Careers

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist. You will develop and implement state-of-the-art algorithms and models for advanced information retrieval, and tune LLM-based prompting to optimize Retrieval Augmented Generation (RAG) for customer experiences. As a Senior Applied Scientist, you will play a critical role developing Amazon's foundational Generative AI (Gen AI) technologies that serve our global customers. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports

Are you a MS or PhD student interested in a 2025 Internship in the field of machine learning, deep learning, speech, robotics, computer vision, optimization, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! As a Data Scientist on this team you will: - Lead Data Science solutions from beginning to end. - Deliver with independence on challenging large-scale problems with complexity and ambiguity. - Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data. - Build Machine Learning and statistical models to solve specific business problems. - Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance. - Analyze historical data to identify trends and support optimal decision making. - Apply statistical and machine learning knowledge to specific business problems and data. - Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed. - Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes. - Build decision-making models and propose effective solutions for the business problems you define. - Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication. Why you will love this opportunity: Amazon has invested heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video ~ https://youtu.be/zD_6Lzw8raE

Do you want to lead the Ads industry and redefine how we measure the effectiveness of the WW Amazon Ads business? Are you passionate about causal inference, Deep Learning/DNN, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation? If so, come join Amazon Ads to be an Applied Science leader within our Advertising Incrementality Measurement science team! Key job responsibilities As an Applied Science leader within the Advertising Incrementality Measurement (AIM) science team, you are responsible for defining and executing on key workstreams within our overall causal measurement science vision. In particular, you will lead the science development of our Deep Neural Net (DNN) ML model, a foundational ML model to understand the impact of individual ad touchpoints for billions of daily ad touchpoints. You will work on a team of Applied Scientists, Economists, and Data Scientists to work backwards from customer needs and translate product ideas into concrete science deliverables. You will be a thought leader for inventing scalable causal measurement solutions that support highly accurate and actionable causal insights--from defining and executing hundreds of thousands of RCTs, to developing an exciting science R&D agenda. You will solve hard problems, advance science at Amazon, and be a leading innovator in the causal measurement of advertising effectiveness. In this role, you will work with a team of applied scientists, economists, engineers, product managers, and UX designers to define and build the future of advertising causal measurement. You will be working with massive data, a dedicated engineering team, and industry-leading partner scientists. Your team’s work will help shape the future of Amazon Advertising.

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities • Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate cutting-edge generative AI solutions to address real-world challenges • Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production • Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder • Provide customer and market feedback to product and engineering teams to help define product direction A day in the life Here at AWS, 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 (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. About the team Diverse Experiences Amazon 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 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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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.

The Builder Studio team is looking for a talented Senior Applied Scientist with expertise in Large Language Models (LLMs) and multimodal AI systems. You will develop algorithms and techniques to address our core challenges around data quality, AI agent orchestration with appropriate guardrails, and optimizing resource-intensive AI workloads across infrastructure stacks. Key job responsibilities As a Senior Applied Scientist, you will research and develop AI techniques to enhance knowledge retrieval, visualization, and representation. You will design systems that reduce errors in AI outputs and build frameworks to evaluate model performance. The role involves creating methods for efficient AI deployment across infrastructure stacks, developing agent orchestration mechanisms with appropriate guardrails, and implementing resource optimization algorithms for complex AI workloads. You will collaborate with engineering teams to transition research innovations into production systems that deliver real impact. About the team The Builder Studio team is building a next-generation platform that combines advanced knowledge retrieval with AI orchestration to improve developer workflows. Our team is tackling three key challenges: establishing data quality baselines and metrics, orchestrating and managing interactions with required guardrails between specialized AI agents deployed across different stacks of the infrastructure, and maintaining hosting and scaling demands of resource-intensive AI workloads and their associated computational needs. We bring together specialists in machine learning, distributed systems, and developer experience to build scalable solutions that make AI more accessible, reliable, and useful for builders across the organization. We focus on transforming research techniques into robust, production-ready systems that deliver measurable impact.

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX Science team is building an AI-powered conversational assistant to transform the Selling Partner experience. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the cutting edge of Generative AI, going beyond a typical chatbot to provide a powerful, personalized experience to sellers running real businesses, large and small. Do you want to join an innovative team of scientists, engineers, product and program managers who use state-of-the-art Generative AI and Machine Learning technologies to help Amazon create a delightful Selling Partner experience? Do you want to build solutions to real business problems by automatically understanding and addressing sellers’ challenges, needs and opportunities? Are you excited by the prospect of contributing to one of Amazon’s most strategic Generative AI initiatives? If yes, then you may be a great fit to join the Selling Partner Experience Science team (SPeXSci). Key job responsibilities - Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Selling Partner Experience Science (SPeXSci) is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We are focused on building seller facing AI-powered tools using the latest science advancements to empower sellers to drive the growth of their business. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.

The Seller Fees organization drives the monetization infrastructure powering Amazon's global marketplace, processing billions of transactions for over two million active third-party sellers worldwide. Our team owns the complete technical stack and strategic vision for fee computation systems, leveraging advanced machine learning to optimize seller experiences and maintain fee integrity at unprecedented scale. We're seeking an exceptional Applied Scientist to push the boundaries of large-scale ML systems in a business-critical domain. This role presents unique opportunities to • Architect and deploy state-of-the-art transformer-based models for fee classification and anomaly detection across hundreds of millions of products • Pioneer novel applications of multimodal LLMs to analyze product attributes, images, and seller metadata for intelligent fee determination • Build production-scale generative AI systems for fee integrity and seller communications • Advance the field of ML through novel research in high-stakes, large-scale transaction processing • Develop SOTA causal inference frameworks integrated with deep learning to understand fee impacts and optimize seller outcomes • Collaborate with world-class scientists and engineers to solve complex problems at the intersection of deep learning, economics, and large business systems. If you're passionate about advancing the state-of-the-art in applied ML/AI while tackling challenging problems at global scale, we want you on our team! Key job responsibilities Responsibilities: . Design measurable and scalable science solutions that can be adopted across stores worldwide with different languages, policy and requirements. · Integrate AI (both generative and symbolic) into compound agentic workflows to transform complex business systems into intelligent ones for both internal and external customers. · Develop large scale classification and prediction models using the rich features of text, image and customer interactions and state-of-the-art techniques. · Research and implement novel machine learning, statistical and econometrics approaches. · Write high quality code and implement scalable models within the production systems. · Stay up to date with relevant scientific publications. · Collaborate with business and software teams both within and outside of the fees organization.

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX Science team is building an AI-powered conversational assistant to transform the Selling Partner experience. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the state-of-the-art Generative AI, going beyond a typical chatbot to provide a personalized experience to sellers running real businesses, large and small. Do you want to join an innovative team of scientists, engineers, product and program managers who use the latest Generative AI and Machine Learning technologies to help Amazon create a delightful Selling Partner experience? Do you want to build solutions to real business problems by automatically understanding and addressing sellers’ challenges, needs and opportunities? Are you excited by the prospect of contributing to one of Amazon’s most strategic Generative AI initiatives? If yes, then you may be a great fit to join the Selling Partner Experience Science team. Key job responsibilities - Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Selling Partner Experience Science is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We are focused on building seller facing AI-powered tools using the latest science advancements to empower sellers to drive the growth of their business. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX Science team is building an AI-powered conversational assistant to transform the Selling Partner experience. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the state-of-the-art Generative AI, going beyond a typical chatbot to provide a personalized experience to sellers running real businesses, large and small. Do you want to join an innovative team of scientists, engineers, product and program managers who use the latest Generative AI and Machine Learning technologies to help Amazon create a delightful Selling Partner experience? Do you want to build solutions to real business problems by automatically understanding and addressing sellers’ challenges, needs and opportunities? Are you excited by the prospect of contributing to one of Amazon’s most strategic Generative AI initiatives? If yes, then you may be a great fit to join the Selling Partner Experience Science team. Key job responsibilities - Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Selling Partner Experience Science is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We are focused on building seller facing AI-powered tools using the latest science advancements to empower sellers to drive the growth of their business. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.