Careers

We are Amazon's central Responsible AI team. Our mission is to advance the science and practice of Responsible AI (RAI) to enable Amazon's tens of thousands of builders to build and deploy AI solutions to the high standards that our customers and society expect. As a scientist on this team, you will: - understand in depth the technical and scientific issues related to RAI, including controllability, security, privacy, safety, veracity, robustness, fairness, explainability, transparency, and governance - help define the strategies, priorities and metrics for RAI - solve open problems in RAI to unblock traditional, generative and/or agentic AI use cases and solutions, publishing as appropriate - help develop our team - liase with internal and external stakeholders, including the academic community, on issues related to RAI About the team Diverse Experiences Amazon Security 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 Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 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.

Amazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. Are you an expert in Natural Language Processing (NLP), computer vision Large Language Models (LLM) and multi-modality? Are you interested in building Generative AI solutions on complex business problems that have significant global benefit. The Brand Protection Science team designs and builds high performance AI systems using machine learning and deep learning that identify and prevent infringement and counterfeit on behalf of brand owners worldwide. We are looking for a highly talented scientist to help build of our AI vision for Brand Protection. As a applied scientist on the team, you will use SOTA AI and ML techniques to understand and extract key information from product detail page, built automated AI solutions that thinks like human to make autonomous decisions. You will work backwards from data insights and customer feedback to build the right machine learning solutions, and resourceful in finding innovative solutions to unsolved problems. You will work closely will product team and engineering partners to launch the solution into production and own the end-to-end solution. An ideal candidate should be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied scientist, you will own the design and development of end-to-end AI solutions, from conception to launch in a rapidly evolving environment. You’ll have the opportunity to create science roadmaps, and drive production level projects that will support Amazon Science. extensive experience driving Machine Learning initiatives, specially in NLP and LLM applications, from conception to launch in a rapidly evolving environment. You will work closely with other scientists and enigneers to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Major responsibilities: - Understand business challenges by analyzing data and customer feedback - Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement - Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems. - Use deep learning and machine learning techniques to create scalable solutions for business problems - Create business and analytics reports and present to the senior management teams - Research and implement novel AI solutions and publish research papers Key job responsibilities Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work. For more information on the Amazon Science community please visit https://www.amazon.science.

The Amazon Fulfillment Technologies (AFT) Science team is looking for an exceptional Data Scientist, with strong analytical skills and understanding of optimization, to partner with scientists, engineers, product managers, and operations leaders, and develop data-driven solutions for one of the most complex systems in the world: Amazon’s Fulfillment Network. At AFT Science, we design, build and deploy optimization, simulation, and machine learning solutions to power the production systems running at world wide Amazon Fulfillment Centers. We solve a wide range of problems that are encountered in the network, including labor planning and staffing, demand prioritization, stow guidance, pick scheduling, and flow process optimization. We are tasked to develop innovative, scalable, and reliable science-driven solutions that are beyond the published state of art in order to run frequently (ranging from every few minutes to every few hours per use case) and continuously in our large scale network. Key job responsibilities As an Data Scientist, you will work with other scientists, software engineers, product managers, and operations leaders to develop scientific solutions and analytics using a variety of tools and observe direct impact to process efficiency and associate experience in the fulfillment network. Key responsibilities include: - Design and conduct rigorous experimental design for production pilots to evaluate the impact of the solution and improve model performance - Lead the end-to-end lifecycle of forecasting models, from research and experimentation through production launch including defining success metrics, obtaining stakeholder sign-off, and managing rollout - Develop and deploy production grade ML and statistical models using Python, Scala, SQL, and related tools - Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development - Translate complex science findings into clear insights and recommendations for technical and non-technical stakeholders at all levels - Contribute to Amazon's scientific community and the broader research field through collaboration and presentation in top-tier venues About the team Amazon Fulfillment Technology (AFT) designs, develops and operates the end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FC). We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT Science team has expertise in operations research, optimization, statistics, simulation, and machine learning. We also have domain expertise in the operational processes within the FCs and their defects. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment which includes both developing novel solutions or improving existing approaches. Resulting production systems rely on a diverse set of technologies, our teams therefore invest in multiple specialties as the needs of each focus area evolves.

Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like Echo, Fire Tablets, Fire TV, and other consumer devices. We are looking for exceptional scientists to join our Applied Science team to advance the state-of-the-art in developing efficient multimodal language models across our product portfolio. Through close hardware-software integration, we design and train models for resource efficiency across the hardware and software tech stack. The Silicon and Solutions Group Edge AI team is looking for a talented Applied Scientist who will develop new evaluation methods for multimodal language models and agents for our devices, including audio and vision experiences. Key job responsibilities Collaborate with cross-functional engineers and scientists to advance the state of the art in multimodal model evaluations for devices, including audio, images, and videos Invent and validate reliability for novel automated evaluation methods for perception tasks, such as fine-tuned LLM-as-judge Develop and extend our evaluation framework(s) to support expanding capabilities for multimodal language models Analyze large offline and online datasets to understand model gaps, develop methods to interpret model failures, and collaborate with training teams to enhance model capabilities for product use cases Work closely with other scientists, compiler engineers, data collection, and product teams to advance evaluation methods. A day in the life As a Sr. Applied Scientist with the Silicon and Solutions Group Edge AI team, you'll contribute to innovative methods for evaluating new product experiences and discover ways to enhance our model capabilities and enrich our customer experiences. You'll have opportunities to collaborate across teams of engineers and scientists to bring algorithms and models to production. About the team Our Edge AI science team brings together our unique skills and experiences to deliver state-of-the-art multimodal AI models that enable new experiences on Amazon devices.

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art 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 This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond!

We are seeking an Applied Scientist to focus on Robotics Spatial Intelligence and Semantic Understanding. In this role, you'll research and build advanced semantic and world understanding algorithms that enable robots to observe, understand, and reason about complex and dynamic home environments. You'll work across a broad spectrum of 3D perception, contextual understanding, and world modeling approaches to build robust solutions that support autonomous decision making, task planning, navigation, and manipulation. Key job responsibilities - Develop and implement robust World Understanding and Modeling algorithms for a domestic robot. - Build simulation-based and on-robot evaluation frameworks with comprehensive benchmarks and metrics for systematic evaluation of Our Spatial Intelligence stack. - Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world performance. - Collaborate with navigation, manipulation, and other teams to ensure seamless integration of World Understanding capabilities. - Stay current with the latest advances in World Modeling, Spatial Reasoning, and related fields and apply relevant findings to improve system performance About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! We're looking for a Applied Scientist with a background in developing simulations for traffic management algorithms, including expert knowledge in strategic deconfliction, tactical deconfliction, or detect-and-avoid systems. Managing a large number of concurrent autonomous drone flights that share airspace with other autonomous or manned aircraft is a challenging problem. Be part of the team building simulation tools and algorithms to solve this at scale. This role will contribute to a portfolio of simulation tools managing concurrent airspace traffic for aviation systems. This will include developing new methodologies in the areas of conflict detection and resolution, as well as developing related software systems that will be used in operation to enable package delivery at scale. The ideal candidate is comfortable with risk-taking and ambiguity and able to build consensus on critical, controversial technical decisions. If you enjoy the process of solving real-world problems that haven’t been solved at scale anywhere before, Prime Air is right for you. Along the way, we guarantee you’ll get opportunities to be a disruptor, prolific innovator, and a reputed problem solver and directly impact Amazon’s customers worldwide. Key job responsibilities The primary focus of this role will be on modeling traffic management frameworks that use a layered conflict detection and resolution strategy to ensure safe and efficient flight operations. This will include developing fundamental simulation infrastructure code, including discrete event simulation tooling. In addition, it will involve developing expert knowledge of the layers of mitigation and conducting in-depth scientific research on alternative solutions for conflict resolution. The candidate will contribute to significant and impactful systems that will provide value for Amazon customers and will drive these projects from the concept stage through development. This role will include substantial software development in prototyping and production environments.

We are seeking an Applied Scientist to focus on Robotics Localization, Mapping, and Geometric Reconstruction. In this role, you'll research and build advanced SLAM and World Reconstruction algorithms that enable robots to know its pose in the world and fulfill various tasks in complex and dynamic home environments. You'll work across a broad spectrum of visual inertial odometry, 3D pose estimation, mapping, and geometric reconstruction problems to build robust solutions that support autonomous decision making, task planning, navigation, and manipulation. Key job responsibilities - Develop and implement robust robot state estimation, pose estimation, mapping, and reconstruction algorithms. - Build simulation-based and on-robot evaluation frameworks with comprehensive benchmarks and metrics for systematic evaluation of our spatial intelligence stack. - Lead scientific and technical projects across the spatial intelligence team. - Collaborate with navigation, manipulation, and other teams to ensure seamless integration of localization, tracking, and mapping capabilities. - Mentor junior scientists and engineers to solve real-world robotics problems. About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

Every day, Amazon Japan delivers millions of packages to customers' doors. Behind every routing decision, capacity plan, and network design is a modeling problem — and the science behind how those models learn, generalize, and improve in production is where you come in. JP OPS STAR Foundation is the applied science and engineering team that builds the decision systems powering Amazon Japan's transportation operations. We sit at the intersection of generative AI, large-scale optimization, and graph-based learning — developing models that turn complex operational structure into actionable intelligence. As an applied scientist, you will formulate and solve research problems that directly shape operational outcomes. Your work will span: - LLM-based agent systems — designing agentic architectures with structured evaluation frameworks that measure reasoning quality, tool use accuracy, and task completion under real operational constraints - GPU-optimized model serving and training — developing pipelines for large model inference and fine-tuning, with rigorous benchmarking of latency, throughput, and cost trade-offs - Graph representation learning — building graph neural network models that capture logistics network topology and learn node/edge representations for downstream prediction and optimization tasks You will own problems end-to-end: from formulation and experimentation through deployment and continuous measurement in production. We expect scientific rigor — well-designed experiments, proper baselines, quantified uncertainty — and the engineering judgment to make your methods work reliably at scale. This is a high-autonomy, high-impact role. You will collaborate with data engineers, BIEs, and operations leaders, and you will have the freedom to define your research agenda within our problem space. We value scientists who publish and share their work, and who treat production performance as ground truth for their ideas. At Amazon, you'll work alongside the latest AI and GenAI tools that are increasingly woven into how teams operate: from AI-powered capabilities that accelerate decision-making, to Generative AI that helps you focus on work that truly matters. You'll have opportunities and resources to develop AI fluency at your own pace, with continuous learning built into the culture. Key job responsibilities - Formulate and solve modeling problems for LLM-powered agent systems (MCP servers, text-to-SQL, RAG), designing validation methods and confidence scoring for reliable outputs under operational constraints. - Design evaluation frameworks for AI agents: define metrics for reasoning quality and task completion, build backtesting pipelines, and develop automated regression detection. - Research and implement graph neural network architectures to learn structural representations of logistics networks; develop training methodology and evaluation protocols for production deployment. - Develop GPU-optimized pipelines for model training and inference, with rigorous benchmarking of latency, throughput, and cost trade-offs. - Own the scientific lifecycle end-to-end: problem formulation, experimental design, deployment, and continuous measurement against real operational outcomes. - Collaborate with data engineers and operations stakeholders to validate model outputs and quantify business impact. A day in the life - Diagnose a confidence-score drift in the agent eval dashboard, trace the root cause to a schema change, and redesign the validation logic to be schema-invariant. - Experiment with a graph attention architecture on the logistics network; benchmark against the baseline embedding on a downstream prediction task. - Profile a GPU training job to unblock a scaling experiment, identify a memory bottleneck, and restructure the data loader to halve iteration time. - Present model accuracy trends to operations leaders and recommend threshold adjustments based on the data.

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 subscriptions such as Apple TV+, HBO Max, Peacock, 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 team member, 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 As a highly experienced and seasoned science leader, you will apply state of the art natural language processing and computer vision research to video centric digital media, while also responsible for creating and maintaining the best environment for applied science in order to recruit, retain and develop top talent. You will lead the research direction for a team of deeply talented applied scientists, creating the roadmaps for forward-looking research and communicate them effectively to senior leadership. You will also hire and develop applied scientists - growing the team to meet the evolving needs of our customers. About the team This team's mission is to deeply understand all content and empower all customers with relevant language options, innovative accessibility assists, and rich title-information across all their content-experiences on Prime Video. We create and publish content on-time that's meaningful, accurate, and accessible to every customer globally. We delight our customers by pushing the boundaries of content understanding and enrichment. Through inclusion and innovation, we do the most fulfilling work of our career.