Careers

Alexa for Shopping (Rufus) is Amazon's new AI-powered shopping assistant that combines the capabilities of Rufus and Alexa+ to provide a more personalized and intelligent shopping experience. We are building the future of AI-powered commerce, where every customer interaction is conversational, personalized, and proactive. We are seeking a Director, Applied Science to lead the science vision and execution for the next-generation conversational AI platform. This leader will own the end-to-end science roadmap for a multi-agent architecture powered by large language models (LLMs), SLMs, reinforcement learning (RL), and post-training optimization to deliver the most helpful, accurate, and fastest AI shopping assistant in the industry. This is a transformational leadership role. You will lead the science that makes this possible: distilling Amazon's vast data assets into rich context, building specialized models through fine-tuning and RL that match frontier model quality at a fraction of the latency, and architecting intelligent agent routing across diverse use cases (pre-purchase, post-purchase, cross-Amazon services). The ideal candidate is deeply steeped in LLM-based architectures, post-training techniques (RLHF, DPO, fine-tuning), and multi-agent systems. They are passionate about applied science, working back from customer experience to define what matters, and building teams that ship production AI at scale. This leader will shape the science philosophy for one of Amazon's highest-visibility AI initiatives. Key job responsibilities - Define and execute the science strategy for Alexa for Shopping conversational AI platform - Lead a large, multidisciplinary organization of Applied Scientists, Research Scientists, and Machine Learning Engineers. - Architect and scale multi-agent systems - Partner with Product, Engineering, and senior leadership (including S-team) to align AI investments with long-term business goals and the vision of conversational commerce replacing traditional shopping paradigms. - Establish scientific best practices across experimentation, evaluation, model iteration, and production deployment for a high-traffic, latency-sensitive customer-facing system. - Mentor and develop senior technical leaders; foster a culture of innovation, customer obsession, and operational excellence.

We are working on improving shopping on Amazon using the conversational capabilities of large language models and through customer behavioral data to make them more personalized for each customer. We are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. In this role, you will be managing a team working on Large Language Model (LLM) and/or Vision-Language Model (VLM) post-training and alignment for new shopping experiences. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. 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!

Amazon is building a world class advertising business and defining and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. Our products are strategically important to our Retail and Marketplace businesses, driving long-term growth. Sponsored Ads helps merchants, retail vendors, and brand owners grows incremental sales of their products sold on Amazon through native advertising. Sponsored Ads achieves this by using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. If you are looking to make an impact, this is the team for you. You will join a newly-founded team with a broad mandate to experiment and innovate, which will give you the flexibility to develop systems and services from the ground up. As a Principal Applied Scientist in FAIM, you will help build new foundational AI technologies from the ground up and create and launch features for advertisers globally. You will partner with engineers, product managers, TPMs, and senior management to help create these world-class solutions. Most importantly, you will have an opportunity to grow and broaden your technical and scientific skills as you work in an environment that thrives on creativity, experimentation, and collaboration. Key job responsibilities Develop optimization strategies for Full-Funnel Ads Campaigns at Amazon Work with the leadership team on long-range AI/ML plans for Full Funnel Ads Campaigns Help the team adopt the latest SOTA technologies for large scale advertising

We are hiring a Senior Manager, Economics to the Sales Channels team within Amazon Web Services (AWS) Central Econ and Science team. The team partners with the business to optimize sales motions, partner programs, and incentives in multi-sided marketplaces. The problem space includes experimental, quasi-experimental, and observational research design, establishing telemetry for future measurement, and the development of recommendation systems and incentive plans. This role will support a strong team in both sourcing new workstreams and executing existing workstreams. We will consider Applied Scientists with experience working with economists for this role. Key job responsibilities This role interfaces directly with executives, product/program owners, science leadership, and science ICs to create multi-year research agendas that drive step-change growth for the business. As this role is responsible for setting and executing the priorities of a centralized team, stakeholder management, working backward and partnering to work across teams (earns trust) is vital. The team’s mandate includes disambiguating structural relationships, so a strong grounding in applied theory is key to success in this position. The role will also own both production recommendation systems and feature generation for external systems, so experience with production-level development is important. This role will shape the strategic direction of the AWS Central Economics and Science team and collaborate with other science teams at AWS, especially those working on developing policies so that AWS sellers and partners meet customers where they are and help them grow. A day in the life Our team takes big swings and works on hard cross-organizational problems where success is long term and not guaranteed. We expect team members to grow their skills in a supportive and collegial environment. We expect and measure impact, and we hold each other to high standards. We work hard during work hours, but we also don’t encourage working at nights or on weekends: burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed and excited. It makes for bigger impact, faster skill accrual and thus career advancement. About the team Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn’t translate into actionable insights that are rolled out and impact the real economy. We emphasize clear, consistent communication since being able to explain what we do ensures high success rates and lowers administrative churn. Also: we laugh a lot. If it’s not fun, what’s the point?

Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2026, we are focused on economics and science in areas related to (1) lowering cost-to-serve, (2) optimizing selection, and (3) emerging machine learning. We also have some ongoing and highly-leveraged collaborations that help partner teams inside Amazon short-circuit months of R&D or otherwise look around corners. We are looking for an Applied Scientist to build and deliver state-of-the-art science and engineering solutions to improve our Stores business. In this role, you will work in a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing and maintaining the scientific models, benchmarks, and services. Graduate education or hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a big plus. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity. Key job responsibilities The successful candidate will lead large-scale science initiatives from research to production and translate complex business problems into mathematical frameworks. They will design and implement large-scale algorithms for complex supply chain and marketplace problems, and design incentive-compatible mechanisms for marketplace challenges. The ideal candidate will have a strong publication record in top-tier conferences/journals (INFORMS, EC, WINE, ICML, NeurIPS, etc.) and experience coordinating cross-functional projects. Hands-on experience building science solutions to mechanism design problems (e.g., optimal auction design, welfare maximization under constraints, incentive compatible coordination), with expertise in statistical learning and algorithm development. Leadership responsibilities include influencing technical strategy and roadmaps for complex initiatives, influencing senior stakeholders and shaping technical direction, and fostering team growth.

Are you passionate to join an innovative team of scientists and engineers who use machine learning and AI techniques to create state-of-the-art solutions to help seller succeed on Amazon? The Selling Partner Selection Success org is looking for a Principal Applied Scientist to lead us on our mission to provide selection success support on Amazon, and empower sellers to grow their business and provide a great customer experience. As a Principal Applied Scientist on our team of scientists and engineers, you will have opportunities to create significant impact on our systems, our business and most importantly, our customers as we take on challenges that can revolutionize the e-commerce industry. You will identify specific and actionable opportunities to solve business problems, propose state-of-the-art solutions and collaborate with engineering, and business teams for future innovation. You need to be a great translation between ambiguous business domains and rigorous scientific solutions, an expert at inventing and simplify, and a good communicator to surface insights and recommendations to audiences of varying levels of technical sophistication. Key job responsibilities - Drive and advocate technical vision that drives the significant business impact - Use machine learning and AI techniques to create scalable seller-facing solutions - Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes - Design, development and evaluation of highly innovative models - Work closely with software engineering teams to drive real-time model implementations and new feature creations

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for computer vision applications. - Research and implement the state-of-the-art computer vision and Vision Language models algorithms. - Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices - Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors.

We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to help build industry-leading language technology powering Alexa for Shopping, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey. This innovative role focuses on developing conversation-based, multimodal shopping experiences, utilizing data analysis, statistical modeling, machine learning (ML) technologies, and experimentation to drive product decisions and optimize customer experiences. Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more. We do this by leveraging advanced analytics, Natural Language Processing (NLP), Machine Learning (ML), A/B testing, causal inference, and data-driven insights to continuously improve our systems. Key job responsibilities Key job responsibilities As a Data Scientist on our team, you will be responsible for the analysis, modeling, and optimization of AI technologies that will shape the future of shopping experiences. You will play a critical role in measuring and improving multimodal conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graphs, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include designing experiments, analyzing results, and launching new features, products and systems. A day in the life Perform hands-on analysis and modeling of enormous multimodal datasets to develop insights into how to best help customers throughout their shopping journeys. Use statistical methods, machine learning, and data mining techniques to create scalable solutions for measuring and optimizing shopping assistant systems based on a rich set of structured and unstructured contextual signals. Design and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insights. Develop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impact. Build predictive models and conduct deep-dive analyses to identify opportunities for improving customer experience, conversion, and satisfaction. Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment. Establish automated processes for large-scale data analysis, ETL pipelines, metric generation, and experimentation frameworks. Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations. About the team The Alexa for Shopping Science team, based in London, works alongside ~150 engineers, designers and product managers, shaping the future of AI-driven shopping experiences at Amazon. The team works on every aspect of the AfS AI, from making it agentic, enabling customers to set price alerts or empower AfS to act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance. We utilize and advance state-of-art techniques in the fields of Natural Language Processing, gen AI, Information Retrieval, Machine/Deep Learning, and Data Mining. We validate our work by actively participating in the internal and external scientific communities.

AWS Security is seeking a Research Scientist to apply rigorous quantitative methods to problems at the intersection of cloud security and customer experience. In this role, you will design and conduct large-scale research studies—leveraging advanced statistical modeling, survey research, and behavioral science—to surface actionable insights. Key job responsibilities Design and develop quantitative measurement models—including structural equation models (SEM) and latent variable frameworks—that map the relationships between security experiences and customer perception outcomes. Define and validate customer perception constructs through confirmatory factor analysis, survey design, and large-scale data collection across diverse customer segments, including technical and non-technical decision-makers. Extend existing scientific techniques and invent new approaches to address complex measurement challenges in the enterprise and emerging technology domain, including multi-stakeholder modeling, cross-segment analysis, and longitudinal study design. Partner cross-functionally with security specialists, program managers, and customer teams to integrate data sources into a unified research program. Establish baseline metrics and develop leading and lagging indicators that enable data-driven goal-setting and ongoing measurement of customer perception trends over time. Ensure scientific rigor by documenting methodology, validating model fit using established statistical criteria, and maintaining reproducibility of results. A day in the life You will spend your time designing research instruments, analyzing complex multi-source datasets, iterating on quantitative models, and presenting findings to senior leaders. You will collaborate with program managers, engineers, and strategists to connect research insights to real-world customer outcomes. About the team The AWS Security team owns security for all services offered by AWS, including EC2 and S3. This creates a lot of different opportunities for cross-team collaboration and high visibility into the company. We dive deep into security technologies to innovate and provide our customers the best possible experience with every transaction that happens in the cloud. As part of the AWS Security team, you’ll work alongside a motivated and diverse team eager to transform the cloud security landscape. Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the 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 Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

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.