Careers

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.

The Camera and Sensors team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with computer vision and multimodal perception models for various Amazon devices. Key job responsibilities As an Applied Scientist with the Camera and Sensors team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal models with an emphasis on computer vision. Your work will directly impact our customers in the form of products and services that make use of Computer Vision technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances for Amazon devices. A day in the life An Applied Scientist with the Camera and Sensors team you will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. About the team You will work with a team of applied scientists and software engineers locally in Cambridge, along with a broader team of principle scientists, applied scientists and software engineers across multiple global teams in the devices group.

Interested in building something new? Join the Amazon Autos team on an exhilarating journey to redefine the vehicle shopping experience. This is an opportunity to be part of the Amazon's new business ventures. Our goal is to create innovative automotive discovery and shopping experiences on Amazon, providing customers with greater convenience and a wider selection. You'll work in a creative, fast-paced, and entrepreneurial environment at the center of Amazon's innovation. As a key member, you'll play a pivotal role in helping us achieve our mission. We are looking for a highly accomplished Data Science professional to lead our data science strategy, foster a culture of data-driven decision-making, and drive impactful business outcomes through advanced analytics and state-of-the-art data science methodologies. If you are passionate about innovation, delivering exceptional customer experiences, and thrive in tackling new challenges, this role is for you. We seek someone with expertise in Statistical Analysis, Machine Learning, and Data Mining, with a proven ability to analyze large, complex, and diverse datasets. If you're motivated to grow professionally as a Data Scientist, you could be the ideal candidate for this opportunity Join us on this exhilarating journey and be part of redefining the vehicle shopping experience on Amazon. Key job responsibilities As a Data Scientist in Amazon Autos, you will: * Develop and implement the data science strategy for Amazon Autos, ensuring it aligns with both program goals and broader business objectives. * Leverage your skills in areas such as statistical analysis, deep learning, machine learning, and reinforcement learning to drive innovation and enhance the automotive shopping experience. * Effectively analyze large, complex, and diverse datasets collected from diverse sources to derive key insights, build segmentation models and improve customer shopping experience. * Utilize your Generative AI, time series and predictive modeling skills, and creative problem-solving skills to drive new projects from ideation to implementation. * Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. * Design, develop, and evaluate innovative ML models to solve diverse obstacles and opportunities across business teams. * Interface with business customers, gathering requirements and delivering science solutions. * Effectively communicate complicated machine learning concepts to multiple partners. A day in the life In this role, you will be part of a multidisciplinary team working on one of Amazon's newest business ventures. As a key member, you will collaborate closely with engineering, product, design, operations, and business development to bring innovative solutions to our customers. Your science expertise will be leveraged to research and deliver data-driven solutions to existing problems, explore emerging problem spaces, and create new knowledge. You will report updates and insights from your work to leadership and invent and apply state-of-the-art technologies, such as large language models, machine learning, natural language processing, and computer vision, to build next-generation solutions for Amazon. You'll publish papers, file patents, and work closely with engineers to bring your ideas to production. About the team This is a critical role for a newly formed team with a vision to create innovative automotive discovery and shopping experiences on Amazon, providing customers better convenience and more selection. We’re collaborating with other experienced teams at Amazon to define the future of how customers research and shop for cars online.

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.

At Amazon's Selection Monitoring team, we leverage advanced AI technologies, including the latest Large Language Models (LLMs) and Generative AI (GenAI), to enrich and expand Amazon's brand selection in alignment with consumers’ interests. Our mission is to establish the world's most comprehensive, accurate, and up-to-date universal brand catalog, setting new standards in brand discovery and coverage. We're seeking innovative Applied Scientists passionate about leveraging advanced AI to tackle complex challenges in brand intelligence, data integration, and knowledge discovery. In this role, you'll collaborate with teams across Amazon to drive customer-focused solutions and amplify the impact of your work on our global customer base. Key job responsibilities - Design and implement advanced AI models using the latest LLM and GenAI technologies to enhance brand understanding, matching, and categorization at an unprecedented scale. - Develop novel approaches to extract, generate, and validate brand attributes and relationships using multimodal AI, combining text, image, and structured data analysis. - Create intelligent systems that can automatically generate high-quality brand descriptions, features, and specifications using GenAI techniques. - Implement advanced natural language processing and computer vision models to extract insights from diverse data sources, including web content, user-generated data, and product imagery. - Develop innovative solutions for entity resolution, knowledge graph construction, and semantic reasoning to build a comprehensive understanding of the global brand landscape. - Collaborate with cross-functional teams to integrate AI-driven insights into Amazon's brand selection strategies and decision-making processes. - Lead the design and implementation of scalable, production-ready AI systems that can process millions of brands efficiently on Amazon Web Services (AWS). - Stay at the advance of AI research, continuously exploring and implementing new techniques in LLMs, GenAI, and multimodal learning to drive innovation in brand intelligence. - Contribute to the scientific community through publications, presentations, and collaborations with academic institutions.

Amazon is looking for world class scientists and engineers to join its AWS AI Labs working within natural language processing. This group is entrusted with developing core data mining, natural language processing, and machine learning solutions for AWS services. At AWS AI Labs you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually large scale natural language processing solutions. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. About the team AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Diverse Experiences AWS 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 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 & 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 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 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 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.