Careers

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.

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.

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

The Kindle team is seeking innovative Applied Scientists for improving the reading experience. Our team is dedicated to enhancing the book reading experience using advancements in Science to improve the book reading experience for Kindle customers. Key job responsibilities - Inspect science initiatives across Amazon to identify how these can be applied and scaled to book reading experience. - Participate in team design, scoping and prioritization discussions. You must be able to map a business goal to a scientific problem, and map business metrics to technical metrics. - Spearhead the design and implementation of new features and algorithms based on thorough research and collaboration with cross-functional teams. - You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning - You are able to use reasonable assumptions, data, and customer requirements to solve problems. - You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. - You work with SDEs to deliver solutions into production to benefit customers or an area of the business. - You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. - You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. - You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly - You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. - You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. - You keep current with research trends in your area of expertise and scrutinize your results. A day in the life You will solve customer problems through innovative solutions that leverage the advancements in science. You will work with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team.

Amazon Industrial Robotics Group is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics Group, we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of dexterous manipulation system that: - Enables unprecedented generalization across diverse tasks - Enables contact-rich manipulation in different environments - Seamlessly integrates low-level skills and high-level behaviors - Leverage mechanical intelligence, multi-modal sensor feedback and advanced control techniques. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. A day in the life - Lead design and implementation of methods for Visual SLAM, navigation and spatial reasoning - Leverage simulation and real-world data collection to create large datasets for model development - Develop a hierarchical system that combines low-level control with high-level planning - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for dexterous manipulation

Amazon Prime is looking for an ambitious Economist Intern to help create econometric insights for world-wide Prime. Prime is Amazon's premiere membership program, with over 200M members world-wide. This role is at the center of many major company decisions that impact Amazon's customers. These decisions span a variety of industries, each reflecting the diversity of Prime benefits. These range from fast-free e-commerce shipping, digital content (e.g., exclusive streaming video, music, gaming, photos), reading, healthcare, and grocery offerings. Prime Science creates insights that power these decisions. As an economist intern in this role, you will create statistical tools that embed causal interpretations. You will utilize massive data, state-of-the-art scientific computing, econometrics (causal, counterfactual/structural, experimentation), and machine-learning, to do so. Some of the science you create will be publishable in internal or external scientific journals and conferences. You will work closely with a team of economists, applied scientists, data professionals (business analysts, business intelligence engineers), product managers, and software/data engineers. You will create insights from descriptive statistics, as well as from novel statistical and econometric models. You will create internal-to-Amazon-facing automated scientific data products to power company decisions. You will write strategic documents explaining how senior company leaders should utilize these insights to create sustainable value for customers. These leaders will often include the senior-most leaders at Amazon. The team is unique in its exposure to company-wide strategies as well as senior leadership. It operates at the research frontier of utilizing data, econometrics, artificial intelligence, and machine-learning to form business strategies. A successful candidate will have demonstrated a capacity for building, estimating, and defending statistical models (e.g., causal, counterfactual, machine-learning) using software such as R, Python, or STATA. They will have a willingness to learn and apply a broad set of statistical and computational techniques to supplement deep training in one area of econometrics. For example, many applications on the team motivate the use of structural econometrics and machine-learning. They rely on building scalable production software, which involves a broad set of world-class software-building skills often learned on-the-job. As a consequence, already-obtained knowledge of SQL, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or PySpark would be a plus. Additionally, this candidate will show a track-record of delivering projects well and on-time, preferably in collaboration with other team members (e.g. co-authors). Candidates must have very strong writing and emotional intelligence skills (for collaborative teamwork, often with colleagues in different functional roles), a growth mindset, and a capacity for dealing with a high-level of ambiguity. Endowed with these traits and on-the-job-growth, the role will provide the opportunity to have a large strategic, world-wide impact on the customer experiences of Prime members.

Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that improve Amazon's customers experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions? If yes, we invite you to join the Amazon Customer Fulfillment & Prime analytics team. We're seeking an exceptional scientist who can revolutionize how we delight our customers. As a key member of our team, you'll develop and deploy machine learning systems that analyze millions of customer interactions daily, ensuring state of art experience for customers across 10 countries. Your work will directly impact the shopping experience for hundreds of millions of customers worldwide. Key job responsibilities • Use machine learning and statistical techniques to create scalable abuse detection solutions that identify fraudulent customer behavior, rings of accounts, identity change, holistic customer risk and marketplace manipulation schemes • Innovate with the latest GenAI technology to build highly automated solutions for efficient customer promotions • Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to delight Amazon customers • Collaborate with cross-functional teams to develop comprehensive ML/statistical models that can scale to millions of customers and 10+ countries About the team You'll be working closely with business partners, science and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.

We are looking for an Economist to work on exciting and challenging business problems related to Amazon Retail’s worldwide product assortment. You will build innovative solutions based on econometrics, machine learning, and experimentation. You will be part of a interdisciplinary team of economists, product managers, engineers, and scientists, and your work will influence finance and business decisions affecting Amazon’s vast product assortment globally. If you have an entrepreneurial spirit, you know how to deliver results fast, and you have a deeply quantitative, highly innovative approach to solving problems, and long for the opportunity to build pioneering solutions to challenging problems, we want to talk to you. Key job responsibilities * Work on a challenging problem that has the potential to significantly impact Amazon’s business position * Develop econometric models and experiments to measure the customer and financial impact of Amazon’s product assortment * Collaborate with other scientists at Amazon to deliver measurable progress and change * Influence business leaders based on empirical findings

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. Key job responsibilities - Build, adapt and evaluate ML models for life sciences applications - Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers

The Mission Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. What You'll Build You'll pioneer breakthrough solutions in Responsible AI at Amazon's scale. Imagine training models that set new safety standards, designing automated testing systems that hunt for vulnerabilities before they surface, and certifying the systems that power millions of daily conversations. You'll create intelligent evaluation systems that judge responses with human-level insight, build models that truly understand what makes interactions safe and delightful, and craft feedback mechanisms that help Alexa+ grasp the nuances of complex customer conversations. Here's where it gets even more exciting: you'll build AI agents that act as your team's safety net—automatically detecting and fixing production issues in real-time, often before anyone notices there was a problem. Your innovations won't just improve Alexa+; they'll fundamentally shape how it learns, evolves, and earns customer trust. As Alexa+ continues to delight customers, your work ensures it becomes more trustworthy, safer, and deeply aligned with customer needs and expectations. Your work directly protects customer trust at Amazon's scale. Every innovation you create—from novel safety mechanisms to sophisticated evaluation techniques—shapes how millions of people interact with AI confidently. You're not just building products; you're defining industry standards for responsible AI. This is frontier research with immediate real-world impact. You'll tackle problems that require innovative solutions: training models that remain truthful and grounded across diverse contexts, building reward models that capture the nuanced spectrum of human values across cultures and languages, and creating automated systems that continuously discover and address potential issues before customers encounter them. You'll collaborate with world-class scientists, product managers, and engineers to transform state-of-the-art ideas into production systems serving millions. What We're Looking For * Deep expertise in state-of-the-art NLP and Large Language Models * Track record of building scalable ML systems * Passion for impactful research—where frontier science meets real-world responsibility at scale * Excitement about solving problems that will shape the future of AI Ready to work on AI safety challenges that define the industry? Join us. Key job responsibilities This is where you'll make your mark. You'll architect breakthrough Responsible AI solutions that become industry benchmarks, pioneering algorithms that eliminate false information, designing frameworks that hunt down vulnerabilities before bad actors find them, and developing models that understand human values across every culture we serve. Working with world-class engineers and scientists, you'll push the boundaries of model training—transforming bold research into production systems that protect millions of customers daily while withstanding attacks and delivering exceptional experiences. But here's what makes this role truly special: you'll shape the future. You'll lead certification processes, advance optimization techniques, build evaluation systems that reason like humans, and mentor the next generation of AI safety experts. Every innovation you drive will set new standards for trustworthy AI at the world's largest scale. A day in the life As a Responsible AI Scientist, you're at the frontier of AI safety—experimenting with breakthrough techniques that push the boundaries of what's possible. You partner with engineering to transform research into production-ready solutions, tackling complex optimization challenges. You brainstorm with Product teams, translating ambitious visions into concrete objectives that drive real impact. Your expertise shapes critical deployment decisions as you review impactful work and guide go/no-go calls. You mentor the next generation of AI safety leaders, watching ideas spark and capabilities grow. This is where science meets impact—building AI that's not just intelligent, but trustworthy and aligned with human values. About the team Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.