Careers

We are seeking a passionate, talented, and inventive scientist to join the Amazon AGI team. As an Applied Scientist, you'll be at the forefront of developing intelligent systems that can seamlessly process, understand, and retrieve multimodal information. You'll work on advancing the state-of-the-art in vision-language models and multimodal embeddings, while developing efficient and scalable algorithms for cross-modal retrieval. Your role will involve creating innovative solutions for multimodal ranking and relevance, ultimately building the next generation of multimodal search systems that can understand and process information the way humans do. You'll collaborate with a talented team of researchers and engineers, contribute to research in multimodal search, and see your innovations directly impact millions of customers. If you're passionate about multimodal search and want to shape the future of how machines understand and retrieve information across different modalities, we want to hear from you. Our team values research excellence and encourages publishing in top-tier conferences while maintaining a strong focus on practical applications that benefit real users. Key job responsibilities - As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful search experiences. - Develop state-of-the-art multimodal search technology, including training novel retrieval and ranking models for images/videos, scaling models and optimizing performance, partnering with engineering to deploy and debug model performance in production, and building and scaling quality training data sets. - Leverage Amazon's data and computing resources to accelerate advances in the state of the art in multimodal learning and information retrieval. - Work backwards from customer needs and use that information to make trade-offs between different modeling approaches - Collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems - Report results to technical and business audiences in a manner that is statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment - Drive best practices, helping to set high scientific and engineering standards on the team - Promote the culture of experimentation and applied science at Amazon

The Perfect Order Experience (POE) AI team combines artificial intelligence, machine learning, and economic insights to ensure exceptional customer experiences and seller success on Amazon. We develop advanced scientific solutions that protect product authenticity, maintain quality standards, and safeguard intellectual property across Amazon's vast catalog. Our work spans from building detection systems using state-of-the-art Large Language Models to creating automated investigation processes and risk treatment mechanisms. Our solutions directly impact billions of customer interactions and enable millions of sellers to thrive while maintaining the highest standards of trust and quality. We are seeking an exceptional Senior Applied Science Manager to lead key AI initiatives to ensure a perfect order experience for Amazon customers. In this role, you will spearhead the development of a domain specific large language model designed to comprehend complex seller behaviors and relationships. You will lead the research and implementation on LLM pre-training, fine-tuning and reinforcement learning for LLM reasoning. You will implement and influence ranker models that intelligently adjust product visibility based on risk signals and trust metrics. Key job responsibilities - Drive AI strategy and lead a team of applied scientists in developing ML solutions. - Lead the end-to-end development of a domain specific LLM. - Drive the development of large-scale pre-training and post-training strategies for the LLM using domain-specific datasets. - Architect automated risk detection and treatment systems that combine multi-modal signals to identify product quality issues and implement optimization-based mitigation strategies. - Collaborate with other science teams to develop/ influence ranker models that optimize product visibility.

Project Kuiper is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. We are looking for an experienced Data Scientist to help architect state-of-the-art test infrastructure and lead the development of data models and analysis tools to represent the ground truth about satellite test results in order to facilitate important business decisions. Our team is responsible for core infrastructure and tools that will serve as the backbone of automated satellite testing operations to enable rapid scaling of manufacturing processes. Key job responsibilities - Work with engineering, software and manufacturing teams to understand drivers, impacts, and key influences on satellite performance - Lead the design, build and implementation of production models and make decisions in real time for satellite test results - Drive actions at scale to optimize test methodology and drive increases to satellite reliability - Analysis and modeling of satellite telemetry from test results in lab and on-orbit - Develop models and data pipelines for satellite telemetry - Create and manage datasets for continued pre-training and supervised fine-tuning of LLMs - Develop scalable visualizations for analysis of satellite performance A day in the life As a Project Kuiper Data Scientist you will own the architecture definition and development of data analysis tools to to aid engineering and production teams in deciding flight-worthiness of each Kuiper satellite and historical traceability tools to enable simplified discovery and interpretation of past test data. You will work with multiple engineering, software and manufacturing teams across ground and space systems, to specify requirements, define data collection, interpretation strategies, data pipelines and implement data analysis and reporting tools for Integrated Vehicle tests. Your focus will be in optimizing the analysis of test results to enable Project Kuiper production plans. About the team The Automated Vehicle Testing Team is responsible for core infrastructure and tools that will serve as the backbone of automated satellite testing operations to enable rapid scaling of manufacturing processes.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to build Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will work with talented peers to lead the development of GenAI algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in GenAI. About the team The AGI team has a mission to push the envelope with GenAI in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

The Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians on a mission to develop a fault-tolerant quantum computer. You will be joining a team located in Pasadena, CA that conducts materials research to improve the performance of superconducting quantum processors. We seek a Quantum Research Scientist to investigate how material defects affect qubit performance. In this role, you will combine expertise in numerical simulations and materials characterization to study materials loss mechanisms such as two-level systems, quasiparticles, vortices, etc. Key job responsibilities Provide subject matter expertise on integrated experimental and computational studies of materials defects Develop and use computational tools for large-scale simulations of disordered structures Develop and implement multi-technique materials characterization workflows for thin films and devices, with a focus on the surfaces and interfaces Identify material properties that can be a reliable proxy for the performance of superconducting resonators and qubits Communicate findings to teammates, the broader CQC team and, when appropriate, publish findings in scientific journals A day in the life At the AWS CQC, we understand that developing quantum computing technology is a marathon, not a sprint. The work/life integration within our team encourages a culture where employees work hard and also have ownership over their downtime. We are committed to the growth and development of every employee at the AWS CQC, and that includes our research scientists. You will receive management and mentorship from within the team that is geared toward career growth, and also have the opportunity to participate in Amazon's mentorship programs for scientists and engineers. Working closely with other quantum research scientists in other disciplines – like design, measurement and cryogenic hardware – will provide opportunities to dive deep into an education on quantum computing. About the team Our team contributes to the fabrication of processors and other hardware that enable quantum computing technologies. Doing that necessitates the development of materials with tailored properties for superconducting circuits. Research Scientists and Engineers on the Materials team operate deposition and characterization systems in order to develop and optimize thin film processes for use in these devices. They work alongside other Research Scientists and Engineers to help deliver the fabricated devices for quantum computing experiments. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a U.S export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. 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. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.

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.

We are looking for an Applied Scientist who is passionate about building services and tools for developers that leverage artificial intelligence and machine learning. You will be part of a team building the next generation of AI agents for software builders. The team continuously pushes the frontier of agentic AI capabilities throughout the entire software development life-cycle. If you are excited about working in cloud computing and building new AWS services, then we'd love to talk to you. As an Applied Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs. You take a long-term view of the business objectives, product roadmaps, technologies, and how they should evolve. You drive mindful discussions with customers, engineers, and scientist peers. You bring perspective and provide context for current technology choices, and make recommendations on the right modeling and component design approach to achieve the desired customer experience and business outcome. Key job responsibilities Understand the challenges that developers face when building software today, and develop generalizable solutions. Collaborate with developers and pave the way towards bringing your solution into production systems. Lead cross team projects and ensure technical blockers are resolved. Communicate and document your research via publishing papers in external scientific venues. About the team The Amazon Web Services (AWS) Agentic AI science team builds AI solutions to reimagine the experience of all software builders. From the IDE and CLI to web-based tools and services, we build AI applications to help software builders. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you.

Amazon Advertising is one of Amazon's fastest growing and most profitable 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! As an Applied Scientist on this team, you will: - Be a strong contributor to Machine Learning; lending effort within this team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build 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. - 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. - Research new and innovative machine learning approaches. Why you will love this opportunity: Amazon is investing 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 join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a Sr. manager of Applied Science who can lead a team of talented scientists to build advanced algorithmic systems that help manage the safety of millions of transactions every day. You will also spearhead initiatives to leverage Generative AI technologies to revolutionize our fraud detection capabilities and create next-generation risk prevention solutions Key job responsibilities - Lead a team of scientists in developing machine learning and statistical techniques to create scalable risk management systems, including exploration of GenAI applications - Guide team strategy in analyzing Amazon's historical business data to identify risk patterns and trends that inform business decisions - Partner with senior leaders to frame business problems, establish scientific vision, and execute strategic roadmaps across the organization - Direct research initiatives in novel machine learning approaches and ensure successful implementation of promising solutions - Oversee the design, development, and evaluation of highly innovative risk management models - Build and maintain strategic partnerships with software engineering teams to ensure successful real-time model implementations and new feature creations - Develop and maintain relationships with operations staff to optimize risk management operations - Drive the establishment of scalable, efficient, automated processes for large-scale data analyses, model development, validation, and implementation - Provide clear, compelling management reporting on team progress, model performance, and business impact. - Hire, grow, and develop excellent scientific and analytic talents within the BRP Payment Risk team.