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 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!

Join the next science and engineering revolution at Amazon's Delivery Foundation Model team, where you'll work alongside world-class scientists and engineers to pioneer the next frontier of logistics through advanced AI and foundation models. We are seeking an exceptional Principal Applied Scientist to help develop innovative foundation models that enable delivery of billions of packages worldwide. In this role, you'll combine highly technical work with scientific leadership, ensuring the team delivers robust solutions for dynamic real-world environments. Your team will leverage Amazon's vast data and computational resources to tackle ambitious problems across a diverse set of Amazon delivery use cases. Key job responsibilities - Design and implement novel deep learning architectures combining a multitude of modalities, including image, video, and geospatial data. - Solve computational problems to train foundation models on vast amounts of Amazon data and infer at Amazon scale, taking advantage of latest developments in hardware and deep learning libraries. - As a foundation model developer, collaborate with multiple science and engineering teams to help build adaptations that power use cases across Amazon Last Mile deliveries, improving experience and safety of a delivery driver, an Amazon customer, and improving efficiency of Amazon delivery network. - Guide technical direction for specific research initiatives, ensuring robust performance in production environments. - Mentor fellow scientists while maintaining strong individual technical contributions. A day in the life As a member of the Delivery Foundation Model team, you’ll spend your day on the following: - Develop and implement novel foundation model architectures, working hands-on with data and our extensive training and evaluation infrastructure - Guide and support fellow scientists in solving complex technical challenges, from trajectory planning to efficient multi-task learning - Guide and support fellow engineers in building scalable and reusable infra to support model training, evaluation, and inference - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems- Drive technical discussions within the team and and key stakeholders - Conduct experiments and prototype new ideas - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team The Delivery Foundation Model team combines ambitious research vision with real-world impact. Our foundation models provide generative reasoning capabilities required to meet the demands of Amazon's global Last Mile delivery network. We leverage Amazon's unparalleled computational infrastructure and extensive datasets to deploy state-of-the-art foundation models to improve the safety, quality, and efficiency of Amazon deliveries. Our work spans the full spectrum of foundation model development, from multimodal training using images, videos, and sensor data, to sophisticated modeling strategies that can handle diverse real-world scenarios. We build everything end to end, from data preparation to model training and evaluation to inference, along with all the tooling needed to understand and analyze model performance. Join us if you're excited about pushing the boundaries of what's possible in logistics, working with world-class scientists and engineers, and seeing your innovations deployed at unprecedented scale.

Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 200 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. The Insights team is looking for an Applied Scientist for our London office experienced in generative AI and large models. This is a hands-on role with Prime Video wide impact working with development teams across the UK, India, and the US. This greenfield project will deliver features that reduce the operational load for internal Prime Video builders and for this, you will need to develop personalized recommendations for their services. You will lead the design of machine learning models that scale to very large quantities of data across multiple dimensions. You will embody scientific rigor, designing and executing experiments to demonstrate the technical effectiveness and business value of your methods. You will work alongside other scientists and engineering teams to deliver your research into production systems. Successful candidates will have strong technical ability, excellent teamwork and communication skills, and a strong motivation to deliver customer value from their research. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills and make a global impact immediately. Key job responsibilities - Develop machine learning algorithms for high-scale recommendations problems. - Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. - Collaborate with software engineers to integrate successful experimental results into Prime Video wide processes. - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports. About the team Our team owns Prime Video observability features for development teams. We consume PBs of logs daily which feed into multiple observability features focussed on reducing the customer impact time. In 2025, we are expanding our remit to consume data from more sources to provide more holistic observability for our development teams.

Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the The Generative AI Innovation and Delivery Team (GenAIID) Startup Organization! The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI Platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with worlds’ leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Applied Scientists passionate about helping startups use GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities * Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities * Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production * Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization * Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience * Provide customer and market feedback to product and engineering teams to help define product direction * Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements About the team 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. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

We are seeking a Senior Applied Scientist to drive innovation in machine learning and artificial intelligence for Amazon's autonomous delivery systems. In this role, you will develop novel algorithms and models that power our autonomous vehicle perception, prediction, and decision-making systems. You will combine rigorous scientific methodology with practical engineering to solve complex problems in real-world autonomous navigation and delivery. Key job responsibilities - Design and develop advanced machine learning models and algorithms for autonomous vehicle systems - Lead research initiatives in areas such as computer vision, sensor fusion, behavioral prediction, and path planning - Transform research concepts into production-ready solutions that meet strict safety and performance requirements - Develop novel approaches to solve complex technical challenges in autonomous navigation - Create and implement metrics and evaluation frameworks to measure model performance - Collaborate with engineering teams to integrate ML solutions into the autonomous vehicle stack - Publish research findings and represent Amazon at technical conferences - Mentor junior scientists and contribute to building a culture of scientific excellence A day in the life A typical day for a Senior Applied Scientist begins with analyzing experimental results from recent model deployments. They might spend the morning developing new deep learning architectures for sensor fusion or improving prediction models for pedestrian behavior. Mid-day could involve collaborating with engineering teams to optimize model performance and reduce inference latency. Afternoon activities might include designing experiments to validate new approaches, reviewing research papers for potential application, and participating in technical discussions to solve challenging problems in perception or planning. They would regularly engage in code reviews, documentation of methods, and mentoring of team members. The role requires balancing innovative research with practical implementation, ensuring that scientific advances translate into reliable autonomous system capabilities. About the team The Applied Science team within Amazon's Last Mile Delivery Automation organization focuses on developing cutting-edge machine learning solutions for autonomous systems. We work at the intersection of computer vision, deep learning, robotics, and control systems to create robust and scalable algorithms that enable safe autonomous operation. Our team combines expertise from diverse scientific backgrounds to tackle fundamental challenges in perception, prediction, and decision-making. We collaborate closely with software engineering teams to deploy our solutions across Amazon's autonomous delivery fleet.

We are seeking a Senior Economist to accelerate Amazon Japan's customer growth and engagement. In this exciting charter, you will use economic principles and econometrics to foster and drive innovations for some of Amazon's flagship programs, including Prime, Amazon Points, and Deal Events (e.g., Prime Day). Amazon has a trailblazing track record of working with Ph.D. economists in the tech industry and offers a unique environment for economists to thrive. As an economist at Amazon, you will apply the frontier of econometric and economic methods to Amazon’s terabytes of data and intriguing customer problems. Your expertise in building reduced-form or structural causal inference models is exemplary in Amazon. Your strategic thinking in designing mechanisms and products influences how Amazon evolves. In this role, you will work with a diverse team of product and science talents to identify business opportunities and build best-in-class econometric models to address them. You will work with engineering teams to productionize your models and improve the experiences of our customers and associates. You will own, execute, and expand a research roadmap that contributes to Amazon's long term success. As one of the first economists outside North America/EU, you will make an outsized impact to our international marketplaces and pioneer in expanding Amazon’s economist community in Asia. The ideal candidate will be an experienced economist in empirical industrial organization, labour economics, or related structural/reduced-form causal inference fields. You are a self-starter who enjoys ambiguity in a fast-paced and earns trust from stakeholders in an ever-changing environment. You think big on the next game-changing opportunity but also dive deep into every detail that matters. You insist on the highest standards and are consistent in delivering results. Key job responsibilities - Work with Product, Finance, Data Science, and Engineering teams across the globe to deliver data-driven insights and products for regional and world-wide launches. - Use economic insights to guide business to make the right strategic decisions. - Innovate on how Amazon can leverage data analytics to improve customer growth and engagement. - Contribute to building a strong data science community in Amazon Asia.

The Amazon Selection and Catalog Systems team (ASCS) builds global selection and catalog management systems. The Selection Monitoring team is responsible for building the biggest product selection on the planet to satisfy our customers’ all shopping needs. We build platforms, systems and tools to create and take advantage of datasets that contains billions of records, use the latest machine learning, data processing technologies and a broad set of AWS technologies. In order to drive the expansion of Amazon selection, we use cluster-computing technologies such as MapReduce and Spark to process billions of products and find the products/brands not already sold on Amazon. We work with structured and unstructured content such as text and images and apply Machine Learning algorithms such as Clustering, Natural Language processing, Fuzzy matching and Image processing at a massive scale. We are looking for a Senior Manager, Applied Science to tackle ambiguous problems in the areas of data processing, machine learning algorithms and distributed systems of cloud-scale. You are expected to take ownership, dive deep and drive solutions from developing prototypes, doing experiments, design to coding, testing and deployment. The role demands innovation and expects you to push the boundaries. You will get opportunity to work with many tech teams and business teams within Amazon and deliver solutions that will have an impact to both Amazon top-line & bottom line.

急成長する組織で、データサイエンス・アルゴリズムのスキルを武器に物流に変革を起こしませんか？ アマゾンジャパン トランスポーテーション部門では、Data ScientistやData EngineerのチームをLeadし、Businessに必要な機械学習/Heuristicモデル・ソリューションの構築を主導するSenior Data Scientistを募集します。 当社は日本最大級のEコマースモールを運営しています。「地球上で最もお客様を大切にする企業になること」を企業理念に掲げ、お客様が欲しい商品を欲しい時に最速のお届けでお買い物出来るようなネットワークの構築を行っています。遅延なく商品を入荷しお客様に幅広いセレクションを提供し、お約束通りに商品をお届けすることはサービスの根幹ですが、物流・小売業界を取り巻く環境は日々変化しています。常に変化する状況にあってもお客様のために常に高いサービス品質を提供することは、当社の競争力に必要不可欠な要素です。 Amazon Japanの成長に伴って拡大を続けるサプライチェーンは日々複雑性を増しており、Business Operationの効率化・可視化・意思決定の質の向上が求められています。AWSやAmazon 独自のToolを使って、これらのチャレンジに対して最適なモデル・ソリューションを提供するチームをリードするEngineerを募集しています。 ------------------------------- Revolutionize logistics with your data science and algorithm skills in a rapidly growing organization. The Amazon Japan Transportation division is seeking a Senior Data Scientist to lead a team of Data Scientists and Data Engineers, and spearhead the development of machine learning/heuristic model solutions that meet the business's needs. This is an exciting opportunity to contribute your talents. Our company operates Japan's largest e-commerce marketplace. Guided by the vision of becoming "Earth's most customer-centric company," we are building a network that delivers the products customers want, when they want them, as quickly as possible. Seamlessly replenishing inventory and providing a wide selection are core to our service, but the logistics and retail landscape is constantly evolving. Maintaining high service quality amidst this change is essential to our competitiveness. As Amazon Japan continues to grow, our expanding supply chain is becoming increasingly complex. There is a strong need to improve the efficiency, visibility, and quality of our business operations. We are seeking an engineer to lead a team that leverages AWS and Amazon's proprietary tools to deliver optimal model and technology solutions for these challenges. Key job responsibilities • 複雑でBusiness Impactの大きな課題に対するモデル・ソリューションを提供します。アーキテクチャレベルから設計し、必要に応じて他のエンジニアリングチームと協力して行います。 • People Managementを除くTech Leading・Project Leading・Team Leadingを行います。Scrumプロセスに基づき、チームの優先順位を設定し、顧客やステークホルダーと効果的に連携する必要があります。Managerとともにロードマップを確立し、ビジネスニーズを満たすソリューションを提供します。 • エンジニアリング上の基準(正確性、効率性など)や運用上の基準(品質、一貫性、信頼性など)を確立するためのメカニズムをManagerとともに構築します。 • チームの進捗状況、データ/ソリューションの品質、エンジニアリング/運用の状況を測定する指標をManagerとともに定義します。 • 戦略的に考え、トレードオフを行う必要があります。あなたの決定は、組織のインフラストラクチャ(リソースやコストを含む)に影響を与えます。 • アイデアを効果的に伝える必要があり、あらゆるタイプのステークホルダーに対して口頭および文章で伝えることが出来ます。戦略的な文書を作成します。 • 限られたガイダンスの下で、プロジェクトをリードする必要があります。 ------------------------------- • Provide model and technology solutions for complex, high-impact business challenges. Design these solutions from an architectural level, collaborating with other engineering teams as needed. • Serve as a Tech Lead, Project Lead and Team Lead (excluding people management). Based on Scrum processes, you will set team priorities, effectively liaise with customers and stakeholders. Partner with Managers to establish a roadmap and deliver solutions that meet business needs. • Collaborate with Managers to establish mechanisms that uphold engineering standards (e.g., accuracy, efficiency) and operational standards (e.g., quality, consistency, reliability). • Define metrics with Managers to measure team progress, data/solution quality, and the state of engineering/operations. • Think strategically and make tradeoffs, as your decisions will impact the organization's infrastructure (including resources and costs). • Communicate ideas effectively, both verbally and in writing, to all types of stakeholders. Produce strategic documentation. • Lead projects with limited guidance. A day in the life • 10:00 出勤。自分がLeadしているプロジェクトのコードを書く • 10:30 同僚が実装した新しいMLOpsツールの説明を受ける。前から欲しかったInput Feature Validation機能がついており感動 • 11:00 プロジェクトメンバーと一緒にHyper Parameter Tuningのコードを設計。Notebookで実行し、午前中の仕事は終了 • 12:00 ランチ。今週の週替わりメニューのタンドリーチキンを初めて食べてみる。エキゾチック！ • 13:30 Scrum Daily Meeting。同僚の進捗を確認しつつ情報交換。Lossの改良に別プロジェクトの知見が使えそう • 14:00 Biz sideとフラッシュディスカッション。実装アイデアについて目線合わせ • 14:30 肩が凝ったので会社でマッサージの施術を受ける。最高 • 15:00 一旦退社。残りは家で • 16:00 Hyper Parameter tuneの結果を確認。Bayesでよさそうだけど、探索空間は要検討。いったん大域探索のために分散並列処理をDEと一緒に書く • 18:00 明日のProject Weeklyの準備。各メンバーの進捗をSlackで確認し、事前にアドバイスをいくつか提供。Notebookに作ってくれたFigureを保存 • 18:30 コードレビュー。コメントをいくつか付けてApprove • 19:30 お仕事終了 About the team 弊チームはData Scienceソリューションを提供しており、主なミッションは以下の3つです。 • 1: 幹線輸送情報を包括的に管理・分析するための、大規模なData Martの改修・維持管理 • 2: 上記1のデータを利用した機械学習・最適化系アルゴリズムソリューションの提供 • 3: 上記1のデータを利用したBusiness Insight導出用のData Pipeline・Dashboardソリューションの提供 特に2の領域についてはニーズが高まっており、開発を加速しています。一例を挙げると、件数ベースで新たな開発ニーズの80%を占めるとともに、Business Impactも従来のプロジェクトにくらべ非常に大きくなっています。 機械学習系のソリューションは提供開始からまだ1年が経過したばかりですが、非常に期待を集めている成長著しい領域となります。 ---------------- Our team provides Data Science solutions, and our main missions are the following three: • 1: Overhaul and maintain a large-scale Data Mart to comprehensively manage and analyze trunk transportation information • 2: Provide machine learning, optimization algorithm solutions utilizing the data from the above 1 • 3: Provide Data Pipeline and Dashboard solutions to derive Business Insights using the data from the above 1 In particular, there is a growing demand in the area 2, and we are accelerating the development.

Want to help develop the next generation of web search to support intelligent assistant products? Join us! We are looking for a talented Applied Scientist to help us develop state-of-the-art, next generation web search capabilities within Amazon AGI. You will have an opportunity to directly impact the customer experience, design, architecture, and implementation of products that will be used every day by people you know. We're looking for someone passionate about innovating on behalf of customers, who demonstrates strong product ownership and is willing to think in new ways to solve difficult problems. You'll develop novel solutions to challenging technical problems, driving key improvements in our web search capabilities. You'll perform rigorous research, publishing papers in top IR conferences along the way. Key job responsibilities Develop state-of-the-art web search technology, including training novel retrieval and ranking models, scaling models and optimizing performance, partnering with engineering to deploy and debug model performance in production, and building and scaling quality training data sets.

Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to lead key initiatives in robotic intelligence. As a Principal Applied Scientist, you'll spearhead the development of breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence in areas such as perception, manipulation, science understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll combine hands-on technical work with scientific leadership, ensuring your team delivers robust solutions for dynamic real-world environments. You'll leverage Amazon's vast computational resources to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Lead technical initiatives in robotics foundation models, driving breakthrough approaches through hands-on research and development in areas like open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for specific research initiatives, ensuring robust performance in production environments - Mentor and support fellow scientists while maintaining strong individual technical contributions - Collaborate with engineering teams to optimize and scale models for real-world applications - Influence technical decisions and implementation strategies within your area of focus A day in the life - Develop and implement novel foundation model architectures, working hands-on with our extensive compute infrastructure - Guide and support fellow scientists in solving complex technical challenges, from sim2real transfer to efficient multi-task learning - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions within your team and with key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster - Mentor team members while maintaining significant hands-on contribution to technical solutions 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! About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through ground breaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.