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 self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (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; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at https://www.amazon.com/music. Key job responsibilities We are looking for an Applied Scientist II to lead and drive innovation in spoken word content intelligence. You will provide machine learning leadership to the team that helps accelerate the business. You will build various data and machine learning models that help us innovate different ways to enhance customer experience. About the team The Amazon Music Catalog team is responsible for persisting, computing, reconciling and vending Music and Spoken Word rights and metadata to other teams and services across Amazon. We process millions of updates per day and our services serve tens of thousands of requests per second to all Amazon Music Customers. We own critical platforms that makes access to the Amazon Music Catalog highly available and accessible to every one.

We are looking for passionate, talented, and inventive Principal Applied Scientist with a strong machine learning background to help build industry-leading Conversational AI Systems. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Understanding (NLU), Dialog Systems including Generative AI with Large Language Models (LLMs) and Applied Machine Learning (ML). As part of our team, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use language technology. You will gain hands on experience with Amazon’s heterogeneous text, structured data sources, and large-scale computing resources to accelerate advances in language understanding. We are hiring in all areas of human language technology: NLU, Dialog Management, Conversational AI, LLMs and Generative AI. A day in the life The team uses generative AI and foundation models to reimagine the experience of all customers on AWS. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you.

Amazon’s Artificial General Intelligence (AGI) organization is developing a next-generation web-scale information retrieval system to support RAG applications across Amazon. We are looking for a Sr. Applied Scientist with expertise in information retrieval (IR) and ranking 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 Sr. 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 You will lead a team of scientists to improve our RAG applications. You will be responsible for: (i) developing novel retrieval and ranking models and partnering closely with engineering to improve model performance; (ii) improve content and query understanding models to deliver improved signal to retrieval and ranking models; (iii) partner closely with content acquisition and client teams to ensure our dependencies are met and we’re delivering value to the end customers, enhancing information grounding for LLMs; (iv) develop science roadmaps for critical web search components; (v) publish your work and remain active in the academic communities; (vi) coach and develop junior scientists. A day in the life A mix of (i) technical deep dives: working with the team to develop the right models, setup good experiments, debug models, etc. (ii) coaching and development: providing feedback, setting up mechanisms to ensure the team’s success, and (iii) working with customers and dependency teams to ensure delivery.

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

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

Are you interested in computational advertising and sponsored recommendations? Do you thrive in a fast-paced organization with a significant impact on hundreds of millions of customers? Do you love to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems? If so, Amazon Sponsored Products could be the right place for you. The Sponsored Products (SP) Detail Page Experience, Monetization, and Marketplace Intelligence team is responsible for building compelling advertising experiences on one of the most visited destinations on the internet—Amazon’s product detail pages. We focus on delivering personalized, context-aware ads that align with shopper preferences, adapt to seasonal and event-driven moments, and integrate naturally with organic content such as deals, new arrivals, basket-building features, and fast-delivery options. The team operates full-stack—from auction mechanisms to customer-facing experiences—working closely with Amazon Stores to drive the growth of SP on detail pages. Key job responsibilities We are seeking a seasoned and technically proficient leader to own and expand this space. As a single-threaded leader, you will guide the transformation of the detail page into a high-impact surface for product discovery and monetization through scalable, customer-centric advertising solutions—ranging from fully sponsored content to blended ad-organic formats. This role also entails end-to-end responsibility for marketplace operations, including auction allocation and pricing strategies. The successful candidate will apply a diverse set of signals, such as page context, shopper intent, seasonality, regional trends, delivery speed, and return likelihood, as well as deep learning and generative AI models to enhance customer experience, unlock incremental monetization, reduce cost to serve, and drive sustainable advertiser RoAS (return on ad spend). Additionally, the role involves developing real-time dynamic blending systems that optimize ad load and placement to balance business and customer outcomes. This leader will oversee a cross-functional organization of applied scientists, engineers, and product managers, owning core components such as: Tier-1 auction service for detail pages, innovation across large-scale ML, deep learning, and generative AI/LLMs, and design and deployment of new product experiences that improve discovery and deliver business impact. This is a high-impact leadership role at the intersection of personalization, monetization, product innovation, marketplace dynamics, and machine learning—ideal for a strategic, technically fluent, and customer-obsessed leader ready to shape the future of Sponsored Products advertising on Amazon product detail pages.

The Inventory Planning and Control team is looking for an applied scientist to help build next generation models for supply chain systems in the Supply Chain Optimization Technology (SCOT) group. We own the systems that decide where to place hundreds of millions of units of inventory a week, globally, shaping Amazon’s cost structures and value proposition to the customer and ultimately maximizing Amazon’s long term free cash flow. The work is complex and important to Amazon. There are no textbook solutions to the problems we are solving and very few attempts have been made to solve at Amazon's scale, which necessitates deep analytical thinking to solve problems. As a Applied Scientist, you will work with other Scientists, Software Engineers, Product Managers and business teams to understand the current challenges in our inventory systems, map these challenges to scientific models, innovate solutions using techniques in Operations Research, Machine Learning, Statistics, and Optimization and pick the right tools to deploy these solutions at scale. You will be a part of shaping the future of inventory placement systems at Amazon. Your work will be visible to the business leaders in SCOT and will impact on how we serve our customers so that they get the right product at the right time.

Amazon Japan Store Tech (JST) Science team serves as the core science division of JP Store Tech, with the vision to enable and accelerate the best-in-class CX through state-of-the-art machine learning technologies. This team owns the science vision definition, science roadmap planning, and science solution delivery in key business areas in Japan including Search, Customer Growth and Engagement, Personalization and Delivery. As an Applied Scientist, you will design, implement and deliver models on Amazon site, helping millions of customers every day to find quickly what they are looking for. You will propose innovation to build ML models trained on terabytes of product and traffic data, which are evaluated using both offline metrics as well as online metrics from A/B testing. You will then integrate these models into the production system that serves customers, closing the loop through data, modeling, application, and customer feedback. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times. Key job responsibilities * Invent or adapt new scientific approaches, models or algorithms inspired and driven by customers’ needs and benefits at the project level. * Analyze data and identify the gaps in existing solutions, and propose innovative science solutions. * Contribute to research papers that are published at peer-reviewed internal and/or external venues, and contribute to the wider scientific community. * Working with teams worldwide on global projects. About the team Your benefits include: * Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers * The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems with tangible customer impact * Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and and complex reasoning; with a focus across text, image, and video modalities. As an Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results 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 Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports