Careers

The Healthcare AI organization in AWS is seeking an Applied Science Manager to lead science and data teams working on innovative AI-powered healthcare solutions. We are developing innovative products that leverage generative and agentic AI to transform clinical and administrative workflows for healthcare providers. Our aim is to improve patient care, enhance operational efficiency, and deliver exceptional value to our customers. You will lead a team of applied scientists, working on transformative healthcare solutions powered by cloud computing and artificial intelligence. This role offers an opportunity to work at the forefront of applied AI/ML and distributed systems, building new products and services from the ground up. Our team builds on our existing successful healthcare business, which serves major providers and payers in the US. You'll be instrumental in creating solutions that address complex challenges in areas such as clinical documentation, health data analytics, and accurate billing, ultimately contributing to better health outcomes for individuals and populations. Key job responsibilities As an Applied Science Manager, you will be responsible for building and leading a world-class team that pushes the boundaries of computer vision, machine learning, and artificial intelligence. In this role, you will drive the technical vision and strategy for your team while fostering a culture of innovation and scientific excellence. You will balance hands-on technical leadership with people management responsibilities, ensuring your team delivers innovative solutions while growing professionally. The role requires someone who can think strategically about business problems while diving deep into technical details when needed. - Building and mentoring teams of Applied Scientists and ML Engineers - Setting technical direction and research strategy aligned with business goals - Driving innovation in medical administration reasoning systems, AI agent design, and medical coding - Collaborating with cross-functional teams to translate research into production - Managing project portfolios and resource allocation A day in the life Inclusive Team Culture Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have 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, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life Balance Our team puts a high value on work-life 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. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign opportunities based on what will help each team member develop into a better-rounded contributor. About the team Our team builds on our existing successful healthcare business, which serves major providers and payers in the US. You'll be instrumental in creating solutions that address complex challenges in areas such as clinical documentation, health data analytics, and accurate billing, ultimately contributing to better health outcomes for individuals and populations.

Amazon Ads is a multi-billion dollar global business that delivers advertising experiences across Amazon's owned-and-operated properties (including Prime Video, Twitch, Fire TV, and Amazon.com), third-party publisher networks, and emerging channels like generative AI-powered shopping experiences. As one of the fastest-growing segments of Amazon, we operate at unprecedented scale across desktop, mobile, connected TV, and emerging surfaces. Within Amazon Ads, Traffic Quality is a critical pillar of advertiser trust and marketplace integrity. Our mission is to build advanced capabilities that work at petabyte scale to detect sophisticated invalid traffic (IVT) which includes sophisticated non-human traffic, bot networks, and fraudulent engagement patterns across programmatic advertising. We are on a journey to establish Amazon Ads as an industry leader in traffic quality standards and transparency. Our research agenda focuses on staying ahead of adversarial actors through continuous innovation in detection methodologies, leveraging state-of-the-art techniques in deep learning and generative modeling, user behavior and multi-modal representation learning, anomaly detection, time-series analysis, and sparse labeling methods. We process billions of ad events daily, developing novel algorithms that balance precision and recall while operating under strict latency constraints. Our work directly protects hundreds of millions of dollars in advertiser spend annually while maintaining a seamless user experience. Key job responsibilities As a Data Scientist II in Traffic Quality, you will solve inherently hard problems in advertising fraud detection by applying advanced statistical techniques and machine learning. You'll work on systems that process billions of ad impressions and clicks per day, using Amazon's cloud services including EC2, S3, EMR, Sagemaker, and RedShift. - Define and frame new research problems in fraud detection where neither problem nor solution is well-defined. - Apply new machine learning approaches, models, and algorithms to detect sophisticated invalid traffic. - Apply domain knowledge to perform broad data analysis as a precursor to modeling and build business insights. - Work with unstructured and massive datasets to deliver results. - Produce research reports meeting top-tier external publication standards. - Mentor and develop junior scientists on the team. About the team Here are a few papers published by the team: 1/ [Scaling Generative Pre-training for User Ad Activity Sequences. AdKDD 2023.](https://assets.amazon.science/b7/42/03be071743d5a57cb1656e6caa34/scaling-generative-pre-training-for-user-ad-activity-sequences.pdf) 2/ [SLIDR: Real-time Robot Detection On Online Ads, IAAI 2023, Deployed Highly Innovative Applications of AI Track (AAAI 2023)](https://assets.amazon.science/75/2f/3b7106b143f38f7f4d2806388ace/real-time-detection-of-robotic-traffic-in-online-advertising.pdf) 3/ [Self-supervised Representation Learning Across Sequential and Tabular Features Using Transformers, NeurIPS 2022, First Table Representation Learning Workshop](https://openreview.net/forum?id=wIIJlmr1Dsk)

The AI Center of Excellence (AICE) builds AI primitives that power system-intrinsic intelligence and Trusted Intelligent Knowledge Infrastructure for both AI-as-a-Consumer and human users. We develop AI capabilities independently and in partnership with product-owning teams to evolve Amazon's AI-driven operations and productivity. Our impact is enterprise-broad and global. We are looking for an Applied Scientist who can identify high-impact problems, design rigorous experiments, and translate research into hardened, reusable primitives ready for broad consumption across the enterprise. Key job responsibilities * Research, design, and develop AI/ML primitives - defining problem spaces, formulating approaches, running experiments, and validating outcomes with scientific rigor * Translate research findings into production-ready primitives, working closely with machine learning engineers to harden and scale solutions * Drive the scientific direction of AICE primitives, identifying opportunities where novel approaches can unlock step-function improvements * Design and execute experiments to validate primitive performance, robustness, and generalizability before broad consumption by partner teams * Collaborate with product-owning teams to understand their problem spaces and ensure AICE primitives deliver measurable value when integrated * Contribute to AICE's mission of driving AI transformation through best practices in applied research, evaluation methodology, and responsible AI within your area of expertise * Publish findings, share learnings, and raise the scientific bar across the team A day in the life Every day brings new challenges. You might be deep in experimentation - designing evaluations to stress-test a new primitive's robustness. The next day, you could be analyzing results and iterating on model architectures. Later in the week, you may collaborate with partners to understand their domain and shape a primitive that fits their product needs. Other days, you'll work alongside our MLEs to harden a validated approach for broader consumption. No two weeks look the same. You'll move fluidly between research and applied problem-solving - always with the goal of building AI primitives that are scientifically sound, trusted, and impactful at enterprise scale. About the team AICE is a team of scientists and machine learning engineers building the AI primitives that power Amazon's intelligent systems. We develop and harden reusable capabilities for broad consumption by product teams across the enterprise - and partner with those teams to integrate them.

We are seeking an Economist to join our growing team in Japan. In this role, you will apply rigorous economic and econometric methods to guide critical business decisions affecting Amazon's JP marketplace. You will build causal inference models to measure the impact of business initiatives on pricing, product selection, delivery speed, profitability, and customer experience. Working alongside economists, data scientists, and business intelligence engineers, you will tackle challenging problems using state-of-the-art analytical techniques while providing advisory support to business stakeholders. As one of the first economists based outside North America and EU, you will play a pioneering role in expanding Amazon's economist community in Asia and make an outsized impact on our international marketplace operations. At Amazon, you'll work alongside the latest AI and GenAI tools that are increasingly woven into how teams operate: from AI-powered capabilities that accelerate decision-making, to Generative AI that helps you focus on work that truly matters. You'll have opportunities and resources to develop AI fluency at your own pace, with continuous learning built into the culture. Key job responsibilities Design and execute causal inference analyses using econometric techniques to measure the impact of business initiatives on key marketplace metrics Build economic models to optimize pricing strategies, product selection decisions, and delivery speed investments that balance customer experience with business profitability Collaborate with product managers, engineers, and business leaders to translate complex business questions into tractable research problems and deliver actionable insights Design and analyze experiments to test hypotheses and validate causal relationships in observational data Develop scalable analytical frameworks and tools using R, Python, or Stata that can be leveraged across multiple business use cases Present findings and recommendations to technical and non-technical audiences, including senior leadership, through clear written narratives and data visualizations Partner with Machine Learning and BI team members to integrate economic insights into automated decision-making systems About the team The JP Economics and Decision Sciences team is a central science team that applies rigorous economic theory, causal inference methods, and machine learning to solve complex business challenges across the JP marketplace and beyond. We work closely with JP business leaders to drive change at Amazon, focusing on solving long-term, ambiguous problems while providing advisory support for short-term business pain points. Key topics include pricing, product selection, delivery speed, profitability, and customer experience. We tackle these issues by building novel economic and econometric models, machine learning systems, and high-impact experiments which we integrate into business, financial, and system-level decision making. Our work is highly collaborative and we regularly partner with JP-, EU-, and US-based interdisciplinary teams.

Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. Key job responsibilities We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. * Define and implement new automated reasoning features that employ scalable and efficient approaches to solve complex problems using neural learning and symbolic/formal reasoning * Apply software engineering best practices to ensure a high standard of quality for all team deliverables * Work in an agile, startup-like development environment * Deliver high-quality scientific artifacts * Work with the team to help drive business decisions About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.

MULTIPLE POSITIONS AVAILABLE Employer: Amazon Development Center U.S., Inc. Offered Position: Applied Scientist III - AMZ007408 Job Location: New York, NY Position Responsibilities: Participate in the design, development, evaluation, deployment, and updating of formal reasoning systems for security, privacy, and data protection applications. Drive technical and scientific innovation in security automation, data protection, and privacy-preserving technologies, with a focus on developing scalable solutions for cloud environments. Develop and/or apply formal verification techniques and automated theorem proving methods for different applications in cloud security and privacy. Collaborate with internal and external users to understand requirements and enhance formal verification and automated reasoning capabilities. Lead research and development efforts in AI security, specifically evaluate emerging threats and opportunities, including securing Generative AI systems and designing robust safeguards. Proactively identify and explore new opportunities for deploying and leveraging formal reasoning solutions across various domains.

Amazon Seller Assistant is our flagship GenAI-first, multi-agent system that reimagines Seller experience. Our vision is to provide each seller with a proactive, autonomous, agentic assistant that understands their business and helps them navigate the complexities of selling by anticipating their needs, surfacing insights, resolving issues, taking actions on their behalf, and helping them grow. Amazon Seller Assistant helps millions of sellers on Amazon serve billions of customers worldwide. We are seeking a world-class Senior Data Scientist to help define and build the next generation of Amazon Seller Assistant. You will partner with top-tier scientist, engineers and product teams to launch production-grade agentic capabilities at Amazon's scale — owning your problem space end-to-end, from a crisp customer insight to a shipped product that millions of sellers rely on. Key job responsibilities • Own the science vision, strategy, and roadmap for a key Seller Assistant capability area. • Define and ship agentic experiences — sub-agent onboarding, tool onboarding, evaluations— that solve hard seller problems at scale. • Partner with scientists and engineers to translate frontier AI research into production-grade features sellers trust and depend on. • Design rigorous evaluation frameworks — automated and human-in-the-loop — to measure agent quality, accuracy, and business impact. • Deep-dive into seller data, identify unmet needs, and write compelling PRFAQs that set the direction for your team. • Drive cross-functional alignment across science, engineering, UX, and business teams to deliver with speed and quality. About the team Amazon Seller Assistant team operates at the very frontier of agentic AI and agentic commerce — not as a research group, but as a team shipping production-grade, multi-agent systems used by millions of sellers worldwide. We move with the urgency of a startup and the resources of the world's most customer-obsessed company, the latest breakthroughs in science and engineering into capabilities that sellers rely on every day.

Amazon is looking for talented Postdoctoral Scientists to join our research team for a full-time research position focused on visual localization and navigation for real-world applications. Our work focuses on developing next-generation assistive technologies and logistics platforms that rely on robust, scalable visual perception systems. We are building solutions that enable devices and agents to understand, localize within, and navigate complex real-world environments—from indoor spaces with dynamic layouts to large-scale outdoor settings. We are looking for Postdoctoral Scientists to work at the intersection of computer vision, SLAM, and scene understanding—supporting innovations that will be deployed to real systems at global scale. The core technical challenges include building metric-semantic maps of complex environments, performing robust visual relocalization under appearance change, maintaining long-term map consistency, and achieving accurate monocular localization using both geometric and learning-based approaches—all under real-time constraints on real hardware. The solution space is deliberately open-ended. We are looking for researchers who want to push the boundaries of visual localization and spatial AI—and see their work running on real platforms within months. Key job responsibilities In this role you will: * Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. * Publish your innovation in top-tier academic venues and hone your presentation skills. * Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. A day in the life 0

Employer: Amazon Web Services, Inc. Position: Data Scientist II - AMZ27351.1 Location: San Francisco, CA Multiple Positions Available: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. (40 hours / week, 8:00am-5:00pm, Salary Range $175425 - $212800) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

How to use the world’s richest collection of e-commerce data to improve payments experience for our customers? Amazon Payments Data Science team seeks a Data Scientist for building analytical solutions that will address increasingly complex business questions in the Amazon Currency convertor space. Amazon.com has a culture of data-driven decision-making and demands insights that are timely, accurate, and actionable. This team provides a fast-paced environment where every day brings new challenges and new opportunities. As a Data Scientist in this team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the Amazon currency convertor business team through a combination of Gen AI, LLM and other machine learning techniques for text analytics, segmentation and prediction. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. Key job responsibilities • Understand the applications of causal inference models on real datasets, including assessment of marketing campaigns, online experiments, uplift analysis etc • Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management • Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus are • Innovate by adapting new modeling techniques and procedures • Effective exploratory data analysis, and model building using industry standard regression and classification techniques such as Random Forest, XGBoost package, Keras framework • Demonstrate thorough technical knowledge Fine Tuning of Amazon LLMs to handle large blocks of text, using Generative AI to solve for summarization tasks and prevent catastrophic forgetting, feature engineering of massive datasets, • Be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets • Have exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive