Careers

Device Economics is looking for a senior economist experienced in causal inference, machine learning, empirical industrial organization, and scaled systems to work on business problems to advance critical resource allocation and pricing decisions in the Amazon Devices org. Senior roles lead vision setting, methods innovation, and act as thought leaders to Devices finance and business executives. Output will be included in scaled systems to automate existing processes and to maximize business and customer objectives. Amazon Devices designs and builds Amazon first-party consumer electronics products to delight and engage customers. Amazon Devices represents a highly complex space with 100+ products across several product categories (e-readers [Kindle], tablets [Fire Tablets], smart speakers and audio assistants [Echo], wifi routers [eero], and video doorbells and cameras [Ring and Blink]), for sale both online and in offline retailers in several regions. The space becomes more complex with dynamic product offering with new product launches and new marketplace launches. The Device Economics team leads in analyzing these complex marketplace dynamics to enable science-driven decision making in the Devices org. Device Economics achieves this through scientific applications that provide deep understanding of customer preferences. Our team’s outputs inform product development decisions, investments in future product categories, and product pricing and promotion. We have achieved substantial impact on the Devices business, and will achieve more. Device Economics seeks an experienced economist adept in measuring customer preferences and behaviors with proven capacity to innovate, scale measurement, drive rigor, and mentor talent. Key job responsibilities The candidate will work with Amazon Devices science leadership to refine science roadmaps, models, and priorities for innovation and simplification, and advance adoption of insights to influence important resource allocation and prioritization decisions. Effective communication skills (verbal and written) are required to ensure success of this collaboration. The candidate must be passionate about advancing science for business and customer impact.

Economists on the Seller Fee Science team design scalable strategies and technology for the fees Amazon charges to third-party sellers, world wide. Our challenge is to facilitate continued improvement in both customer experience (selection, prices, delivery speed) and selling partner growth and innovation, while optimizing for Amazon's long-term profits. Key job responsibilities Design and develop models to assess the causal impact of fees, and fee-related policy on third party sellers’ behavior and business performance. Lead enhancements into existing fee calculation models to maximize the long term health of the Amazon third-party marketplace. Own the scientific vision and direction related to fees worldwide. Collaborate with product managers, data scientists, and software developers to incorporate models into production processes and influence senior leaders. Act as an ambassador of our team in the broader scientific community.

Are you a MS or PhD student interested in a 2024 Applied Science Internship in the fields of Speech, Robotics, Computer Vision, or Machine Learning/Deep Learning? Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful products that improve the lives of people in a meaningful way? If this describes you, come join our research teams at Amazon. Key job responsibilities As an Applied Scientist, you will have access to large datasets with billions of images and video to build large-scale machine learning systems. Additionally, you will analyze and model terabytes of text, images, and other types of data to solve real-world problems and translate business and functional requirements into quick prototypes or proofs of concept. We are looking for smart scientists capable of using a variety of domain expertise combined with machine learning and statistical techniques to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

Have you ever wanted to solve a mystery or be part of solving a case? Are you fascinated by detective stories or crime shows on TV? Do you love to catch bad actors, build ML models and solve complex problems. If so, working on the WWOS Tech team as a Sr Applied Scientist is the place for you! We detect theft, fraud and organized crime happening across our global supply chain and operations for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the cost savings of Amazon's inventory losses. The primary role of a Sr Applied Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on all the fraud investigations happening across Amazon operations. Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in ( Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of building fraud detections, detecting organized crime and the ability to use data and research to make changes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment. Key job responsibilities - Own KPIs that measure theft/fraud management performance and efficiencies. - Detect and automate theft, fraud MOs - Detect organized crime rings and bad actor clusters - Perform end to end evaluation of operational defects, system gaps, and scaling challenges (both system and operational). - Contribute to the overall fraud management and product development strategies. - Present key learnings and vision to stakeholders and leadership. - Integrate ML detection models via software applications About the team We believe that building a culture that is welcoming and inclusive is integral to people doing their best work and is essential to what we can achieve as a company. We actively recruit people from diverse backgrounds to build a supportive and inclusive workplace. Our team puts a high value on work-live balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.

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 Recommendation and Personalization 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. A day in the life We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. 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. Please note this position is a Fixed Term Contract role until September 2027. Key job responsibilities - Work backwards from customer problems to research and develop novel machine learning solutions for music and podcast recommendations. Through A/B testing and online experiments done in tandem with engineering teams, you'll implement and validate your ideas and solutions. - Advocate solutions and communicate results, insights and recommendations to stakeholders and partners. - Produce innovative research on recommender systems that shapes the field and meets the high standards of peer-reviewed publications. You'll cement your team's reputation as thought leaders pioneering new recommenders. - Stay current with advancements in the field, adapting latest in literature to build efficient and scalable models A day in the life You will lead innovation in AI/ML to shape Amazon Music experiences for millions. This role will involve developing state of the art models leveraging and advancing the latest developments in machine learning and AI, collaborating with with talented engineers and scientists to guide research and building scalable models across our audio portfolio - music, podcasts, live streaming, and more. You will drive experiments and rapid prototyping, leveraging Amazon's data at scale. This is an opportunity to innovate daily alongside world-class teams to delight customers worldwide through personalization. About the team Our team works with modern AI technologies to transform how customers discover and engage with music and podcasts. We focus on the canonical customer understanding layer for personalization across Amazon audio experiences. We are the "who" experts - we know who the customer is, what they want, where they are in their journey, and how their preferences evolve over time. Amazon Music is available in countries around the world, and our solutions support our mission of delivering music and podcasts to customers in new, exciting ways that enhance their day-to-day lives.

职位：Applied scientist 应用科学家实习生 毕业时间：2026年10月 - 2027年7月之间毕业的应届毕业生 · 入职日期：2026年6月及之前 · 实习时间：保证一周实习4-5天全职实习，至少持续3个月 · 工作地点：深圳福田区 投递须知： 1 填写简历申请时，请把必填和非必填项都填写完整。提交简历之后就无法修改了哦！ 2 学校的英文全称请准确填写。中英文对应表请查这里（无法浏览请登录后浏览）https://docs.qq.com/sheet/DVmdaa1BCV0RBbnlR?tab=BB08J2 关于职位 Amazon Device &Services Asia团队正在寻找一位充满好奇心、善于沟通的应用科学家实习生，成为连接前沿AI研究与现实世界认知的桥梁。这是一个独特的角色——既需要动手参与机器学习项目，又要接受将复杂AI概念转化为通俗易懂内容的创意挑战。D&S Asia是亚马逊设备与服务业务在亚洲的支柱组织，自2009年支持Kindle制造起步，现已发展为横跨软硬件、AI（Alexa）及智能家居（Ring/Blink）的综合性团队，持续驱动区域业务创新与人才发展。 你将做什么 • 解密AI： 将复杂的技术发现转化为直观的解释、博客文章、教程或互动演示，让非技术背景的业务方和更广泛的社区都能理解 • 技术叙事： 与工程团队协作，以清晰、引人入胜的方式记录AI的能力与局限性 • 知识共享： 协助开发内部工作坊或"AI入门"课程，提升跨职能团队（产品、设计、商务）的AI素养 • 保持前沿： 持续学习并整合最新突破（如大语言模型、扩散模型、智能体），为团队输出简明易懂的趋势简报 • 研究与应用： 参与端到端的应用研究项目，从文献综述到原型开发，涵盖自然语言处理、计算机视觉或多模态AI领域

Passionate about books? The Amazon Books team is looking for a talented Applied Scientist II to help invent, design, and deliver science solutions to make it easier for millions of customers to find the next book they will love. In this role, you will - Be a part of a growing team of scientists, economists, engineers, analysts, and business partners. - Use Amazon’s large-scale computing and data resources to generate deep understandings of our customers and products. - Build highly accurate models (and/or agentic systems) to enhance the book reading & discovery experiences. - Design, implement, and deliver novel solutions to some of Amazon’s oldest problems. Key job responsibilities - Inspect science initiatives across Amazon to identify opportunities for application and scaling within book reading and discovery experiences. - Participate in team design, scoping, and prioritization discussions while mapping business goals to scientific problems and aligning business metrics with technical metrics. - Spearhead the design and implementation of new features through thorough research and collaboration with cross-functional teams. - Initiate the design, development, execution, and implementation of project components with input and guidance from team members. - Work with Software Development Engineers (SDEs) to deliver production-ready solutions that benefit customers and business operations. - Invent, refine, and develop solutions to ensure they meet customer needs and team objectives. - Demonstrate ability to use reasonable assumptions, data analysis, and customer requirements to solve complex problems. - Write secure, stable, testable, and maintainable code with minimal defects while taking full responsibility for your components. - Possess strong understanding of data structures, algorithms, model evaluation techniques, performance optimization, and trade-off analysis. - Follow engineering and scientific method best practices, including design reviews, model validation, and comprehensive testing. - Maintain current knowledge of research trends in your field and apply rigorous scrutiny to results and methodologies. A day in the life In this role, you will address complex Books customer challenges by developing innovative solutions that leverage the advancements in science. Working alongside a talented team of scientists, you will conduct research and execute experiments designed to enhance the Books reading and shopping experience. Your responsibilities will encompass close collaboration with cross-functional partner teams, including engineering, product management, and fellow scientists, to ensure optimal data quality, robust model development, and successful productionization of scientific solutions. Additionally, you will provide mentorship to other scientists, conduct reviews of their work, and contribute to the development of team roadmaps. About the team The team consists of a collaborative group of scientists, product leaders, and dedicated engineering teams. We work with multiple partner teams to leverage our systems to drive a diverse array of customer experiences, owned both by ourselves and others, that enable shoppers to easily find their perfect next read and enable delightful reading experiences that would make Kindle the best place to read.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the International Emerging Stores organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team Central Machine Learning team works closely with the IES business and engineering teams in building ML solutions that create an impact for Emerging Marketplaces. This is a great opportunity to leverage your machine learning and data mining skills to create a direct impact on millions of consumers and end users.

The Alexa 1P Devices and Marketing organization is looking for an experienced Research Scientist who is energized by the opportunity to help build the future of AI through Alexa+. You will be joining the Alexa Customer Science (ACS) team, whose mission is to surface timely, scientifically-grounded customer insights that help ground Alexa product and marketing decisions. The ideal candidate will have a strong background in quantitative research methods, excellent analytical skills, comfort with ambiguous problem spaces and large-n quantitative and qualitative data sets, and a passion for understanding individual-level attitudes and behavior. Experience with sampling design and survey data weighting is desirable. General AI fluency is a requirement for this role, and experience with AI research workflow integrations is highly desirable. As a Research Scientist with ACS, you will be responsible for designing, conducting, and analyzing research that helps product and marketing teams in Alexa Devices better understand our customers' preferences, experiences, and behaviors. You will own research projects end-to-end, including measurement strategy, data collection, analysis, and reporting to peers and business leaders. You will work closely with cross-functional teams, including product managers, marketing managers, UX researchers and data scientists, designers, and engineers. You should have deep expertise in the design, creation, management, and business use of surveys, randomized experiments (including conjoints, maxdiff, and other choice tasks), and the latest research tools, including those leveraging AI applications. Competency in mixed-methods or qualitative approaches is also desirable. Key job responsibilities - Work closely with product and marketing teams, as well as fellow researchers, to identify research topics and build a research roadmap; communicate and refresh on a regular basis to ensure relevancy. - Create a deep understanding of customers through descriptive, inferential, and experimental approaches (existing or invented) that you identify as being most effective for answering a given business question. - Design, implement, and analyze data from surveys, randomized experiments, and other large-n data sets. - Work with data engineering and business intelligence teams to triangulate survey data with customer engagement and segmentation data. - Create repeatable and scalable mechanisms to measure key customer metrics that drive product iteration. - Synthesize a wide range of primary and secondary data types leading to focused, insightful, and actionable insights that persuade and inspire partners and leaders to take concerted, informed actions. - Work closely with research peers to promote best practices, build resources, and train team members to enable them to execute their own research projects. A day in the life Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. Amazon has ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences. 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. About the team The Alexa Customer Science (ACS) team is a team of Research Scientists, UX Researchers, and Market Researchers that surfaces timely, scientifically-grounded insights about customers to guide marketing and product leaders.