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.
551 results found
  • (Updated 25 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 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.
  • GB, London
    Job ID: 3194246
    (Updated 27 days ago)
    We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to help build industry-leading language technology powering Rufus, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey. This innovative role focuses on developing and optimizing large language model (LLM)-powered conversational experiences. The core emphasis is to get the best performance out of state-of-the-art LLMs via careful and methodical instruction design, contextual grounding, informed choices of MCP tools and agent/multi-agent systems, evaluation frameworks, and experimentation to systematically improve LLM quality, robustness, and customer impact. The work combines scientific rigor with product intuition to systematically raise the bar for conversational AI performance at Amazon scale. Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more. We do this by leveraging advanced analytics, Natural Language Processing (NLP), Machine Learning (ML), A/B testing, causal inference, and data-driven insights to continuously improve our systems. Key job responsibilities As a Data Scientist on our team, you will develop and maintain LLM instructions iterations and evaluation frameworks, including automated eval pipelines, LLM-as-a-judge methodologies, rubric design, and dataset curation to measure nuanced aspects of response quality. You will partner with the wider org to experiment with techniques such as retrieval augmentation, context enrichment, prompt decomposition, and model fine-tuning or post-training strategies, if and when applicable. You will leverage petabytes of data and identify opportunities to leverage machine learning models aimed at making conversational systems more performant. A day in the life You will: Perform hands-on analysis of large-scale multimodal interaction datasets to develop insights into how customers engage with conversational AI systems and how to improve response quality and customer experience. Use statistical methods, experimentation, and data-driven analysis to develop scalable approaches for measuring, evaluating, and optimizing large language model (LLM)-based shopping assistant systems, leveraging structured and unstructured contextual signals. Design and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insights. Develop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impact. Conduct deep-dive analyses to identify opportunities for improving conversational relevance, grounding, customer satisfaction, and downstream business impact. Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment. Establish automated processes for large-scale data analysis, ETL pipelines, metric generation, and experimentation frameworks. Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations. About the team The Rufus Features Science team, based in London, works alongside ~150 engineers, designers and product managers, shaping the future of AI-driven shopping experiences at Amazon. The team works on every aspect of the Rufus AI, from making Rufus agentic, enabling customers to set price alerts or empower Rufus to act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance. We utilize and advance state-of-art techniques in the fields of Natural Language Processing, gen AI, Information Retrieval, Machine/Deep Learning, and Data Mining. We validate our work by actively participating in the internal and external scientific communities.
  • AT, Graz
    Job ID: 10372543
    (Updated 6 days ago)
    We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve large-scale real world challenges, and provide visible benefit to end-users, this is your opportunity. Come work on the Amazon Prime Air Team! We're looking for an applied scientist who combines superb technical, research and analytical capabilities with a demonstrated ability to get the right things done quickly and effectively. We’re looking for someone who innovates and loves solving hard problems. You will work hard, have fun, and of course, make history! The monthly gross salary according to the CBA is at least EUR 4.006. There is a willingness to make an overpayment, depending on qualification and professional experience. Export Control License: This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf. Key job responsibilities Develop computer vision algorithms for autonomous drones. Monitor systems in operation. Manage ML ops pipelines. Deep dive into data. Build prototypes. Port algorithms to real-time systems. About the team The Perception team of Prime Air develops Computer Vision algorithms that allow our drones to sense and avoid obstacles, allowing to fully autonomously deliver packages to customers in 30 minutes or less.
  • US, WA, Seattle
    Job ID: 10371776
    (Updated 11 days ago)
    Economists at Amazon are expected to work directly with our senior management and scientists from other fields on key business problems faced across Amazon. We are looking for economists who are able to work with business partners to hone complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with engineers and scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work in a team setting with individuals from diverse disciplines and backgrounds. Ideal candidates will own the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Collaborate with economists, data scientists, financial managers, and business leaders to define product requirements, provide science support, and communicate feedback. Implement economics methods to solve specific business problems utilizing code (Python, R, Scala, etc.). Improve existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. Presenting data in a format that is immediately useful to answer the critical business questions. About the team The Perfect Order Experience (POE) Econ team serves as POE teams' trusted economics partner, enhancing business strategy and operational effectiveness across POE and Selling Partner Services (SPS) through economic analysis and insights. We focus on advancing POE's goals towards the perfect order experience vision while delivering value to broader teams where strategic alignment exists. Through rigorous analytical frameworks, we help leaders navigate complex business and operational challenges. We embrace AI to revolutionize how we work and amplify our strategic contributions.
  • (Updated 5 days ago)
    Amazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. Are you an expert in Natural Language Processing (NLP) and Large Language Models (LLM)? Are you interested in building Generative AI solutions on complex business problems that have significant global benefit. The Brand Protection team designs and builds high performance AI systems using machine learning that identify and prevent abuse and counterfeit on behalf of brand owners worldwide. We are looking for a highly talented scientist to help build of our vision for Brand Protection. As a senior applied scientist on the team, you will use NLP and LLM techniques to understand and extract key information from product detail page, built automated AI solutions that thinks like human to assist decision making and eventually make autonomous decisions. You will work backwards from data insights and customer feedback to build the right machine learning solutions, and resourceful in finding innovative solutions to unsolved problems. You will work closely will product team and engineering partners to launch the solution into production and owning the end-to-end solution. An ideal candidate should have extensive experience driving Machine Learning initiatives, specially in NLP and LLM applications, from conception to launch in a rapidly evolving environment. Amazon’s growth requires leaders who move fast, have an entrepreneurial spirit to create new solutions, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex problems. Major responsibilities: - Understand business challenges by analyzing data and customer feedback - Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement - Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems. - Use NLP, LLM and machine learning techniques to create scalable solutions for business problems - Create business and analytics reports and present to the senior management teams - Research and implement novel AI solutions and publish research papers About the team Here at Selling Partner Services, we embrace our differences. We are committed to furthering our culture of inclusion. We have 14 employee-led affinity groups, reaching 10,000+ employees in chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our DEI Ambassador Program. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
  • US, WA, Seattle
    Job ID: 10375257
    (Updated 5 days ago)
    Amazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. Are you an expert in Natural Language Processing (NLP), computer vision Large Language Models (LLM) and multi-modality? Are you interested in building Generative AI solutions on complex business problems that have significant global benefit. The Brand Protection Science team designs and builds high performance AI systems using machine learning and deep learning that identify and prevent infringement and counterfeit on behalf of brand owners worldwide. We are looking for a highly talented scientist to help build of our AI vision for Brand Protection. As a applied scientist on the team, you will use STOA AI and ML techniques to understand and extract key information from product detail page, built automated AI solutions that thinks like human to make autonomous decisions. You will work backwards from data insights and customer feedback to build the right machine learning solutions, and resourceful in finding innovative solutions to unsolved problems. You will work closely will product team and engineering partners to launch the solution into production and own the end-to-end solution. An ideal candidate should be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied scientist, you will own the design and development of end-to-end AI solutions, from conception to launch in a rapidly evolving environment. You’ll have the opportunity to create science roadmaps, and drive production level projects that will support Amazon Science. extensive experience driving Machine Learning initiatives, specially in NLP and LLM applications, from conception to launch in a rapidly evolving environment. You will work closely with other scientists and enigneers to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Major responsibilities: - Understand business challenges by analyzing data and customer feedback - Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement - Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems. - Use deep learning and machine learning techniques to create scalable solutions for business problems - Create business and analytics reports and present to the senior management teams - Research and implement novel AI solutions and publish research papers Key job responsibilities Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work. For more information on the Amazon Science community please visit https://www.amazon.science.
  • (Updated 18 days ago)
    Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. 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! The ADSP Forecasting team's vision is to build the best in class forecasting products offered by any DSP to allow advertisers to forecast campaign outcomes across the full market funnel. Our goal is to empower advertisers using Amazon demand side platform to make informed decisions by providing predictions and recommendations of supply and ad-performance. Our forecasting models and analytical solutions will also help internal teams (sales, PSC, supply desk etc) to gain insights into forecasted supply, demand and ad performance to make the best business decisions. The team comprises scientists and engineers who own end-to-end projects - data collection, analysis, ideation, and prototyping, to development, metrics and monitoring. The models and services are integrated directly with Amazon's Ads eco system and the forecasts are used to drive key business decisions at the VP/SVP level. We are a team of Applied Scientists and Engineers, who are passionate about solving technical problems in the Ad Forecasting space with models using Machine Learning, Bayesian Statistics, etc. You will join a group of highly talented PhDs with diverse background to design, prototype, and implement models to deliver impact directly to customers. You will have the opportunity to present your work in science communities and to leadership As a Applied Scientist on this team, you will: - Be the technical leader in Machine Learning; lead efforts within this team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE
  • (Updated 13 days ago)
    Amazon's advertising business has grown exponentially over the past years, helping connect sellers and vendors to shoppers who may be interested in their products. Our ad products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products that leverage state of the art AI technologies. The Sponsored Products and Brands team is seeking a Principal Applied Scientist to lead the development and implementation of generative AI solutions for ad allocation and ranking on Amazon search pages. This role will be instrumental in revolutionizing how we match ads with customer intent and shopping behavior. Key job responsibilities * Design and develop novel generative AI architectures for real-time ad allocation, focusing on both efficiency and effectiveness at massive scale * Lead research initiatives in applying large language models and multimodal AI to understand deep semantic relationships between ads, queries, and user behavior * Create innovative approaches to leverage GenAI for dynamic ad placement optimization while maintaining strict latency requirements * Collaborate with cross-functional teams to integrate GenAI solutions into existing advertising systems * Author research papers and technical documentation, contributing to the broader scientific community
  • US, WA, Bellevue
    Job ID: 3204828
    (Updated 17 days ago)
    We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference skillsets to solve real world problems. The intern will work in the area of Returns & ReCommerce and develop methods to validate and contextualize causal inference estimates. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The Returns & ReCommerce Economics Intelligence (RREI) team brings together economists, data scientists, data analysts, and business intelligence engineers to deliver innovative research and products that discover and surface returns-influencing behavior, trends and their root causes. We leverage a range of scientific approaches such as causal modeling, structural and choice modeling, time series, ML, and optimization models to yield tangible insights targeted at reducing the cost of returns and concessions without slowing down the Amazon flywheel.
  • (Updated 13 days ago)
    The Fulfillment by Amazon (FBA) Science team is looking for a passionate, curious, and creative Senior Research Scientist with deep expertise in statistical modeling, machine learning, and large language models (LLMs), and a proven record of solving complex forecasting problems at scale. Our team sits at the intersection of supply chain science, seller behavior modeling, and policy analytics — building the forecasting backbone that powers FBA's shipment creation, inbound arrival planning, and inventory management. We develop science solutions that predict seller shipment creation patterns, model inbound arrival timing and quantity, and forecast inventory levels across Amazon's fulfillment network. A key challenge we tackle is understanding how seller behavior changes — driven by market dynamics, FBA policy updates, and incentive structures — and how these behavioral shifts propagate into forecasting signals. We aim to build forecasting systems that are not only accurate but also explainable and actionable for both internal stakeholders and sellers. To do so, we build and innovate science solutions at the intersection of statistical learning, machine learning, econometrics, operations research, and generative AI. As a Senior Research Scientist, you will propose and deploy solutions drawing from a range of scientific areas including time-series forecasting, causal inference, Bayesian methods, LLMs, and deep learning. This role has high visibility to senior Amazon business leaders and involves close collaboration with scientists, engineers, and product teams to integrate scientific work into production systems. Key job responsibilities - As a senior member of the FBA Science forecasting team, play an integral role in building and advancing Amazon's FBA shipment creation, inbound arrival, and inventory forecasting systems. - Research and develop statistical models, ML models, and LLM-based solutions to forecast seller shipment creation behavior, inbound arrival patterns, and downstream inventory levels across the FBA network. - Model and quantify the impact of seller behavior changes and FBA policy updates (e.g., capacity limits, fee structures, inbound placement policies) on forecasting accuracy, and develop robust forecasting approaches that adapt to these dynamics. - Build explainability frameworks for forecasting models — enabling science teams, product managers, and business stakeholders to understand model drivers, diagnose forecast errors, and trust model outputs. - Define a long-term science vision and roadmap for the forecasting team, driven fundamentally by customer and seller needs, translating those directions into specific plans for research and applied scientists, as well as engineering and product teams. - Drive and execute forecasting science projects end-to-end: from ideation, analysis, and prototyping through to development, deployment, metrics definition, and monitoring. - Review and audit modeling processes and results for other scientists, both junior and senior. - Advocate the right science solutions to business stakeholders, engineering teams, and executive-level decision makers. A day in the life In this role, you will be a technical leader in forecasting science with significant scope, impact, and high visibility. Your solutions will directly influence billions of dollars in inventory decisions, inbound logistics planning, and seller experience across Amazon's global fulfillment network. As a senior scientist on the team, you will be involved in every aspect of the process — from idea generation, business analysis, and scientific research, through to development and deployment of advanced forecasting models — giving you a real sense of ownership. From day one, you will work with experienced scientists, engineers, and product designers who are passionate about what they do. You are expected to make decisions about modeling methodology, technology choices, and explainability approaches. You will strive for simplicity and demonstrate judgment backed by mathematical rigor. You will also collaborate with the broader decision and research science community at Amazon to broaden the horizon of your work, and mentor engineers and scientists. We are seeking someone who wants to lead projects requiring innovative thinking and deep technical problem-solving skills to create production-ready forecasting solutions. The candidate will need to be entrepreneurial, wear many hats, and work in a fast-paced, high-energy, highly collaborative environment. About the team Fulfillment by Amazon (FBA) is a service that allows sellers to outsource order fulfillment to Amazon, enabling them to leverage Amazon's world-class fulfillment infrastructure to deliver on the Prime promise. FBA ships more than half of all products offered on Amazon, and our science team is at the heart of making that possible. The FBA Science forecasting team focuses on predicting seller shipment creation, inbound arrival, and inventory dynamics — providing the signals that drive capacity planning, inbound logistics, and inventory positioning across the network. We work full-stack, from foundational forecasting models to seller-facing explainability tools. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.

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.