel machine learning models for product recommendations, personalized search, and information retrieval tasks. 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. Must be eligible and available for a full-time (40h / week) 12 week internship between May 2026 and September 2026 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, Programming/Scripting Languages, Time Series, Machine Learning, Natural Language Processing, Deep Learning,Neural Networks/GNNs, Large Language Models, Data Structures and Algorithms, Graph Modeling, Collaborative Filtering, Learning to Rank, Recommender Systems 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 - Design, implement, and experimentally evaluate new recommendation and search algorithms using large-scale datasets - Develop scalable data processing pipelines to ingest, clean, and featurize diverse data sources for model training - Conduct research into the latest advancements in recommender systems, information retrieval, and related machine learning domains - Collaborate with cross-functional teams to integrate your innovative solutions into production systems, impacting millions of Amazon customers worldwide - Communicate your findings through captivating presentations, technical documentation, and potential publications, sharing your knowledge with the global AI community

Do you enjoy solving challenging problems and driving innovations in research? Do you want to create scalable optimization models and apply machine learning techniques to guide real-world decisions? We are looking for builders, innovators, and entrepreneurs who want to bring their ideas to reality and improve the lives of millions of customers. As a Research Science intern focused on Operations Research and Optimization intern, you will be challenged to apply theory into practice through experimentation and invention, develop new algorithms using modeling software and programming techniques for complex problems, implement prototypes and work with massive datasets. As you navigate through complex algorithms and data structures, you'll find yourself at the forefront of innovation, shaping the future of Amazon's fulfillment, logistics, and supply chain operations. Imagine waking up each morning, fueled by the excitement of solving intricate puzzles that have a direct impact on Amazon's operational excellence. Your day might begin by collaborating with cross-functional teams, exchanging ideas and insights to develop innovative solutions. You'll then immerse yourself in a world of data, leveraging your expertise in optimization, causal inference, time series analysis, and machine learning to uncover hidden patterns and drive operational efficiencies. 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. Amazon has positions available for Operations Research 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: Optimization, Causal Inference, Time Series, Algorithms and Data Structures, Statistics, Operations Research, Machine Learning, Programming/Scripting Languages, LLMs In this role, you will gain hands-on experience in applying cutting-edge analytical techniques to tackle complex business challenges at scale. If you are passionate about using data-driven insights to drive operational excellence, we encourage you to apply. 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 and apply optimization, causal inference, and time series modeling techniques to drive operational efficiencies and improve decision-making across Amazon's fulfillment, logistics, and supply chain operations Design and implement scalable algorithms and data structures to support complex optimization systems Leverage statistical methods and machine learning to uncover insights and patterns in large-scale operations data Prototype and validate new approaches through rigorous experimentation and analysis Collaborate closely with cross-functional teams of researchers, engineers, and business stakeholders to translate research outputs into tangible business impact

Join us in the evolution of Amazon’s Seller business! The Selling Partner Growth organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources. We are looking for a Senior Economist to lead us to identify data-driven insight and opportunities to improve our SP growth strategy and drive new seller success. As a successful Economist on our talented team of scientists and economists, you will solve complex problems to identify actionable opportunities, and collaborate with engineering, research, and business teams for future innovation. You need to have deep understanding on the business domain and have the ability to connect business with science. You are also strong in econometrics modeling and scientific foundation with the ability to collaborate with engineering to put models in production to answer specific business questions. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research). Key job responsibilities As a Sr. Economist in the team, you will: - Identify opportunities to improve SP growth and translate those opportunities into science problems via principled scientific solutions (e.g. ML, causal). - Mentor and guide the applied scientists and economists in our organization and hold us to a high standard of technical rigor and excellence in science. - Design and lead roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers. - Work with our engineering partners and draw upon your experience to meet latency and other system constraints. - Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver. - Be responsible for communicating our science innovations to the broader internal & external scientific community.

Employer: Amazon.com Services LLC Position: Research Scientist II Location: Arlington, VA Multiple Positions Available: Interact with various software and business groups to develop an understanding of their business requirements and operational processes. Utilize acquired knowledge and business judgment to build decision-supporting and operational tools to improve the bottom line. Build quantitative mathematical models to represent a wide range of supply chain, transportation and logistics systems. Implement these models and tools through the use of modeling languages and engineering code in software languages such as Java, C++, C# or C. Gather required data for analysis and mathematical model building by writing ad-hoc scripts and database queries. Perform quantitative, economic, and numerical performance analyses of these systems under uncertainty using statistical and optimization tools. Create computer simulations to support operational decision-making. Identify areas with potential for improvement and work with internal teams to generate requirements to realize improvements. Design optimal or near optimal solution methodologies to be used by in-house decision support tools and software. Create software prototypes to verify and validate the devised solutions methodologies. Integrate prototypes into production systems using standard software development tools and methodologies.