careers-lead-image

Careers

At Amazon, we believe that scientific innovation is essential to being the most customer-centric company in the world. Our scientists' ability to have an impact at scale allows us to attract some of the brightest minds across diverse fields including artificial intelligence, robotics, computer vision, economics, and sustainability. Join us in pioneering solutions to complex challenges that not only delight our customers but also help define the future of technology.
  • The program is designed for academics from universities around the globe who want to work on large-scale technical challenges while continuing to teach and conduct research at their universities.
  • The program offers recent PhD graduates an opportunity to advance research while working alongside experienced scientists with backgrounds in industry and academia.
  • Our internship roles span research areas to provide hands-on experience working alongside world-class scientists and engineers to advance the state of the art in your field.
734 results found
  • US, NY, New York
    Job ID: 10441249
    (Updated 4 days ago)
    Amazon Web Services (AWS) is looking for a Principal Applied Scientist to join the Quick Science team. Quick is AWS’s enterprise generative AI assistant that helps users answer questions, summarize documents, generate content, take actions, and automate workflows using information across enterprise systems. As a key member of this team, you will lead research and development efforts in generative AI and Agentic AI to enable intelligent agents that perform complex reasoning, automate multi-step workflows, and make enterprise users significantly more productive. Key job responsibilities You’ll work on building and optimizing multi-modal foundation models, training and fine-tuning state-of-the-art LLMs, and architecting systems that scale efficiently across domains. This role blends science leadership, hands-on innovation, and deep collaboration with engineering teams to bring research into production.
  • (Updated 5 days ago)
    At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale. Key job responsibilities In this role you will build and maintain the data infrastructure that powers our robotics manipulation research. You'll work alongside our existing team of platform engineers to extend the systems that turn raw robot session data into curated, trainable episodes. This team owns streaming ingestion pipelines, platform and schema design, heterogeneous data sources, data curation and quality controls, full-stack inspection and dataset-builders that researchers and human annotators actually use, and tools to let scientists go from dataset to training job without leaving the platform. We run on a modern cloud-native stack — distributed compute on Kubernetes, streaming data infrastructure, columnar lakehouse storage, and a TypeScript/React frontend. We’re looking for engineers willing and eager to work on the full stack in a fast iteration cycle while working with researchers as close customers. What matters is that you can ship full-stack data infrastructure real users depend on, treat researchers as collaborators rather than customers, and have a strong bias toward iteration in a flat org where engineers pick up science-driven work directly instead of waiting for approval layers.
  • (Updated 5 days ago)
    Amazon is looking for a talented Postdoctoral Scientist to join the Fleet Science team at Amazon Robotics for a one-year, full-time research position with an optional extension for a second year. This Postdoctoral Scientist will advance AI-driven optimization of operations workflows for robotic fulfillment at scale. Research areas include automated optimization formulation that enables non-expert users to formulate, solve, and interpret complex optimization problems through natural language, intelligent solver configuration that adapts to problem structure for significant performance gains, and fleet-level AI for dynamic task allocation methods that coordinate decisions across large robot fleets in real time. The postdoc will have the opportunity to develop scalable solutions that democratize and accelerate optimization workflows for the world's largest robotic fulfillment network. At Amazon, we experiment and innovate relentlessly. Science is core in our offering to shoppers, advertisers and customers. Our scientists apply machine learning, optimization, and probabilistic modeling at scale to enhance customer experience, help advertisers reach relevant audiences, and support brand building. We are seeking talented scientists to invent cutting-edge techniques in a variety of areas and innovate on behalf of shoppers, advertisers, and customers. Key job responsibilities In this role you will: - Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon's vibrant and diverse global science community. - Publish your innovation in top-tier academic venues and hone your presentation skills. - Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. A day in the life On a typical day in this role, you will work to progress your research projects, meet with engineering, systems, and solutions stakeholders, brainstorm with other scientists on the team, and participate in team processes. You will lead your AI-based optimization research through the full life cycle, from design and implementation to evaluation and analysis. Publication of findings in top-tier academic venues is expected. About the team The Fleet Science team at Amazon Robotics is a multi-disciplinary science team that includes scientists with backgrounds in planning and scheduling, optimization, machine learning, and operations research. We develop novel planning algorithms and machine learning methods and apply them to real-world robotic warehouses, including: (1) Planning and coordinating the paths of thousands of robots (2) Dynamic allocation and scheduling of tasks to thousands of robots (3) Learning how to adapt system behavior to varying operating conditions and (4) Co-design of robotic logistics processes and the algorithms to optimize them.
  • US, WA, Bellevue
    Job ID: 10438958
    (Updated 6 days ago)
    Amazon has the world's most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. We need your skills to optimize our supply chain, with the end goal of delighting our customers. A core part of the supply chain operations is Demand Forecasting: We forecast the demand of tens of millions of products. These forecasts are used to make many decisions, such as automatically order hundreds of millions worth of inventory, decide where to place that inventory, and establish labor plans for hundreds of warehouses. The Product Data Science team within Forecasting & Labs (part of Supply Chain Optimization Technologies) is looking for an analytical and technically skilled Data Scientist to join our team. Our team is responsible for bias correction model development and A/B testing for forecast improvements, GenAI/LLM research for forecast explainability, and deep analytics for Labs and Foundation Models. We work horizontally across the forecasting product portfolio—including National, Regional, Grocery, SSD, Inbound, and CIV forecasting—to embed advanced analytics and machine learning solutions where they create the most value. This position will be responsible for developing and supporting data science methodologies and building models to address ambiguous forecasting questions. The Data Scientist will design and analyze experiments (A/B tests) to measure the impact of forecast model changes, develop bias correction models to improve forecast accuracy, and contribute to GenAI/LLM-based approaches for forecast explainability and interpretability. The role also involves supporting the Labs experimentation platform, which designs and executes inference and experimentation systems that measure the impact of initiatives across SCOT. The Data Scientist needs to be familiar with deriving causal inferences using observational and experimental data and able to model variations related to demand prediction, out of stock, seasonality, and different lead times and spans. This role requires an individual with excellent analytical abilities as well as business acumen. The successful candidate will be a self-starter comfortable with ambiguity, with attention to detail, vocally self-critical, and an ability to work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had. The Demand Forecasting Team is looking for an analytical and technically skilled Data Scientist to join our team. This position will be responsible for developing and supporting best-in-class data science methodologies and building models to address ambiguous forecasting questions. The Data Scientist needs to be familiar with deriving causal inferences using observational data and able to model variations related with demand prediction, out of stock, seasonality, and different lead times and spans. Upon completion of statistical analysis, the Data Scientist needs to communicate measurement results to stakeholders by translating technical framework to business-oriented insights. This role requires an individual with excellent analytical abilities as well as business acumen. The successful candidate will be a self-starter comfortable with ambiguity, with attention to detail, vocally self-critical, an ability to work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had. Key job responsibilities - Design and analyze experiments (A/B tests) to measure the impact of forecast model changes and SCOT initiatives, drawing causal inferences from both experimental and observational data - Develop bias correction models to improve forecast accuracy across Amazon's demand forecasting systems, including National, Regional, Grocery, SSD, Inbound, and CIV forecasts - Contribute to GenAI/LLM-based research for forecast explainability and interpretability, helping stakeholders understand what drives forecast signals - Support and enhance the Labs experimentation platform by building scalable inference and measurement solutions that quantify the impact of forecasting improvements - Work horizontally across the forecasting product portfolio and collaborate with product managers, applied scientists, and engineering teams to embed analytics and ML solutions where they create the most value - Use large datasets to build models addressing ambiguous forecasting questions, including demand prediction, out of stock, seasonality, and varying lead times and spans - Interpret data, write reports, and communicate measurement results to stakeholders by translating technical frameworks into business-oriented insights and actionable recommendations - Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. The candidate will need to be able to extract insights from data and clearly communicate appropriate triggers and actions A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
  • (Updated 7 days ago)
    About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through 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. Key job responsibilities As a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling and Generative AI solutions to optimize all aspects of Sponsored Products and Brands business About the team The Ad Response Prediction team within Sponsored Products and Brands (SPB) drives personalized shopping experiences for SPB Ads across placements, pages, and devices worldwide. We achieve this through ML and GenAI solutions that include customized shopper response prediction and session-level understanding to optimize every stage of the ad-serving process, from sourcing and bidding to widget discovery and auctions. Our responsibilities include advancing response prediction through model and feature innovations and extending prediction beyond the auction stage to areas such as targeting, sourcing, and bidding.
  • US, WA, Seattle
    Job ID: 10438206
    (Updated 7 days ago)
    Are you interested in shaping the future of Advertising and B2B Sales? We are a growing team with an exciting AI-first charter and need your passion, innovative thinking, and creativity to help take our products to new heights. 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 are strategically important to our businesses driving long term growth. We break fresh ground in product and technical innovations every day! Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top Applied Science talent to help us build new, science-backed services that drive success for our customers. Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency. As an Applied Scientist on the team, you will bring deep expertise in modeling dynamic systems using statistical methods and deep learning, and in optimizing those systems using reinforcement learning and operations research. You have the scientific and technical skills to build and refine models that can be implemented in production, and you leverage natural language processing and generative AI to enhance their explainability. You will chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. You will be part of a team of fellow scientists and engineers taking iterative approaches to tackle big, long-term problems. You are fluently able to leverage the latest generative AI systems and services to accelerate and improve your work while maintaining high quality in your outputs. Key job responsibilities Scientific Modeling - Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business - Lead the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects - Run regular A/B experiments, gather data, and perform statistical analysis - Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving - Publish scientific findings in reports and papers that can be shared internally and externally Product Development Support - Partner with software engineering and product management teams to support product and service development, define success metrics and measurement approaches, and help drive adoption of innovative new features for our services. - Lead requirements gathering sessions with product teams and business stakeholders - Maintain scientific documentation and knowledge for product initiatives Collaboration & Communication - Work closely with software engineers to deliver end-to-end solutions into production - Translate complex scientific findings into actionable business recommendations for stakeholders and senior management - Provide clear, compelling reports and presentations on a regular basis with respect to your models and services - Communicate with internal teams to showcase results and identify best practices. About the team Sales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows.
  • (Updated 7 days ago)
    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 Personalization and Discovery team owns science solution to power personalized experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering and product teams to launch our solutions in production.
  • US, NY, New York
    Job ID: 10435099
    (Updated 11 days ago)
    Are you passionate about solving big problems from ground-up? Do you enjoy building new state-of-the-art products at internet scale? Come lead the innovation in this startup team, vertical ad products. This is a green field problem without a known answer or a pattern to follow. We have ambitious vision to simplify full funnel advertising solutions, at scale, with specialized agentic AI-powered models and diversify the demand to strategic verticals including finserv, autos, locals.. etc. We are seeking an experienced Applied Scientist to drive innovation in our Ads Foundational Model. In this individual contributor role, you will apply advanced machine learning techniques to improve advertiser performance and customer experience. Key job responsibilities As an Applied Scientist on this team, you will: 1. Develop and drive the science strategy for Ads Foundational Model (Ads-FM), aligning it with the program's objectives and overall business goals. 2. Identify high-impact opportunities within Ads-FM program and lead the ideation, planning, and execution of science initiatives to address them. 3. Build and deploy machine learning models using computer vision, natural language processing, and deep learning to evaluate and enhance ad effectiveness. 4. Develop algorithms that extract meaningful signals from image, video, and audio content to predict and improve customer engagement 5. Leverage Amazon's extensive data repository to create predictive models that generate actionable recommendations for more compelling ad creative 6. Collaborate with business leaders and cross-functional teams to implement ML-powered solutions 7. Contribute to the ML roadmap for the Ads-FM program through innovation and research.
  • US, WA, Seattle
    Job ID: 10434897
    (Updated 11 days ago)
    This role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees. Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scaleable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Principal Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes. In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.
  • US, NY, New York
    Job ID: 10440472
    (Updated 5 days ago)
    As part of the AWS Applied AI 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. The Applied Scientist II will contribute to the development of AI systems. The role requires extending existing scientific techniques and inventing new ones to address specific customer needs at a project level. You should be comfortable working semi-autonomously on difficult problems with visible risks or roadblocks. You'll work closely with technical leaders within the team. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Design and implement solutions that extend or adapt scientific approaches for customer needs at the project level * Deliver components into production that meet high quality standards (efficient, reproducible, testable code) * Produce research reports demonstrating correctness, scholarship, and scientific rigor * Work with product and science teams to deliver impactful AI features * Contribute to operational excellence in the team's deliverables About the team ABOUT AWS: Diverse Experiences Amazon 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. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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.

Science at Amazon around the world

Amazon scientists are working on large-scale technical challenges in a variety of research areas across the globe. Use the pins below to learn more about the customer-obsessed science being conducted at some of our research locations.
world map in greyscale
Australia
South Australia, AU
City
New South Wales, AU
City
Canada
British Columbia
City
Ontario
City
China
Shanghai, CN
City
Beijing, CN
City
Germany
City City City
India
Hyderabad, IN
City
Bengaluru, IN
City
Israel
Luxembourg
City
United Kingdom
United States
California (Southern)
California (Northern)
San Francisco
Massachusetts
New York
Pennsylvania
City
Texas
City
Virginia
Washington
download (18).jpeg

Academia

Amazon collaborates with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly across all sectors of society.