Careers

Do you want to join an innovative team applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience? Are you excited about working with large-scale datasets and developing models that solve real-world fraud and risk challenges? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to help develop scalable machine learning solutions that safeguard millions of transactions every day. In this role, you will partner with senior scientists and engineers to translate business problems into data-driven solutions, build and evaluate models, and contribute to next-generation risk prevention systems, including applications of Generative AI and LLM technologies. Key job responsibilities Apply machine learning and statistical techniques to build and improve risk management models Analyze large-scale historical data to identify risk patterns and emerging trends Develop, validate, and deploy innovative models under the guidance of senior scientists Experiment with emerging technologies, including GenAI/LLMs, to enhance automation and risk evaluation Collaborate closely with software engineers to implement models in real-time production systems Partner with operations and business teams to improve risk policies and operational efficiency Build scalable, automated pipelines for data analysis, model training, and validation Monitor model performance and provide clear reporting on key risk and business metrics Research and prototype new modeling approaches to improve system performance

Alexa International is looking for passionate, talented, and inventive Senior Applied Scientists to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. Senior applied scientists will drive cross-team scientific strategy, influence partner teams, and deliver solutions that have broad impact across Alexa's international products and services. Key job responsibilities As a Senior Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs, particularly delivering industry-leading scientific research and applied AI for multi-lingual applications — a challenging area for the industry globally. Your work will directly impact our global customers in the form of products and services that support Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in text, speech, and vision domains. The ideal candidate possesses a solid understanding of machine learning, speech and/or natural language processing, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environment, like to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and are able to influence and align multiple teams around a shared scientific vision. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Fine-tune/post-train LLMs using advanced and innovative techniques like SFT, DPO, Reinforcement Learning (RLHF and RLAIF) for supporting model performance specific to a customer’s location and language. * Quickly experiment and set up experimentation framework for agile model and data analysis or A/B testing. * Contribute through industry-first research to drive innovation forward. * Drive cross-team scientific strategy and influence partner teams on LLM evaluation frameworks, post-training methodologies, and best practices for international speech and language systems. * Lead end-to-end delivery of scientifically complex solutions from research to production, including reusable science components and services that resolve architecture deficiencies across teams. * Serve as a scientific thought leader, communicating solutions clearly to partners, stakeholders, and senior leadership. * Actively mentor junior scientists and contribute to the broader internal and external scientific community through publications and community engagement.

Amazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. Are you an expert in Natural Language Processing (NLP), computer vision, Large Language Models (LLM) and multi-modality? Are you interested in building Generative AI solutions on complex business problems that have significant global benefit. The Brand Protection Science team designs and builds high performance AI systems using machine learning and deep learning that identify and prevent infringement and counterfeit on behalf of brand owners worldwide. We are looking for a highly talented scientist to help build of our AI vision for Brand Protection. As a applied scientist on the team, you will use STOA AI and ML techniques to understand and extract key information from product detail page, built automated AI solutions that thinks like human to make autonomous decisions. You will work backwards from data insights and customer feedback to build the right machine learning solutions, and resourceful in finding innovative solutions to unsolved problems. You will work closely will product team and engineering partners to launch the solution into production and own the end-to-end solution. An ideal candidate should be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied scientist, you will own the design and development of end-to-end AI solutions, from conception to launch in a rapidly evolving environment. You’ll have the opportunity to create science roadmaps, and drive production level projects that will support Amazon Science. extensive experience driving Machine Learning initiatives, specially in NLP and LLM applications, from conception to launch in a rapidly evolving environment. You will work closely with other scientists and enigneers to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Major responsibilities: - Understand business challenges by analyzing data and customer feedback - Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement - Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems. - Use deep learning and machine learning techniques to create scalable solutions for business problems - Create business and analytics reports and present to the senior management teams - Research and implement novel AI solutions and publish research papers Key job responsibilities Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work. For more information on the Amazon Science community please visit https://www.amazon.science.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.

Amazon’s third-party marketplace is a multibillion-dollar global ecosystem, connecting customers and sellers across the world through millions of transactions annually. The Seller Fee Science Team integrates economic modeling, machine learning, and artificial intelligence to guide business fee strategy, ensure fees are accurately computed for millions of products, and improves the seller experience with AI tools that support any fee related contact (understanding, audit, and dispute). We build the scientific foundation that empowers sellers to grow their businesses with clarity and confidence. Our team brings together world-class economists, physicists, mathematicians, and computer scientists to tackle diverse challenging problems that require theoretical rigor and deliver real-world impact. For example, precision measurement of difficult to measure products, large-scale simulation of sales, inventory, and policy changes, as well as leveraging natural language understanding and automated reasoning to interpret policy, generate code, resolve disputes, audit fees, and respond to sellers at meaninful scale. As an applied scientist on our team, this role will focus on the application of machine learning and artificial intelligence to predict and reconcile measurement of products globally. This blends together statistical modeling, application of NLP, image processing, classical machine learning, cost-benefit analysis, causal modeling, and optimization. Your work will shape not only how fees are implemented, but how they are interpreted, experienced, and trusted at scale. You will partner closely with engineers and product partners to take your solutions from research to production. We are seeking scientists who are motivated by first principles, disciplined experimentation, and the technical challenge of deploying ideas at global scale. This is an opportunity to work on consequential problems where mathematical rigor meets real-world complexity, and where your models, algorithms, and systems will directly influence the experience of millions of sellers. If you are driven to build elegant solutions to hard problems—and to see them operate in production at meaningful scale—we would welcome the opportunity to build with you. Key job responsibilities - Identify opportunities to improve Seller Experience and translate ambiguous business challenges into well-defined scientific problems with measurable impact. - Design, develop, and deploy AI/ML models that improve fee accuracy, automate policy-to-code translation, and enhance seller understanding of fee calculations. - Partner closely with engineering and product teams to productionize solutions, meeting latency, scalability, reliability, and other system constraints. - Apply rigorous experimentation, causal inference, and simulation methods to validate models and quantify business impact at scale. - Communicate scientific innovations and results clearly to cross-functional stakeholders and contribute to the broader internal and external scientific community through publications, talks, and technical artifacts.

The North America Stores GenAI Evaluation Media (GEM) team is seeking a Senior Applied Scientist to help shape the future of visual shopping experiences. We're building CXs and foundational capabilities to understand, enhance, and generate real-time GenAI imagery, videos and CXs that inspire customers and drive purchase confidence, towards our vision to be the leader in visual media. Specifically, the charter will focus on visual agentic experiences, multi-modal personalization, and real-time image/video generation, looking ahead as customer shopping continues to inspirational assistant-driven experiences. As a Senior Applied Scientist on the team, you will own and define the scientific vision, strategy, and roadmap for agentic AI capabilities that inform and guide the customer's shopping journey through visuals. This includes architecting and advancing core science primitives for multimodal understanding, visual content generation and editing, personalized virtual try-on, and automated quality assurance. You will establish the technical direction for foundational capabilities that enable customers to express and discover styles through multimodal conversation and receive personalized, visual responses that bring their ideas to life. Your scientific leadership will emphasize accurate, real-time visual understanding and generation, contextual understanding, and scalable personalization, enabling agentic AI to actively collaborate with customers to achieve their style goals. You will set the long-term research agenda, bringing together computer vision, natural language processing, generative AI, and human-centered design to create agentic shopping experiences that are as intuitive as talking to a human specialist with a deep domain knowledge base. Success requires defining and institutionalizing robust evaluation frameworks and metrics, influencing and aligning cross-functional partners across organizations, validating asset effectiveness across diverse customer touch points, identifying whitespace opportunities, and staying at the forefront of rapid advances in AI technology. The ideal candidate will have deep and broad technical expertise in Computer Vision, Generative AI, or related fields with a proven track record of connecting scientific work to customer and business outcomes at scale. You will serve as a technical leader and thought partner to scientists, engineers, and senior stakeholders across Amazon, mentoring junior scientists, raising the scientific bar, and delivering innovation while upholding a culture of scientific excellence and customer obsession. This role requires both rigorous research skills and practical engineering instincts, with a focus on delivering solutions that scale and a demonstrated ability to navigate ambiguity, make high-judgment trade-offs, and drive alignment across competing priorities. You will be expected to contribute to the broader scientific community through publications, patents, and internal knowledge sharing. This is a unique opportunity to shape the technical strategy for visual commerce through applied AI research, building the systems that will define how hundreds of millions of customers discover and evaluate products and styles through visual experiences. Key job responsibilities Innovation & Technical Execution Define the research roadmap and advance core science primitives for vision and language understanding, visual content generation and editing, virtual try-on, and automated quality assurance via state-of-the-art computer vision, machine learning, and generative AI Architect visual agentic systems, making high-judgment trade-offs across visual quality, relevance, latency, cost, and long-term extensibility Establish evaluation frameworks, metrics, and success criteria for the team's scientific initiatives, institutionalizing rigorous validation across customer touch points Own end-to-end delivery of complex, ambiguous research initiatives from problem formulation through experimentation to production deployment, with minimal guidance Identify whitespace opportunities by staying at the forefront of AI/ML advances and translating them into actionable research directions with clear customer and business impact Drive development and deployment of scalable agentic systems for visual content understanding and generation, ensuring architectural decisions support long-term platform evolution Set and continuously raise the scientific and engineering bar across the team Tackle the team's most complex technical problems while maintaining practical focus on customer value and solution generalizability Advance the team's scientific reputation through high-impact publications and presentations at top-tier internal and external venues, and generate intellectual property through patents Cross-functional Influence & Leadership Influence product and engineering roadmaps by partnering with senior leadership to shape customer-facing features grounded in scientific insight Drive technical alignment across multiple teams and organizations within Amazon, resolving ambiguity and building consensus on approaches Communicate research vision, findings, and technical trade-offs persuasively to executive, technical, and non-technical stakeholders, shaping investment decisions Mentor and develop junior and mid-level scientists, accelerating their growth and impact

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.

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 Data Scientist to help define and build the next generation of Amazon Seller Assistant. You will partner with top-tier scientists, product managers and engineers 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 -- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience -- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience. -- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods). -- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring. -- Apply NLP and statistical modeling techniques—including topic modeling, clustering, semantic similarity, and classification—to uncover insights from unstructured seller interactions, feedback, and content. -- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations. -- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams. -- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement. -- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI. 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, transforming the latest breakthroughs in science and engineering into capabilities that sellers rely on every day.

The Supply Chain Optimization Technologies (SCOT) Buying team is at the heart of Amazon's global inventory management. We build sophisticated automated systems that decide what to buy, when to buy it, and where to place billions of dollars in inventory across Amazon's vast network. These decisions directly impact Amazon's ability to delight customers and drive operational efficiency. Join us to solve complex technical challenges at massive scale, shaping the core of Amazon's retail business through data-driven decisions. As a Data Scientist in SCOT Buying Outcomes, you will be responsible for developing and supporting best-in-class data science methodologies and models that provide crucial inputs to Amazon’s diverse buying programs. You’ll address ambiguous buying questions at scale by building tools drive key decisions in buying and sourcing strategies across Just in Time, Advanced Purchasing, and Global Ordering programs. This role requires exceptional technical expertise to handle massive datasets, familiarity with deriving causal inferences using observational data, and able to model variations related with different buying and cost scenarios across different planning horizons. Upon completion of statistical analysis, the Data Scientist needs to communicate results and recommendations to stakeholders by translating technical framework to business-oriented insights. This role requires an individual with excellent analytical abilities as well as business acumen. The successful candidate will be comfortable with ambiguity, with attention to detail, an ability to balance analysis with critical thinking and judgement, and work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had. Key job responsibilities - Collaborate with product managers and deep learning science and engineering teams to design and implement model solutions for Amazon buying systems - Develop edge case agile models for on-going buying assessments toward the end goal of optimizing buying decisions for millions of products world-wide - Use large datasets or experiments to make causal inferences or predictions - Work with engineers to automate science analysis processes and build scalable measurement solutions - Interpret data, write reports, and make actionable recommendations - Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. The candidate will need to be able to extract insights from data and be able to clearly communicate appropriate triggers and actions - Drive technical standards and best practices for the team's data architecture and analytics approaches - Mentor and provide technical guidance to other team members on complex projects A day in the life You might start your day working with a teammate to optimize a complex metric attribution logic. You could then collaborate with a Senior SDE to design the model architecture that enables our Gen AI tools for understanding the buying decisions. Later, you could lead a model backtesting and lab design review for a new cross-program framework and present analysis on a strategic business decision to senior leadership. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team You'll join a dynamic team of Data Scientists, Production Managers, SDEs, and BIEs within SCOT Buying Outcomes, focusing on data-driven decisions that impact Amazon's global supply chain. Our team brings together simulation and analytics across multiple buying programs, creating exciting opportunities to reshape our next generation of buying tools. We're passionate about making our models and data accessible and actionable, whether it's through self-service tools or deep-dive analyses. We value collaboration, innovation, and the ability to translate complex technical concepts into business impact.

Amazon's advertising business has grown exponentially over the past years, helping connect sellers and vendors to shoppers who may be interested in their products. Our ad products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products that leverage state of the art AI technologies. The Sponsored Products and Brands team is seeking a Principal Applied Scientist to lead the development and implementation of generative AI solutions for ad allocation and ranking on Amazon search pages. This role will be instrumental in revolutionizing how we match ads with customer intent and shopping behavior. Key job responsibilities * Design and develop novel generative AI architectures for real-time ad allocation, focusing on both efficiency and effectiveness at massive scale * Lead research initiatives in applying large language models and multimodal AI to understand deep semantic relationships between ads, queries, and user behavior * Create innovative approaches to leverage GenAI for dynamic ad placement optimization while maintaining strict latency requirements * Collaborate with cross-functional teams to integrate GenAI solutions into existing advertising systems * Author research papers and technical documentation, contributing to the broader scientific community