Careers

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. The Amazon Web Services Professional Services (ProServe) team seeks an experienced Principal Data Scientist to join our ProServe Shared Delivery Team (SDT). In this role, you will serve as a technical leader and strategic advisor to AWS enterprise customers, partners, and internal AWS teams on transformative AI/ML projects. You will leverage your deep technical expertise to architect and implement innovative machine learning and generative AI solutions that drive significant business outcomes. As a Principal Data Scientist, you will lead complex, high-impact AI/ML initiatives across multiple customer engagements. You will collaborate with Director and C-level executives to translate business challenges into technical solutions. You will drive innovation through thought leadership, establish technical standards, and develop reusable solution frameworks that accelerate customer adoption of AWS AI/ML services. Your work will directly influence the strategic direction of AWS Professional Services AI/ML offerings and delivery approaches. Your extensive experience in designing and implementing sophisticated AI/ML solutions will enable you to tackle the most challenging customer problems. You will provide technical mentorship to other data scientists, establish best practices, and represent AWS as a subject matter expert in customer-facing engagements. You will build trusted advisor relationships with customers and partners, helping them achieve their business outcomes through innovative applications of AWS AI/ML services. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. Key job responsibilities Architecting and implementing complex, enterprise-scale AI/ML solutions that solve critical customer business challenges Providing technical leadership across multiple customer engagements, establishing best practices and driving innovation Collaborating with Delivery Consultants, Engagement Managers, Account Executives, and Cloud Architects to design and deploy AI/ML solutions Developing reusable solution frameworks, reference architectures, and technical assets that accelerate customer adoption of AWS AI/ML services Representing AWS as a subject matter expert in customer-facing engagements, including executive briefings and technical workshops Identifying and driving new business opportunities through technical innovation and thought leadership Mentoring junior data scientists and contributing to the growth of AI/ML capabilities within AWS Professional Services

Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that safeguard Amazon's customers and legitimate sellers while ensuring a fair and trusted shopping experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions? If yes, we invite you to join the Amazon Risk Intelligence Science Team. We're seeking an exceptional scientist who can revolutionize how we protect our marketplace through intelligent automation. As a key member of our team, you'll develop and deploy state-of-the-art machine learning systems that analyze millions of seller interactions daily, ensuring the integrity and trustworthiness of Amazon's marketplace while scaling our operations to new heights. Your work will directly impact the safety and security of the shopping experience for hundreds of millions of customers worldwide, while supporting the growth of honest entrepreneurs and businesses. Key job responsibilities • Use machine learning and statistical techniques to create scalable abuse detection solutions that identify fraudulent seller behavior, identity change, and marketplace manipulation schemes • Innovate with the latest GenAI technology to build highly automated solutions for efficient seller verification, transaction monitoring, and risk assessment • Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to prevent and detect sophisticated abuse patterns across the marketplace • Learn, explore and experiment with the latest machine learning advancements to protect customer trust and maintain marketplace integrity while supporting legitimate selling partners • Collaborate with cross-functional teams to develop comprehensive risk models that can adapt to evolving abuse patterns and emerging threats About the team You'll be working closely with business partners, science and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. The Amazon Web Services Professional Services (ProServe) team seeks an experienced Principal Data Scientist to join our ProServe Shared Delivery Team (SDT). In this role, you will serve as a technical leader and strategic advisor to AWS enterprise customers, partners, and internal AWS teams on transformative AI/ML projects. You will leverage your deep technical expertise to architect and implement innovative machine learning and generative AI solutions that drive significant business outcomes. As a Principal Data Scientist, you will lead complex, high-impact AI/ML initiatives across multiple customer engagements. You will collaborate with Director and C-level executives to translate business challenges into technical solutions. You will drive innovation through thought leadership, establish technical standards, and develop reusable solution frameworks that accelerate customer adoption of AWS AI/ML services. Your work will directly influence the strategic direction of AWS Professional Services AI/ML offerings and delivery approaches. Your extensive experience in designing and implementing sophisticated AI/ML solutions will enable you to tackle the most challenging customer problems. You will provide technical mentorship to other data scientists, establish best practices, and represent AWS as a subject matter expert in customer-facing engagements. You will build trusted advisor relationships with customers and partners, helping them achieve their business outcomes through innovative applications of AWS AI/ML services. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. Key job responsibilities Architecting and implementing complex, enterprise-scale AI/ML solutions that solve critical customer business challenges Providing technical leadership across multiple customer engagements, establishing best practices and driving innovation Collaborating with Delivery Consultants, Engagement Managers, Account Executives, and Cloud Architects to design and deploy AI/ML solutions Developing reusable solution frameworks, reference architectures, and technical assets that accelerate customer adoption of AWS AI/ML services Representing AWS as a subject matter expert in customer-facing engagements, including executive briefings and technical workshops Identifying and driving new business opportunities through technical innovation and thought leadership Mentoring junior data scientists and contributing to the growth of AI/ML capabilities within AWS Professional Services

Customer Experience and Business Trends (CXBT) is looking for an Applied Scientist to join their team. CXBT's mission is to create best-in-class AI agents that seamlessly integrate multimodal inputs like speech, images, and video, enabling natural, empathetic, and adaptive interactions. We leverage advanced architectures, cross-modal learning, interpretability, and responsible AI techniques to provide coherent, context-aware responses augmented by real-time knowledge retrieval. The ideal candidate will have expertise in Large Language Models (LLMs), speech, audio, Natural Language processing (NLP) or multimodal learning to pioneer innovations in data simulation, representation, generation, reasoning, retrieval, and evaluation. Key job responsibilities - Build scalable solutions for real-time conversational experiences, including multilingual support, customizable personalities, and conversational turn-taking. - Develop data simulation approaches that mimic real-world speech interactions. - Research and implement novel algorithms and modeling techniques. - Acquire and curate diverse datasets while ensuring user privacy. - Create robust evaluation metrics and test sets to assess language model performance. - Integrate human feedback to improve data selection and model performance. - Innovate in data representation and model training techniques. - Apply responsible AI practices throughout the development process. A day in the life Our team is dedicated to improving Amazon's products and services through evaluation of the end-to-end customer experience using both internal and external processes and technology. Our mission is to deeply understand our customers' experiences, challenge the status quo, and provide insights that drive innovation to improve that experience. Through our analysis and insights, we inform business decisions that directly impact customer experience as customers of new GenAI and LLM technologies. About the team Customer Experience and Business Trends (CXBT) is an organization made up of a diverse suite of functions dedicated to deeply understanding and improving customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings – for almost every business at Amazon – for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers). Our approach is based on determining the customer need, along with problem solving, and we work backwards from there. We use technical and non-technical approaches and stay aware of industry and business trends. We are a global team, made up of a diverse set of profiles, skills, and backgrounds – including: Product Managers, Software Developers, Computer Vision experts, Solutions Architects, Data Scientists, Business Intelligence Engineers, Business Analysts, Risk Managers, and more.

Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.

Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. 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! The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (audio, images, videos, text) by building AI-driven solutions for advertisers. To accomplish this, we are investing in understanding how best users can leverage Generative AI methods such as latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related. As an Applied Scientist you will be part of a close-knit team of other applied scientists and product managers, UX and engineers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who are adept at a variety of skills, especially at the development and use of multi-modal Generative AI and can use state-of-the-art generative music and audio, computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring SOTA research to raise the bar within the team. As an Applied Scientist on this team, you will: - Drive the invention and development of novel multi-modal agentic architectures and models for the use of Generative AI methods in advertising. - Work closely and integrate end-to-end proof-of-concept Machine Learning projects that have a high degree of ambiguity, scale and complexity. - Build interface-oriented systems that use Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Curate relevant multi-modal datasets. - Perform hands-on analysis and modeling of experiments with human-in-the-loop that eg increase traffic monetization and merchandise sales, without compromising the shopper experience. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Mentor and help recruit Applied Scientists to the team. - Present results and explain methods to senior leadership. - Willingness to publish research at internal and external top scientific venues. - Write and pursue IP submissions. Key job responsibilities This role is focused on developing new multi-modal Generative AI methods to augment generative imagery and videos. You will develop new multi-modal paradigms, models, datasets and agentic architectures that will be at the core of advertising-facing tools that we are launching. You may also work on development of ML and GenAI models suitable for advertising. You will conduct literature reviews to stay on the SOTA of the field. You will regularly engage with product managers, UX designers and engineers who will partner with you to productize your work. For reference see our products: Enhanced Video Generator, Creative Agent and Creative Studio. A day in the life On a day-to-day basis, you will be doing your independent research and work to develop models, you will participate in sprint planning, collaborative sessions with your peers, and demo new models and share results with peers, other partner teams and leadership. About the team The team is a dynamic team of applied scientists, UX researchers, engineers and product leaders. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads. We are open to hiring candidates to work out of one of the following locations: UK (London), USA (Seattle).

Are you interested in working in the exciting space of Generative Artificial Intelligence (GenAI) to build Agents that will test Amazon product experience and inform how teams across Amazon think about designing world-class products? Amazon is looking for an experienced, talented, and highly motivated Research Scientist to join our Customer Experience and Business Trends (CXBT) team. The right candidate has an unrelenting tenacity to drive business impact, strong communication skills, ability to influence through data, and is capable of breaking down and solving complex and ambiguous problems. As a Research Scientist, you have expertise in research design best practices and identifying the appropriate research methodology based on the defined business objectives. You are a self-starter who thrives in ambiguity and can creatively solve problems. You have excellent business judgment and operate with a strong sense of urgency and commitment. You will have the ability to work with and influence businesses in a global setting and drive strategic change across Amazon. You will be responsible for delivering innovative GenAI products utilizing Agents, and developing and launching novel ways to create datasets that will monitor Amazon's performance across multiple modalities (e.g., speech, text, image, video, audio) based on Amazon's breadth of product offerings. You will work closely with product managers and engineers to develop new methodologies utilizing GenAI technologies and Natural Language Processing (NLP). We are looking for a passionate, talented, and inventive Sr. Research Scientist with a background in Machine Learning (ML) and Large Language Models (LLMs) to help build industry-leading GenAI Agent and Data Generation technology. Key job responsibilities - Work with talented peers to develop novel algorithms and modeling techniques to drive the state of the art in speech synthesis. - Participate in the design, development, evaluation, deployment and updating of data-driven models for GenAI agents and data set generation applications. - Participate in research activities including the application and evaluation of Agent techniques for novel applications. - Research and implement novel ML and statistical approaches to add value to the business. - Mentor junior engineers and scientists. - Build strategic relationships with stakeholders at multiple levels of the organization. - Partner with team members including engineering, product managers, data science, and business intelligence engineers to inform solution design and ensure study success. - Contribute to a team culture of experimentation and innovation. About the team Customer Experience and Business Trends (CXBT) is an organization made up of a diverse suite of functions dedicated to deeply understanding and improving customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings - for almost every business at Amazon – for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers). Our approach is based on determining the customer need, along with problem solving, and we work backwards from there. We use technical and non-technical approaches and stay aware of industry and business trends. We are a global team, made up of a diverse set of profiles, skills, and backgrounds - including: Product Managers, Software Developers, Computer Vision experts, Solutions Architects, Data Scientists, Business Intelligence Engineers, Business Analysts, Risk Managers, and more.

The Amazon Fulfillment Technologies (AFT) Science team is seeking an exceptional Applied Scientist with strong operations research and optimization expertise to develop production solutions for one of the most complex systems in the world: Amazon's Fulfillment Network. At AFT Science, we design, build, and deploy optimization, statistics, machine learning, and GenAI/LLM solutions that power production systems running across Amazon Fulfillment Centers worldwide. We tackle a wide range of challenges throughout the network, including labor planning and staffing, pick scheduling, stow guidance, and capacity risk management. Our mission is to develop innovative, scalable, and reliable science-driven production solutions that exceed the published state of the art, enabling systems to run optimally and continuously (from every few minutes to every few hours) across our large-scale network. Key job responsibilities As an Applied Scientist, you will collaborate with scientists, software engineers, product managers, and operations leaders to develop optimization-driven solutions that directly impact process efficiency and associate experience in the fulfillment network. Your key responsibilities include: - Develop deep understanding and domain knowledge of operational processes, system architecture, and business requirements - Dive deep into data and code to identify opportunities for continuous improvement and disruptive new approaches - Design and develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and emerging challenges - Create prototypes and simulations for agile experimentation of proposed solutions - Advocate for technical solutions with business stakeholders, engineering teams, and senior leadership - Partner with software engineers to integrate prototypes into production systems - Design and execute experiments to test new or incremental solutions launched in production - Build and monitor metrics to track solution performance and business impact About the team Amazon Fulfillment Technology (AFT) designs, develops, and operates end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FCs). We harmonize the physical and virtual worlds so Amazon customers can get what they want, when they want it. The AFT Science team brings expertise in operations research, optimization, statistics, machine learning, and GenAI/LLM, combined with deep domain knowledge of operational processes within FCs and their unique challenges. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment, which includes both developing novel solutions and improving existing approaches. Our production systems rely on a diverse set of technologies, and our teams invest in multiple specialties as the needs of each focus area evolve.

Have you ever wondered what it takes to transform millions of manual network planning decisions into AI-powered precision? Network Planning Solutions is looking for scientific innovators obsessed with building the AI/ML intelligence that makes orchestrating complex global operations feel effortless. Here, you'll do more than just build models; you'll create 'delight' by discovering and deploying the science that delivers exactly what our customers need, right when they need it. If you're ready to transform complex data patterns into breakthrough AI capabilities that power intuitive human experiences, you've found your team. Network Planning Solutions architects and orchestrates Amazon's customer service network of the future. By building AI-native solutions that continuously learn, predict and optimize, we deliver seamless customer experiences and empower associates with high-value work—driving measurable business impact at a global scale. As a Sr. Manager, Applied Science, you will own the scientific innovation and research initiatives that make this vision possible. You will lead a team of applied scientists and collaborate with cross-functional partners to develop and implement breakthrough scientific solutions that redefine our global network. Key job responsibilities Lead AI/ML Innovation for Network Planning Solutions: - Develop and deploy production-ready demand forecasting algorithms that continuously sense and predict customer demand using real-time signals - Build network optimization algorithms that automatically adjust staffing as conditions evolve across the service network - Architect scalable AI/ML infrastructure supporting automated forecasting and network optimization capabilities across the system Drive Scientific Excellence: - Build and mentor a team of applied scientists to deliver breakthrough AI/ML solutions - Design rigorous experiments to validate hypotheses and quantify business impact - Establish scientific excellence mechanisms including evaluation metrics and peer review processes Enable Strategic Transformation: - Drive scientific innovation from research to production - Design and validate next-generation AI-native models while ensuring robust performance, explainability, and seamless integration with existing systems. - Partner with Engineering, Product, and Operations teams to translate AI/ML capabilities into measurable business outcomes - Navigate ambiguity through experimentation while balancing innovation with operational constraints - Influence senior leadership through scientific rigor, translating complex algorithms into clear business value A day in the life Your day will be a dynamic blend of scientific innovation and strategic problem-solving. You'll collaborate with cross-functional teams, design AI algorithms, and translate complex data patterns into intuitive solutions that drive meaningful business impact. About the team We are Network Planning Solutions, a team of scientific innovators dedicated to reshaping how global service networks operate. Our mission is to create AI-native solutions that continuously learn, predict, and optimize customer experiences. We empower our associates to tackle high-value challenges and drive transformative change at a global scale.

Sponsored Products and Brands (SPB) is at the heart of Amazon Advertising, helping millions of advertisers—from small businesses to global brands—connect with customers at the moments that matter most. Our advertising solutions enable sellers, vendors, and brand owners to grow their businesses by reaching shoppers with relevant, engaging ads across Amazon's store and beyond. We're obsessed with delivering measurable results for advertisers while creating a delightful shopping experience for customers. Are you interested in defining the science behind the future of advertising? Sponsored Products and Brands science teams are pioneering breakthrough agentic AI systems—pushing the boundaries of large language models, autonomous reasoning, planning, and decision-making to build intelligent agents that fundamentally transform how advertisers succeed on Amazon. As an SPB applied science leader, you'll have end-to-end ownership of the product and scientific vision, research agenda, model architectures, and evaluation frameworks required to deliver state-of-the-art agentic AI solutions for our advertising customers. You'll get to work on problems that are fast-paced, scientifically rich, and deeply consequential. You'll also be able to explore novel research directions, take bold bets, and collaborate with remarkable scientists, engineers, and product leaders. We'll look for you to bring your diverse perspectives, deep technical expertise, and scientific rigor to make Amazon Advertising even better for our advertisers and customers. With global opportunities for talented scientists and science leaders, you can decide where a career in Amazon Ads Science takes you! We are kicking off a new initiative within SPB to leverage agentic AI solutions to revolutionize how advertisers create, manage, and optimize their advertising campaigns. This is a unique opportunity to lead a business-critical applied science initiative from its inception—defining the scientific charter, establishing foundational research pillars, and building a multi-year science roadmap for transformative impact. As the single-threaded applied science leader, you will build and guide a dedicated team of applied scientists, research scientists, and machine learning engineers, working closely with cross-functional engineering and product partners, to research, develop, and deploy agentic AI systems that fundamentally reimagine the advertiser journey. Your charter will begin with advancing the science behind intelligent agents that simplify campaign creation, automate optimization decisions through autonomous reasoning and planning, and deliver personalized advertising strategies at scale. You will pioneer novel approaches in areas such as LLM-based agent architectures, multi-step planning and tool use, retrieval-augmented generation, reinforcement learning from human and business feedback, and robust evaluation methodologies for agentic systems. You will expand to proactively identify and tackle the next generation of AI-powered advertising experiences across the entire SPB portfolio. This high-visibility role places you as the science leader driving our strategy to democratize advertising success—making it effortless for advertisers of all sizes to achieve their business goals while delivering relevant experiences for Amazon customers. Key job responsibilities Build, mentor, and lead a new, high-performing applied science organization of applied scientists, research scientists, and engineers, fostering a culture of scientific excellence, innovation, customer obsession, and ownership. Define, own, and drive the long-term scientific and product vision and research strategy for agentic AI-powered advertising experiences across Sponsored Products and Brands—identifying the highest-impact research problems and charting a path from exploration to production. Lead the research, design, and development of novel agentic AI models and systems—including LLM-based agent architectures, multi-agent orchestration, planning and reasoning frameworks, tool-use mechanisms, and retrieval-augmented generation pipelines—that deliver measurable value for advertisers and create delightful, intuitive experiences. Establish rigorous scientific methodology and evaluation frameworks for assessing agent performance, reliability, safety, and advertiser outcomes, setting a high bar for experimentation, reproducibility, and offline-to-online consistency. Partner closely with senior business, engineering, and product leaders across Amazon Advertising to translate advertiser pain points and business opportunities into well-defined science problems, and deliver cohesive, production-ready solutions that drive advertiser success. Drive execution from research to production at scale, ensuring models and agentic systems meet high standards for quality, robustness, latency, safety, and reliability for mission-critical advertising services operating at Amazon scale. Champion a culture of scientific inquiry and technical depth that encourages bold experimentation, publication of novel research, relentless simplification, and continuous improvement. Communicate your team's scientific vision, research breakthroughs, strategy, and progress to senior leadership and key stakeholders, ensuring alignment with broader Amazon Advertising objectives and contributing to Amazon's position at the forefront of applied AI. Develop a science roadmap directly tied to advertiser outcomes, revenue growth, and business plans, delivering on commitments for high-impact research and modeling initiatives that shape the future of AI-powered digital advertising.