Careers

Amazon Web Services (AWS) is assembling an elite team of world-class scientists and engineers to pioneer the next generation of AI-driven development tools. Join the Amazon Kiro LLM-Training team and help create groundbreaking generative AI technologies including Kiro IDE and Amazon Q Developer that are transforming the software development landscape. Key job responsibilities As a key member of our team, you'll be at the forefront of innovation, where cutting-edge research meets real-world application: - Push the boundaries of reinforcement learning and post-training methodologies for large language models specialized in code intelligence - Invent and implement state-of-the-art machine learning solutions that operate at unprecedented Amazon scale - Deploy revolutionary products that directly impact the daily workflows of millions of developers worldwide - Break new ground in AI and machine learning, challenging what's possible in intelligent code assistance - Publish and present your pioneering work at premier ML and NLP conferences (NeurIPS, ICML, ICLR , ACL, EMNLP) - Accelerate innovation by working directly with customers to rapidly transition research breakthroughs into production systems About the team The AWS Developer Agents and Experiences (DAE) team is reimagining the builder experience through generative AI and foundation models. We're leveraging the latest advances in AI to transform how engineers work from IDE environments to web-based tools and services, empowering developers to tackle projects of any scale with unprecedented efficiency. Broadly, AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture 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 (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? If so, the WW Amazon Logistics, Business Analytics team is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner. We are looking for an enthusiastic, customer obsessed, Applied Scientist with good analytical skills to help manage projects and operations, implement scheduling solutions, improve metrics, and develop scalable processes and tools. The primary role of an Operations Research 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 how the final phase of delivery is done at Amazon. Candidates will be a high potential, strategic and analytic graduate with a PhD in (Operations 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 operations research, and the ability to use data and research to make changes. This role requires robust program management skills and research science skills in order to act on research outcomes. 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. Responsibilities may include: - Develop input and assumptions based preexisting models to estimate the costs and savings opportunities associated with varying levels of network growth and operations - Creating metrics to measure business performance, identify root causes and trends, and prescribe action plans - Managing multiple projects simultaneously - Working with technology teams and product managers to develop new tools and systems to support the growth of the business - Communicating with and supporting various internal stakeholders and external audiences

Amazon’s Customer Behavior Analytics org is looking for an Senior Manager, Applied Science, to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable ML and causal inference solutions to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. This is a high-impact role with opportunities to develop systems that affect investments to the size of billions of dollars. We work closely with business stakeholders and strive to continuously produce tangible impact on the company’s strategic, tactical planning and operations. A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate complex business problems into scientific challenge, and deliver data driven solutions - which will allow Amazon to make key investment decisions.You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine/deep learning at scale. You should have strong analytical and communication skills, be able to work with stakeholders and partners which include world-wide business leaders, distinguished scientist, economist, product managers and software teams. You will apply your expertise in Economics, ML/DL, statistics, and data-wrangling to identify opportunities for further research and to provide insights that drive larger initiatives. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization. Key job responsibilities The main responsibilities for this position include: - Apply your expertise in ML/DL and statistical modeling to develop solutions and systems that describe how Amazon’s marketing campaigns impact customers’ actions - Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions - Recruit high performing Economist, Applied Scientists and BIEs to the team and provide mentorship. - Establish team mechanisms, including team building, planning, and document reviews. - Review and audit modeling processes and results from scientists within and outside your team - Work with marketing leadership to align our measurement plan with business strategy - Formalize assumptions about how our models are expected to behave and explain why they are reasonable - Identify new opportunities that are suggested by the data insights - Bring a department-wide perspective into decision making About the team The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience.

Amazon's Last Mile Simulation and Analytics Team is seeking a Data Scientist to help design and optimize the world's most complex delivery network. You'll partner with process engineers, design engineers, simulation scientists, and innovation teams to solve high-impact problems across both greenfield and brownfield initiatives. In this role, you'll own the Data Science/ML roadmap—developing statistical and machine learning models, designing global experiments, and discovering new ways to enhance the customer experience. You'll translate ambiguous business challenges into mathematical models, contribute to discrete event simulations, and deliver solutions that scale. Success requires thriving in a fast-paced, collaborative environment while aligning research with Amazon's strategic priorities. Key job responsibilities Design and execute large-scale experiments to uncover insights from complex datasets Build scalable, automated pipelines for data analysis, model development, validation, and deployment Develop advanced ML solutions including regression, clustering, simulation, neural networks, and optimization algorithms Partner with cross-functional teams to implement data-driven strategies and measure impact Validate findings against alternative approaches and key performance indicators Build stakeholder relationships to drive improvements and prioritize customer needs

The Amazon Search team creates customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide. Amazon has grown rapidly and will continue to do so in foreseeable future. Providing a high quality search experience is a unique challenge as Amazon expands to new customers, countries, categories, and product lines. We are seeking a strong applied scientists to join the newly formed Relevance India team. This team’s charter is to increase the pace at which Amazon expands and improve the search experience at launch. In practice, we aim to invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models. Key job responsibilities Build machine learning models for Product Search. Develop new ranking features and techniques building upon the latest results from the academic research community. Propose and validate hypothesis to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system. Focus on identifying and solving customer problems with simple and elegant solutions. Design, develop, and implement production level code that serves billions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment. Collaborate with other engineers and related teams within A9.com and Amazon.com to find technical solutions to complex design problems. Take ownership. Understand the needs of various search teams, distil those into coherent projects, and implement them with an eye on long-term impact. Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects. Be ambitious. Find and eagerly tackle hard problems. Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to the technologies and vast technical tools and resources of Amazon and will need to learn how to use them effectively. Be customer focused. Work backwards from customer problems, figure out elegant solutions, and implement them for speed and scalability.

Amazon is seeking an Applied Scientist II to join our team and drive innovation in Generative AI and Large Language Model (LLM) applications. In this role, you will design, develop, and deploy AI solutions that directly impact millions of customers and transform how Amazon operates at scale. You'll work with state-of-the-art technologies including foundation models, prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques to solve complex business problems. Key job responsibilities • Model Development & Innovation: Design and implement novel GenAI/LLM solutions using foundation models (e.g., Claude, GPT, LLaMA) and AWS services including Amazon Bedrock, SageMaker, and other AWS AI/ML tools • Research & Experimentation: Conduct applied research to advance the state-of-the-art in LLM applications, including prompt engineering, few-shot learning, fine-tuning, and model evaluation • Production Deployment: Build scalable, production-ready AI systems that serve millions of requests with high reliability, low latency, and cost efficiency • Cross-Functional Collaboration: Partner with product managers, engineers, and business stakeholders to translate business requirements into technical solutions and drive measurable impact • Technical Leadership: Mentor junior scientists, contribute to technical strategy, and establish best practices for GenAI development across the organization • Evaluation & Metrics: Design rigorous evaluation frameworks to measure model performance, bias, safety, and business impact • Documentation & Communication: Publish technical papers, create detailed documentation, and present findings to both technical and non-technical audiences

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. We’re looking for scientists with deep LLM expertise to help us build the next generation of large language models. Our team focuses on post-training, including instruction tuning, reward modeling, and reinforcement learning. In this role, you will design and run large-scale experiments, analyze model behavior, and develop new training recipes that directly improve core capabilities like reasoning, user experience, and other frontier paradigms that redefine what LLMs can do. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

As an Applied Scientist for Last Mile Delivery Automation, you will be at the forefront of developing AI and ML solutions that power our delivery solutions. This role combines deep expertise in machine learning, computer vision, and robotics to solve complex challenges in real-world perception, navigation, and path planning. You will work closely with applied scientists, software developers, and product teams to research, design, and implement sophisticated algorithms that enable safe and efficient operations. This position requires a unique blend of theoretical knowledge and practical implementation skills, with a focus on transforming research concepts into production-ready solutions that can operate reliably in diverse real-world environments. Key job responsibilities - Design and develop advanced machine learning models and algorithms for perception, navigation and planning. - Lead research initiatives in areas such as computer vision, sensor fusion, behavioral prediction, and path planning - Transform research concepts into production-ready solutions that meet strict safety and performance requirements - Develop novel approaches to solve complex technical challenges in perception, navigation and planning - Create and implement metrics and evaluation frameworks to measure model performance - Collaborate with engineering teams to integrate ML solutions into production stack - Publish research findings and represent Amazon at technical conferences About the team The Applied Science team within Amazon's Last Mile Delivery Automation organization focuses on developing machine learning solutions for autonomous systems. We work at the intersection of computer vision, deep learning, robotics, and control systems to create robust and scalable algorithms that enable safe autonomous operation. Our team combines expertise from diverse scientific backgrounds to tackle fundamental challenges in perception, prediction, and decision-making.

The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities - Experience in causal ML and treatment effect estimation, including methods like propensity scoring, doubly robust estimators, and uplift modeling. Strong background in Python, ML pipelines, and deploying models to production with robust monitoring and evaluation. Familiarity with causal inference frameworks and translating business questions into actionable causal insights. - Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch. For example, starting from deep scientific thinking about new ways to support customers’ journeys through discovery, you analyze how customers discover, review and purchase Private Brands to innovate marketing and merchandising strategies. - Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results. - Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions. - Present results, reports, and data insights to both technical and business leadership. - Constructively critique peer research and mentor junior scientists and engineers. - Innovate and contribute to Amazon’s science community and external research communities.

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：北京朝阳区 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 如果您正在攻读计算机，AI，ML或搜索领域专业的博士或硕士研究生，而且对应用科学家的实习工作感兴趣。如果您也喜爱深入研究棘手的技术问题并提出解决方案，用成功的产品显著地改善人们的生活。 那么，我们诚挚邀请您加入亚马逊的International Technology搜索团队改善Amazon的产品搜索服务。我们的目标是帮助亚马逊的客户找到他们所需的产品，并发现他们感兴趣的新产品。 这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出和探索创新，基于TB级别的产品和流量数据设计机器学习模型。您将集成这些模型到搜索引擎中为客户提供服务，通过数据，建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。