Careers

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 Data Scientist Manager (DSM) to lead an embedded science team supporting experiment design, evaluation, and decision-making within Prime Video Personalization and Discovery. The ideal candidate brings strong problem-solving skills, stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. You will build cross-functional support within Prime Video, assess business problems, define metrics, and support iterative scientific solutions that balance short-term delivery with long-term science roadmaps. Key job responsibilities - Manage and develop data scientists specializing in experimentation and customer analytics - Own customer segmentation models to understand diverse streaming behaviors and forecast how customers respond to personalization changes - Partner closely with product managers to translate business questions into actionable science projects - Influence product roadmaps through data-driven insights on customer behavior patterns

We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale. You will work backwards from the needs of advertisers—delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production. Key job responsibilities - Lead business, science and engineering strategy and roadmap for Sponsored Products Agentic Advertiser Guidance. - Design and build agents to guide advertisers in conversational and non-conversational experience. - Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO). - Curate datasets and tools for MCP. - Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails. - Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning. - Prototype and iterate on multi-agent orchestration frameworks and workflows. - Collaborate with peers across engineering and product to bring scientific innovations into production. - Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest 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 Advertiser Guidance team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our vision is to build a highly personalized, context-aware agentic advertiser guidance system that leverages LLMs together with tools such as auction simulations, ML models, and optimization algorithms. This agentic framework, will operate across both chat and non-chat experiences in the ad console, scaling to natural language queries as well as proactively delivering guidance based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities—from high-level product guidance down to granular keyword recommendations—and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. We’re looking for scientists with deep LLM expertise to help us build the next generation of large language models. Our team focuses on post-training, including instruction tuning, reward modeling, and reinforcement learning. In this role, you will design and run large-scale experiments, analyze model behavior, and develop new training recipes that directly improve core capabilities like reasoning, user experience, and other frontier paradigms that redefine what LLMs can do. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

Are you interested in a unique opportunity to advance the accuracy and efficiency of Artificial General Intelligence (AGI) systems? If so, you're at the right place! We are the AGI Autonomy organization, and we are looking for a driven and talented Member of Technical Staff to join us to build state-of-the art agents. Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities * Design, build, and maintain the compute platform that powers all AI research at the SF AI Lab, managing large-scale GPU pools and ensuring optimal resource utilization * Partner directly with research scientists to understand experimental requirements and develop infrastructure solutions that accelerate research velocity * Implement and maintain robust security controls and hardening measures while enabling researcher productivity and flexibility * Modernize and scale existing infrastructure by converting manual deployments into reproducible Infrastructure as Code using AWS CDK * Optimize system performance across multiple GPU architectures, becoming an expert in extracting maximum computational efficiency * Design and implement monitoring, orchestration, and automation solutions for GPU workloads at scale * Ensure infrastructure is compliant with Amazon security standards while creatively solving for research-specific requirements * Collaborate with AWS teams to leverage and influence cloud services that support AI workloads * Build distributed systems infrastructure, including Kubernetes-based orchestration, to support multi-tenant research environments * Serve as the bridge between traditional systems engineering and ML infrastructure, bringing enterprise-grade reliability to research computing About the team This role is part of the foundational infrastructure team at the SF AI Lab, responsible for the platform that enables all research across the organization. Our team serves as the critical link between Amazon's enterprise infrastructure and the Lab's research needs. We are experts in performance optimization, systems architecture, and creative problem-solving—finding ways to push the boundaries of what's possible while maintaining security and reliability standards. We work closely with research scientists, understanding their experimental needs and translating them into robust, scalable infrastructure solutions. Our team has deep expertise in ML framework internals and GPU optimization, but we're also pragmatic systems engineers who build traditional infrastructure with enterprise-grade quality. We value engineers who can balance research velocity with operational excellence, who bring curiosity about ML while maintaining strong fundamentals in systems engineering. This is a small, high-impact team where your work directly enables breakthrough AI research. You'll have the opportunity to work with some of the most advanced AI infrastructure in the world while building the skills that define the future of ML systems engineering.

About Sponsored Products and Brands: 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. About Our Team: The Sponsored Brands Impressions-based Offerings team is responsible for evolving the value proposition of Sponsored Brands to drive brand advertising in retail media at scale, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As a Principal Scientist for the team, you will have the opportunity to apply your deep subject matter expertise in the area of ML, LLM and GenAI models. You will invent new product experiences that enable novel advertiser and shopper experiences. This role will liaise with internal Amazon partners and work on bringing state-of-the-art GenAI models to production, and stay abreast of the latest developments in the space of GenAI and identify opportunities to improve the efficiency and productivity of the team. Additionally, you will define a long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of applied scientists and engineers. This role will play a critical role in elevating the team’s scientific and technical rigor, identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. You will communicate learnings to leadership and mentor and grow Applied AI talent across org. * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Design and conduct 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. * Think big about the arc of development of Gen AI over a multi-year horizon and identify new opportunities to apply these technologies to solve real-world problems. #GenAI

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through novel 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 ecosystem. 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 As an applied scientist on our team, you will * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build recommendation systems that leverage generative models to develop and improve campaigns. * You invent and design new solutions for scientifically-complex problem areas and/or opportunities in new business initiatives. * You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses; * Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Stay up-to-date with advancements and the latest modeling techniques in the field About the team The Sponsored Brands Impressions-based Offerings team is responsible for evolving the value proposition of Sponsored Brands to drive brand advertising in retail media at scale, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. #GenAI

The Private Brands team is looking for a Sr. Research Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business and develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Scientists, Engineers, PMTs and Economists. Key job responsibilities You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a Sr Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. We are particularly interested in candidates with experience in Operations Research, ML and predictive models and working with distributed systems. Academic and/or practical background in Operations Research and Machine Learning specifically Reinforcement Learning are particularly relevant for this position. To know more about Amazon science, Please visit https://www.amazon.science About the team We are a one pizza, agile team of scientists focused on solving supply chain challenges for Amazon Private Brands products. We collaborate with Amazon central teams like SCOT and develop both central as well as APB-specific solutions to address various challenges, including sourcing, demand forecasting, ordering optimization, inventory distribution, and inventory health management. Working closely with business stakeholders, Product Management Teams (PMTs), and engineering partners, we drive projects from initial concept through production deployment and ongoing monitoring.

Amazon Industrial Robotics 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 Industrial Robotics 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

Help re-invent how millions of people watch TV! Fire TV remains the #1 best-selling streaming media player in the US, with over 100 million active users. Our goal is to be the global leader in delivering entertainment, with the broadest selection of content, innovative devices, and personalized experiences for customers. Our Fire TV Science team is an interdisciplinary group working at the intersection of Language Understanding (LU), Recommender Systems, Information Retrieval, and Machine Learning (ML). Through close collaboration with engineering and product teams, we develop and deploy innovative algorithms that enhance content discovery and customer engagement. Within this team, our Language Understanding sub-team owns all query understanding components and models that power search and content discovery on Fire TV. Our work directly contributes to making our devices delightful to use and indispensable for the household. Key job responsibilities - Be a hands-on lead for our Language Understanding (LU) sub-team, owning all our query understanding components and models - Lead and mentor a team of 6 scientists, fostering their professional development and technical growth while establishing and executing the research vision - Collaborate closely with Search and Recommendations workstreams within the broader Fire TV Science team, contributing to cross-functional initiatives and expanding technical influence beyond the LU domain - Drive end-to-end impact by designing scalable solutions that systematically address technical challenges and deliver lasting customer benefit - Balance and prioritize multiple workstreams spanning long-term research, applied projects, and production support to ensure high-impact outcomes - Drive adoption of state-of-the-art approaches across the organization by staying at the forefront of relevant technological advances, spanning language understanding models, LLM evaluations, prompt engineering, search and personalization models, and more A day in the life As the Language Understanding sub-team lead, you'll balance hands-on technical work with team leadership and cross-functional collaboration. Your day might include conducting and reviewing model evaluations, interfacing with the Alexa central team on LLM routing and architectural design questions, resolving domain conflicts, and brainstorming with Search and Recommendations leads to explore synergies. You'll dive into code to prototype novel query understanding approaches, prioritize production issues, and engage with engineering and product partners on upcoming features. Throughout, you'll challenge the status quo, identify automation opportunities to free time for higher-impact work, and stay current with NLU research. The role involves regular travel between our two sites.

Amazon’s FinOps Global Data Analytics’s (GDA) science team seeks a Data Scientist with the technical expertise and business intuition to invent the future of Accounts Receivable and Account Payable at Amazon. As a key member of the science team, the Data Scientist will own high-visibility analyses, ML and AI methodology, and algorithms in the Order-to-Cash (O2C) and Procure-to-Pay lifecycles to drive free cash flow and efficiency for Amazon Finance Operations. This is a unique opportunity in a growing data science and economics team with a charter to optimize operations and planning with complex trade-offs between customer experience, credit risk, cash flow, and operational efficiencies. Key job responsibilities The Data Scientist's responsibilities include, but are not limited to the following points: - Extract and analyze large amounts of data from Order-to-Cash and Procure-to-Pay processes and associated business functions. - Adapt statistical, machine learning, GenAI, and agentic methodologies for Finance Operations by developing and testing models, running computational experiments, and fine-tuning model parameters. - Use computational methods to identify relationships between business data and outcomes, define outliers and anomalies, and justify those outcomes to business customers. - Communicate verbally and in writing to business customers with various levels of technical knowledge, educate stakeholders on our research and data science practice, and deliver actionable insights and recommendations - Develop code to analyze data (SQL, PySpark, Scala, etc.) and build statistical and machine learning models and algorithms (Python, R, Scala, etc.). - Collaborate with business and operational stakeholders and product managers to innovate on behalf of customers leveraging data science methodologies, and partner with engineers and scientists to design, develop, and scale machine learning and AI models A day in the life As a successful data scientist in GDA’s Science team, you will dive deep on data from across Amazon's numerous businesses, extract new assets, drive investigations and algorithm development, and interface with technical and non-technical customers. You will leverage your data science expertise and communication skills to pivot between delivering science solutions, translating knowledge of finance and operational processes into models, and communicating insights and recommendations to audiences of varying levels of technical sophistication in support of specific business questions, root cause analysis, planning, and innovation for the future. The role will work in a genuinely global environment, across various functional teams; with daily interaction across India, US, and Europe. About the team Global Data Analytics (GDA) supports decisions in AR and AP. In close cooperation with our stakeholders, we agree and build uniform metrics; use data from a ‘single source of truth’; provide automated, self-service, standard reporting; and build predictive analytics. Our topmost ambition is to actively contribute to the improvement of Amazon's Free Cash Flow by value-adding analytics. Our success is built on users' trust in our data and the reliability of our analytics tools. GDA’s data scientists and economists further that mission with rigorous statistical, econometric, and ML models to compliment reporting and analysis developed by GDA’s analytical, BI, and Finance professionals.