Careers

Amazon's PRISM team is seeking an innovative Applied Scientist to build the intelligence layer powering the Catalog Diagnostic Assistant — a conversational AI agent that unifies Amazon's fragmented catalog diagnostic experience into a single natural-language interface. Rather than switching between legacy tools, internal users ask CDA a question in plain language and CDA coordinates across data sources, reasons through complex diagnostic workflows, and returns a combined answer with source citations. This role sits at the intersection of Generative AI, agentic architectures, and large-scale information retrieval applied to the world's largest product catalog. You will design and build the scientific core of an agent that autonomously investigates catalog anomalies — diagnosing why products aren't live, why attributes aren't publishing, or why matching decisions went wrong — across billions of products, petabytes of multimodal data, and dozens of marketplaces. You will be the founding scientist for the CDA product, defining the research agenda for agentic diagnostics, developing novel approaches to skill-based reasoning and tool orchestration, and owning the full lifecycle from problem formulation through production deployment at Amazon scale. You will pioneer advanced GenAI solutions that power next-generation agentic experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog and tackle problems at the frontier of AI research. Key job responsibilities - Formulate open research problems at the intersection of GenAI, agentic reasoning, and large-scale catalog diagnostics — defining how an autonomous agent should decompose, investigate, and explain complex catalog issues - Design and develop novel agentic architectures (skill planning, tool selection, multi-step reasoning, chain-of-thought verification) that enable CDA to autonomously resolve diagnostic workflows that traditionally required manual expert investigation - Build and optimize retrieval-augmented generation (RAG) systems over Amazon's catalog data, ensuring the agent retrieves the right evidence from the right data sources to ground its diagnostic answers - Advance the science of efficient model deployment — developing distillation, compression, and LLM serving optimization strategies that preserve diagnostic reasoning quality in production-grade architectures while reducing latency and cost - Make frontier models reliable for autonomous decisions — advancing uncertainty calibration, confidence estimation, and interpretability methods so CDA's agentic diagnoses can be trusted at scale - Own the full research lifecycle from problem formulation through production deployment — designing rigorous experiments, iterating rapidly, and seeing your research directly improve diagnostic accuracy and coverage - Partner closely with CDA engineers to translate research prototypes into production systems serving thousands of daily diagnostic sessions - Shape the team's research vision by defining technical roadmaps that balance foundational scientific inquiry with measurable product impact - Mentor engineers on advanced ML/GenAI techniques, experimental design, and scientific rigor About the team We are a GenAI science team within Amazon's Selection and Catalog Systems (ASCS) organization. Our mission is to advance state-of-the-art Generative AI to deeply understand, uniquely identify, and intelligently diagnose every product at Amazon scale. We push the boundaries of multimodal LLMs, agentic systems, and generative AI to solve foundational catalog challenges — from product identity and semantic matching to automated catalog diagnostics and intelligent catalog analytics. Our scientists work across multiple high-impact problem spaces: establishing canonical product identity across billions of items, powering next-generation agentic experiences for catalog operations, and building AI systems that make Amazon's catalog self-diagnosing and self-healing. We operate at the frontier of AI research applied at unprecedented scale — petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity. This is a collaborative, fast-moving environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your ideas at scale, and publish your findings at top venues.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and visual), supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, product similarity, using GenAI, LLMs, NLP and Computer Vision. Key job responsibilities As an Applied Science Manager, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will Lead scientists on the team and oversee research and development projects at various stages ranging from initial exploration to deployment into production systems. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will create the environment in the team to file for patents and/or publish research work where opportunities arise. You will impact the large product strategy, identifies new business opportunities and provides strategic direction to the team.

Your Next Big Challenge Starts Here You've spent years mastering machine learning. Now imagine applying that expertise where it actually reaches billions of people — every single day. At Amazon Ads, we're not just running ads. We're re-inventing the entire advertising experience using generative AI, large language models, and next-generation ML. From the moment a brand crafts a campaign to the instant a customer discovers something they love — your science powers it all. Billions of impressions. Millions of clicks. Petabytes of data. And you — at the center of it. Why This Role Will Excite You Unmatched scale and resources. You'll have access to computational power and datasets most scientists only dream about. Build solutions that don't just work in a notebook — they work at planet scale. Breadth that keeps you sharp. One quarter you might be optimizing real-time bidding systems. The next, you're building creative AI that generates ad content. Ranking, personalization, NLP, computer vision, LLMs — it's all on the table. Your ideas ship. This isn't a research lab where papers collect dust. You'll take models from concept to production, run A/B experiments, and see your work move metrics that matter — for advertisers, customers, and the business. People who push you forward. You'll collaborate with world-class engineers, scientists, and product leaders who are just as passionate about solving hard problems as you are. What You'll Actually Do Research and build next-generation ML solutions — including generative AI and LLM applications — that transform how advertising works Own end-to-end projects: from messy, ambiguous problems to deployed, production-grade models Design experiments that validate your hypotheses and measure real business impact Build models that balance what's best for customers and advertisers — because great advertising should feel helpful, not intrusive Work cross-functionally with engineers, PMs, and fellow scientists to ship fast and iterate faster Develop scalable ML pipelines that optimize monetization without sacrificing customer experience Where This Takes Your Career Whether you want to go deep as a technical IC or grow into people leadership — both paths are real here. You'll have opportunities to: Lead high-visibility technical initiatives Mentor and grow other scientists Shape strategy alongside senior leadership Build a reputation in a community that genuinely values scientific excellence Your work won't just be seen internally — it'll impact millions of customers and advertisers worldwide. Watch Scientists at Amazon Ads Talk About Their Work https://www.youtube.com/watch?v=vvHsURsIPEA Learn More About Amazon Ads https://advertising.amazon.com/ Basic Qualifications 5+ years building ML models for real business applications PhD, or Master's degree + 6 years of applied research experience Strong programming skills in Python, Java, C++, or similar Hands-on experience with deep learning and neural network methods Preferred Qualifications Experience with tools like scikit-learn, TensorFlow, PyTorch, Spark MLLib, MxNet, numpy, scipy Experience with large-scale distributed systems (Hadoop, Spark, etc.)

This role will develop Economic and Econometric models and thought leadership on projects that span our business, with a particular focus on supply chain and inventory selection. Through the lens of economics, you will develop a deeper understanding of how customers value our selection and interact with Amazon's store to make shopping easier. You will be a key scientist, advising Amazon leaders how to evaluate selection and understand customers. You will work on developing frameworks and scaleable, repeatable models supporting optimal pricing and policies for Amazon's business. You will partner with science and technology teams across Amazon including Supply Chain, Operations, Retail, FBA, Consumer Pricing, and Finance. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. Ability to incorporate AI tools and methods into your work is highly valued. They will work closely with Economists, Data/Applied Scientists, Software Engineers and Product Managers to integrate economic insights into policy and systems production. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.

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 Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. 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 - Develop AI solutions for various Prime Video Personalization systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - 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; - Publish your research findings in top conferences and journals. About the team Prime Video Growth Science team owns science solution to power online new content experience and offline experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.

The Amazon Robotics team is seeking an experienced Applied Scientist to join our team. In this role you will apply the latest trends in research to solve real-world problems in robotics and AI. You will collaborate with a team of scientists and engineers building these applications. We holistically design, build, and deliver end-to-end robotic systems. Our team is also responsible for core infrastructure and tools that serve as the backbone of our robotic applications, enabling roboticists, machine learning scientists, software engineers, and hardware engineers to collaborate and deploy systems in the field. Key job responsibilities • Research, design, implement and evaluate complex perception, motion planning, and decision making algorithms integrating across multiple disciplines and leveraging machine learning. • Create experiments and prototype implementations of new learning algorithms and prediction techniques. • Work closely with software engineering team members to drive scalable, real-time implementations. • Collaborate with machine learning and robotic controls experts to implement and deploy algorithms, such as machine learning models. • Collaborate closely with hardware engineering team members on developing systems from prototyping to production level. • Represent Amazon in academia community through publications and scientific presentations. • Work with stakeholders across hardware, science, and operations teams to iterate on systems design and implementation. About the team Watch this video to learn more about Vulcan Pick team in Amazon Robotics: https://www.amazon.science/publications/vulcan-pick-a-robotic-system-for-picking-targeted-objects-from-fabric-pods

We’re looking for a Research Scientist to join a team that measures and explains how over 2.4 million sellers and vendors experience selling on Amazon. You’ll apply survey science, psychometrics, and applied statistics to help drive meaningful change at Amazon on behalf of Sellers. In this role, you’ll work across a variety of research methodologies to optimize our data collection, create scalable analytical approaches, and deep dive the Seller experience to create rigorous, quantitative insights that senior leaders use to set strategy. Key job responsibilities Key Job Responsibilities - Apply psychometric and survey methodology techniques (e.g., IRT, factor analysis, scale development, single-item indicators) to measure seller experience constructs with scientific rigor - Contribute to frameworks that link seller attitudinal data to behavioral outcomes and identify high-impact opportunity areas - Design and execute statistical analyses including regression modeling, significance testing, and driver analysis to identify what matters most to sellers - Apply observational causal evaluation methods to estimate the effects of policy changes, product launches, and platform interventions on seller experience - Build and maintain analytical pipelines that transform raw survey data into production-ready metrics, reports, and dashboards - Analyze open-ended survey responses using text classification, thematic coding, and natural language processing techniques - Monitor and improve survey response rates, sampling methodology, and data quality - Productionalize research code: take analyses from prototype to automated, reproducible pipelines that run reliably in production environments - Communicate findings clearly to technical and non-technical audiences through written reports, data visualizations, and presentations - Collaborate with cross-functional partners to translate business questions into well-defined research problems and scientific metrics - Document research methods, assumptions, and limitations transparently to ensure reproducibility A day in the life Your day typically starts with the data. You might spend the morning reviewing satisfaction trends, investigating a shift in a key metric, and pulling together an analysis that explains what’s driving it. You’ll regularly meet with external teams to help them understand how a proposed product will affect seller sentiment and what the data says they should prioritize. You’ll also spend time in R or Python building, training, or testing models to improve how we measure and act on sentiment data. About the team Our team owns the research and measurement infrastructure that tracks satisfaction across all 2.1 million selling partners on Amazon, spanning Seller Central, Next Gen Selling, and Mobile. We sit at the intersection of data and strategy, partnering with teams across product, design, and engineering to advocate for seller experience improvements. This is a high-visibility team where the work is consequential, the stakeholders are senior, and the problems are genuinely hard.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising! The Amazon Sponsored Products and Brands is looking for a talented Sr. Applied Scientist to join the Global Optimization science team at the forefront of advertising technology innovation. We are working backwards from emerging markets to reimagine Amazon's advertising stack from the ground up, leveraging multilingual and multi-modal GenAI technologies — including semantic hash designs, LLMs, and more — to deliver solutions that scale to non-US marketplaces from day one. This is your opportunity to be part of a small, high-impact team that prototypes, invents, and ships state-of-the-art solutions that will define the future of digital advertising. The ideal candidate combines entrepreneurial drive with deep technical expertise, thriving in ambiguous, fast-moving environments where you define the path forward with minimal structure. Our team regularly goes from ideas on the whiteboard to production-grade experiments. Your Customer Obsession fuels your passion for translating science into real-world value for millions of advertisers and customers worldwide. You are consistently Right, A Lot when navigating complex technical decisions, demonstrating the rare ability to identify solutions that drive maximum impact with minimal resources. Whether you're architecting scalable GenAI systems or optimizing multi-task recommendation engines, you cut through complexity to find the solutions that deliver the most results. Your GenAI experience goes beyond theoretical knowledge—you have successfully delivered value with state-of-the-art technologies at Amazon scale, understanding both the promise and practical challenges of deploying machine learning in production environments (evaluations, etc.). You're not just a scientist or just an engineer—you're a builder who sees the bigger picture and knows how to make it reality. Key job responsibilities * Architect next-generation systems that replace legacy monolithic infrastructure with scalable, intelligent solutions that scale worldwide on day one. * Pioneer breakthrough applied science in multi-modal GenAI applications for advertising, combining text, image, and multi-lingual support. * Drive end-to-end innovation from research ideation through production deployment at Amazon scale. * Lead cross-functional collaboration with product, engineering, and business teams to translate science into customer impact. About the team You will join a newly-founded team with a broad mandate to experiment and innovate, with a focus on driving growth of sponsored products ad experiences across non-US marketplaces. This broad charter gives us the flexibility to explore and apply scientific techniques to novel product problems. You will have the satisfaction of seeing your work improve the experience of millions of Amazon shoppers worldwide while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills, and be a science leader in an environment that thrives on creativity, experimentation, and product innovation.

Are you passionate about leveraging your applied science skills to deliver actionable insights that impact daily business decisions? Do you like using ML, GenAI, Causal Inference, Reinforcement Learning and Experimentation to answer challenging product and customer behavior questions? Do you want to be a technical leader and build flexible and global solutions for complex financial services/payments, risk, and causal problems? If so, here is a great opportunity to consider! Amazon B2B Payments & Lending is seeking an Applied Scientist II who will combine their technical expertise with business acumen to generate critical insights that will set the strategic direction of the business. You will be a thought leader on the team, help set the team's strategic focus and roadmaps, and design and build systems/solutions that support financial products, working closely with business/product partners and engineers. You will utilize ML/GenAI/Causal Inference/Reinforcement Learning/Experimentation methodologies, data and coding skills, problem solving and analytical skills, and excellent communication to deliver customer value. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan. If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!