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.

The R2L team is responsible for building the next generation supply chain for Amazon's world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes! The R2L Science & AI team is the centralized data science and AI function serving all R2L business verticals. We drive data informed decision making and build AI-powered products that optimize every stage of R2L's operational pipeline from supply chain planning through last-mile delivery. We are looking for a customer-focused, solutions-oriented Senior Manager, Data Science to lead and scale the data science function within the R2L organization. In this role, you will build and manage a high-performing team of Data Scientists and BI Engineers while owning the AI technical roadmap for R2L. You will be responsible for delivering data science and AI solutions that drive measurable operational improvements across R2L's end-to-end network including Supply Chain, Operations, Delivery, Operational Excellence, and Finance. This is a people leadership role with deep technical expectations. You will set the technical vision, hire and develop talent, and partner with senior leaders across R2L and external stakeholders to ensure data science and AI investments are aligned with business priorities and deliver outsized impact. Key job responsibilities - Build and manage a team of Data Scientists and BI Engineers - Define and drive the multi-year vision for Science and AI roadmap for R2L, aligning investments with business priorities to deliver measurable efficiency and customer experience improvements - Define and execute the Gen AI strategy for R2L, identifying high-impact use cases for LLMs, agentic AI, and automation across operational workflows - Influence VP and Director-level leaders through data-driven narratives, technical deep dives, and business impact framing - Educate senior leaders about and advocate for high-quality measurement as an input to data-driven decisions - Raise the technical bar across the organization through mentorship, artifact reviews, and establishing best practices for experimentation, model development, and deployment - Stay up-to-date on the latest data science, measurability, AI tools, techniques, and best practices and help evangelize them across the organization A day in the life 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: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 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!

Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Design and implement whole body control methods for balance, locomotion, and dexterous manipulation - Utilize state-of-the-art in methods in learned and model-based control - Create robust and safe behaviors for different terrains and tasks - Implement real-time controllers with stability guarantees - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for loco-manipulation - Mentor junior engineer and scientists

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.

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.

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers, and is becoming the conversational AI interface for Amazon services with the launch of Alexa for Shopping on Amazon.com and Amazon mobile app. At Alexa Ads, we are creating industry's first and most advanced Agentic Advertising products to drive Agentic Commerce. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa Agentic/Conversational Ads and Personalization. In this role, you will build machine learning models that seamlessly and naturally integrate relevant advertising into the Alexa experience while deeply personalizing user interactions. You will work closely with other scientists, engineers, and product managers to take models from conception to production. Key job responsibilities - Design, develop, and evaluate innovative machine learning and deep learning models for natural language processing (NLP), recommendation systems, and personalization. - Conduct hands-on data analysis and build scalable ML pipelines. - Design and run A/B experiments to measure the impact of new models on customer experience and ad performance. - Collaborate with software development engineers to deploy models into high-scale, real-time production environments. About the team We are building a new science team in Bangalore to solve some of the most impactful problems in computational advertising. This isn't about tweaking existing models as we are rethinking how ads are ranked, priced, and personalized across voice-first and screen-first surfaces. These are problems that don't have textbook solutions. Key points to note about the team: 🧪 Greenfield team - you are not joining a mature org with rigid processes. You will shape the science roadmap, pick the problems, and define the culture from day one. 📈 Direct business impact — your models directly drive revenue. No yearly cycles to see if your work matters. 🌏 Global scope, local autonomy — collaborate with scientists and engineers across Seattle, Sunnyvale, and Bangalore, but own your problem space end-to-end. 🎓 Ship AND Publish: We encourage top-tier publications (NeurIPS, ACL, EMNLP, KDD, ICML, WWW) while ensuring your research hits production.

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.

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.

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.

Come join the Device connectivity team in building the next generation of innovative wireless solution that create a magical experience on our products and services. We actively engage in strategic initiatives, foster partnerships with industry and academia, leverage foundational artificial intelligence and large language models to stay at the forefront of the technological advancements. We are seeking an experienced Applied Science Manager to lead and grow a team of applied scientists who are pushing the boundaries of AI/ML in wireless connectivity and sensing. In this role, you will combine deep technical expertise with strong people leadership to drive scientific innovation that directly impacts millions of customers worldwide. Key job responsibilities As a Applied Science Manager in the team, you will: Build, mentor, and develop a high-performing team of applied scientists, setting the technical bar through code reviews, design reviews, and hands-on contributions while fostering a culture of scientific excellence, innovation, and operational rigor. Define and drive the AI/ML science roadmap for wireless solutions by developing a deep understanding of Amazon's Devices and Services offerings, translating complex business problems into well-defined scientific challenges, identifying high-risk and high-impact technical directions, and guiding your team to deliver them from conception through production. Collaborate cross-functionally with engineering, product, and business partners to drive ML development from research through optimization and onto production devices, aligning science investments with product goals while meeting on-device performance, latency, and resource constraints. Balance exploratory research with production delivery timelines, ensuring the team maintains scientific rigor while meeting business commitments. Represent the team's AI innovations to both internal leadership and the external scientific community through leadership reviews, publications, patents, and conference presentations, providing clear articulation of science strategy, progress, and impact. About the team About the team Device Connectivity team is empowering possibilities through wireless innovation on our devices and through services, our vision is to design and develop transformative products and services that consistently exceed our customers' expectations.