Careers

Amazon’s drone delivery program is focused on getting items to customers quickly, cost-effectively, and safely. At Prime Air, we are building autonomous systems using sophisticated new technologies that are designed to work at scale to serve our customers. We are delivering to customers in multiple locations and are excited for what’s to come as we grow. We are looking for a Principal Applied Scientist to help drive software quality across Prime Air, raising the bar for performance and correctness of software systems. You will define the tools and approaches needed to apply formal verification, runtime assurance, new testing approaches, metric collection, and other methods to software systems. You will be joining a talented full-stack development team (hardware and software) that is laser-focused on developing safe and efficient drone and traffic management solutions that operate efficiently and deliver packages to our customers at scale. You will work with this team to apply new techniques to our systems and to define processes and tools to enable other team members to ensure that software is correctly implemented. Key job responsibilities - As a Principal Applied Scientist at Amazon Prime Air you will: Develop the value proposition for formal verification, runtime assurance, and other methods for software under development and drive building these approaches into every area of our software development processes. Write, validate, and maintain formal models of the hardware and software. Develop and maintain specifications and machine-checked proofs to demonstrate that code is correct. Develop testing and metric collection approaches related to software quality and testing that ensure integration into software processes. Work with senior leaders in the organization and be the single-threaded owner of communicating the vision for software correctness assurance to leaders within Amazon and to external stakeholders.

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.

As part of the AWS Applied AI Solutions organization, we're advancing the frontier of visual reasoning and agentic AI technologies. Our vision is to develop sophisticated AI systems that can understand, interpret, and reason about visual information at human-like levels, enabling breakthrough applications across multiple industries. Key job responsibilities * Develop a novel agentic AI framework to solve diverse visual AI challenges in the physical world * Advance the theory and practice of multi-modal foundation models for visual understanding * Design new approaches to memory and attention mechanisms for processing continuous visual streams * Create innovative techniques for efficient visual processing that can scale to real-world applications * Research new methods for autonomous decision-making based on visual inputs * Investigate approaches to reduce the computational and data requirements of visual reasoning systems A day in the life As an Applied Scientist, you'll conduct fundamental research in visual reasoning while maintaining a clear path to practical applications. You'll investigate novel architectural approaches, develop new theoretical frameworks, and validate ideas through rigorous experimentation. You'll collaborate with other scientists and engineers to transform research insights into scalable solutions, publish your findings in top-tier conferences, and help shape the future direction of visual AI technology. Leveraging and advancing generative AI technology will be a big part of your charter as we seek to apply the latest advancements in generative AI to industry-specific problems About the team Our research team is tackling fundamental challenges in visual reasoning that combine generative AI and agentic frameworks. We're investigating novel approaches to how AI systems understand spatial relationships, reason about object interactions, and maintain contextual awareness across time. Working at the intersection of computer vision and large language models, we're developing theoretical frameworks and practical techniques that advance the state-of-the-art in visual AI. AWS Solutions As part of the AWS solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. we blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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 AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship & 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, mentorship 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Amazon’s Artificial General Intelligence (AGI) organization is developing a next-generation web search system to support RAG applications across Amazon. We are looking for a 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 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 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

Amazon Agentic AI is looking for world class scientists to join its newly created org focusing on agentic AI. This group is entrusted with developing core natural language processing, agents, generative AI, deep learning and machine learning algorithms for AWS, with a focus on code development, broadly defined. You will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually new solutions. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS Agentic AI, a generative AI–powered assistant for enterprise computing, and work with other acclaimed engineers and world famous scientists. As an Applied Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs. You take a long-term view of the business objectives, product roadmaps, technologies, and how they should evolve. You drive mindful discussions with customers, engineers, and scientist peers. You bring perspective and provide context for current technology choices, and make recommendations on the right modeling and component design approach to achieve the desired customer experience and business outcome. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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 AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship & 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, mentorship 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

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

Passionate about books? The Amazon Books personalization team is looking for a talented Applied Scientist II to help develop and implement innovative science solutions to make it easier for millions of customers to find the next book they will love. In this role you will: - Collaborate within a dynamic team of scientists, economists, engineers, analysts, and business partners. - Utilize Amazon's large-scale computing and data resources to analyze customer behavior and product relationships. - Contribute to building and maintaining recommendation models, and assist in running A/B tests on the retail website. - Help develop and implement solutions to improve Amazon's recommendation systems. Key job responsibilities The role involves working with recommender systems that combine Natural Language Processing (NLP), Reinforcement Learning (RL), graph networks, and deep learning to help customers discover their next great read. You will assist in developing recommendation model pipelines, analyze deep learning-based recommendation models, and collaborate with engineering and product teams to improve customer-facing recommendations. As part of the team, you will learn and contribute across these technical areas while developing your skills in the recommendation systems space. A day in the life In your day-to-day role, you will contribute to the development and maintenance of recommendation models, support the implementation of A/B test experiments, and work alongside engineers, product teams, and other scientists to help deploy machine learning solutions to production. You will gain hands-on experience with our recommendation systems while working under the guidance of senior scientists. About the team We are Books Personalization a collaborative group of 5-7 scientists, 2 product leaders, and 2 engineering teams that aims to help find the right next read for customers through high quality personalized book recommendation experiences. Books Personalization is a part of the Books Content Demand organization, which focuses on surfacing the best books for customers wherever they are in their current book journey.