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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

Do you want to join an innovative team of scientists who leverage machine learning and statistical techniques to revolutionize how businesses discover and purchase products on Amazon? Are you passionate about building intelligent systems that understand and predict complex B2B customer needs? The Amazon Business team is looking for exceptional Applied Science to help shape the future of B2B commerce. Amazon Business is one of Amazon's fastest-growing initiatives focused on serving business customers, from individual professionals to large institutions, with unique and complex purchasing needs. Our customers require sophisticated solutions that go beyond traditional B2C experiences, including bulk purchasing, approval workflows, and business-grade service support. The AB-MSET Applied Science team focuses on building intelligent systems for delivering personalized, contextual service experiences throughout the customer lifecycle. We apply advanced machine learning techniques to develop sophisticated intent detection models for business customer service needs, create intelligent matching algorithms for optimal service routing based on multiple variables including customer value, maturity, effort, and issue complexity, build predictive models to enable proactive service interventions, design recommendation systems for self-service solutions, and develop ML models for automated service resolution. As an Applied Scientist on the team, you will design and develop state-of-the-art ML models for service intent classification, routing optimization, and customer experience personalization. You will analyze large-scale business customer interaction data to identify patterns and opportunities for automation, create scalable solutions for complex B2B service scenarios using advanced ML techniques, and work closely with engineering teams to implement and deploy models in production. You will collaborate with business stakeholders to identify opportunities for ML applications, establish automated processes for model development, validation, and maintenance, lead research initiatives to advance the state-of-the-art in B2B service science, and mentor other scientists and engineers in applying ML techniques to business problems.

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 Search Ranking and Interleaving (R&I) team within Sponsored Products and Brands is responsible for determining which ads to show and the quality of ads shown on the search page (e.g., relevance, personalized and contextualized ranking to improve shopper experience, where to place them, and how many ads to show on the search page. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of GenAI and ML techniques to continuously explore, learn, and optimize the ranking and allocation of ads on the search page. We are an interdisciplinary team with a focus on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. A day in the life As an Applied Scientist on this team, you will identify big opportunities for the team to make a direct impact on customers and the search experience. You will work closely with with search and retail partner teams, software engineers and product managers to build scalable real-time GenAI and ML solutions. You will have the opportunity to design, run, and analyze A/B experiments that improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact while broadening your technical skillset. Key job responsibilities - Solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. - Drive end-to-end GenAI & Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions. - Develop efficient algorithms for multi-objective optimization using deep learning methods to find operating points for the ad marketplace then evolve them - Research new and innovative machine learning approaches. - Recruit Scientists to the team and provide mentorship.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will work with talented peers to lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI). About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

Are you passionate about building data-driven applied science solutions to drive the profitability of the business? Are you excited about solving complex real world problems? Do you have proven analytical capabilities, exceptional communication, project management skills, and the ability to multi-task and thrive in a fast-paced environment? Join us a Senior Applied Scientist to deliver applied science solutions for Amazon Payment Products. Amazon Payment Products team creates and manages a global portfolio of payment products, including co-branded credit cards, instalment financing, etc. Within this team, we are looking for a Senior Applied Scientist who will be responsible for the following: Key job responsibilities As a Senior Applied Scientist, you will be responsible for designing and deploying scalable ML, GenAI, Agentic AI solutions that will impact the payments of millions of customers and solve key customer experience issues. You will develop novel deep learning, LLM for task automation, text processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. As the Payment Products organization deals with problems that are directly related to payments of customers, the Senior Applied Scientist role will impact the large product strategy, identify new business opportunities and provides strategic direction, which will be very exciting.

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 and implement a modern, fast, and ergonomic development environment for AI researchers, eliminating current pain points in build times, testing workflows, and iteration speed * Build and manage CI/CD pipelines (CodePipeline, Jenkins, etc.) that support large-scale AI research workflows, including pipelines capable of orchestrating thousands of simultaneous agentic experiments * Develop tooling that bridges local development environments with remote supercomputing resources, enabling researchers to seamlessly leverage massive compute from their IDEs * Manage and optimize code repository infrastructure (GitLab, Phabricator, or similar) to support collaborative research at scale * Implement release management processes and automation to ensure reliable, repeatable deployments of research code and models * Optimize container build systems for GPU workloads, ensuring fast iteration cycles and efficient resource utilization * Work directly with researchers to understand workflow pain points and translate them into infrastructure improvements * Build monitoring and observability into development tooling to identify bottlenecks and continuously improve developer experience * Design and maintain build systems optimized for ML frameworks, CUDA code, and distributed training workloads About the team The team is shaping developer experience from the ground up. Building tools that enable researchers to move at the speed of thought: IDEs that seamlessly shell out to supercomputers, CI/CD pipelines that orchestrate thousands of agentic commands simultaneously, and build systems optimized for GPU-accelerated workflows. Your infrastructure will be the foundation that enables the next generation of AI research, directly contributing to our mission of building the most capable agents in the world.

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.

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX AI Lab team is building the AI capabilities powering the Selling Assistant, Amazon's conversational assistant experience for Selling Partners. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the latest advances in Generative AI, going beyond a typical chatbot to provide an intuitive, intelligent, and personalized experience to sellers running real businesses, large and small. Do you want to join an innovative group of scientists, engineers, and product managers who use state-of-the-art Generative AI and Machine Learning technologies to help Amazon create a delightful Selling Partner experience? Do you want to build solutions to real business problems by automatically understanding and addressing sellers’ challenges, needs and opportunities? Are you excited by the prospect of contributing to one of Amazon’s most strategic Generative AI initiatives? If yes, then you may be a great fit to join the SPX AI Lab team. Key job responsibilities - Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team SPX AI Lab is a growing team of scientists driving the research and development of the next generation of GenAI experiences that empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.

Amazon’s Artificial General Intelligence (AGI) organization is developing a next-generation web search system to support RAG applications across Amazon. Web search is a foundational capability for enabling AGI products across Amazon. We are looking for a Applied Scientist with expertise in information retrieval (IR), content understanding, and natural language processing (NLP) to join the team! If you are looking for an opportunity to develop innovative solutions to deep technical problems in web-scale IR, having a massive customer impact, this might be the role for you! As a Applied Scientist, you will work with smart, passionate colleagues in a fast-paced environment. You will invent, develop, and help deploy novel, scalable algorithms to advance the state-of-the-art in our IR stack. You will keep up with relevant research in the field of IR and publish your work in top-tier conferences. You will develop and help lead the execution of multi-year research roadmaps, enabling the team to focus on the right technical challenges to delight our customers. Key job responsibilities As an Applied Scientist, you will apply scientific rigor to your work. You will deliver incrementally, setting up and executing experiments informed by rigorous failure space analysis of prior experiments. You have a knack for writing clear, succinct and informative reports of your experiments. You collaborate and seek guidance from other scientists on your team to define the next experiments. You collaborate closely with engineers to bring your innovations into production. You will continuously with customers and stakeholders to simplify and adapt to deliver for our customers. You will 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.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Our team owns personalization, guidance and experimentation science and is placed centrally in the organization which owns the Amazon Advertising Console from UX design to components and services. We leverage a breadth of state-of-the-art techniques such as deep learning, reinforcement learning, LLMs, long term causal modeling as well as sophisticated A/B testing to develop personalized experiences with directly quantifiable business and advertiser success outcomes. We are looking for an accomplished machine learning expert to lead the Applied Science strategy for our recommendation creation and recommendation personalziation program. In this role, you will work closely with business leaders, stakeholders and cross-functional teams to drive program success through ML-driven solutions. You will shape the applied science roadmap, promote a culture of data-driven decision-making, and deliver significant business impact for millions of advertisers worldwide and the company using advanced data techniques and applied science methodologies. Key job responsibilities As an Applied Scientist on this team, you will - Serve as the technical leader in Machine Learning, driving collaboration between scientists and engineers, guiding efforts within the team and collaborating with other teams. - Conduct hands-on analysis and modeling of large-scale data to generate insights that boost ads revenue while maintaining a positive advertiser and shopper experience. - Lead end-to-end Machine Learning projects that involve high levels of ambiguity, scale, and complexity. - Build, experiment, optimize, and deploy machine learning models, collaborating with software engineers to bring your models into production. - Run A/B experiments, gather data, and perform statistical analysis to validate your models. - Develop scalable and automated processes for large-scale data analysis, model development, validation, and serving. - Explore and research innovative machine learning approaches to push the boundaries of what’s possible.