Careers

The Next Generation Developer Experience (NGDE) Science team is looking for an Applied Scientist who is passionate about building services and tools for developers that leverage artificial intelligence (AI) and machine learning (ML). You will be part of a team building AI-based services for Amazon Q Developer with the focus on redefining the way developer work. The team works in close collaboration with other AWS AI services such as AWS Bedrock, the AWS IDE Toolkit, and Amazon Sagemaker. If you are excited about working in cloud computing and building new AWS services, then we'd love to talk to you. Key job responsibilities 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. A day in the life 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. This team is part of AWS Utility Computing: Utility Computing (UC) 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. About the team The Amazon Web Services (AWS) Next Gen DevX (NGDE) team is building Amazon Q for Developers to re-imagine all aspects of how builders create applications. We build AI products that are deployed in the IDE, the AWS console, and in web-based tools and services. We provide developers with AI assistants to generate code, features, and entire applications as well as to interact with AWS. We explore new technologies and find creative solutions, produce original research and bring cutting edge innovation to our customers. 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, this is the team for you.

We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference skillsets to solve real world problems. The intern will work in the area of 3P Seller Fees Science and develop models to understand differential impacts of changing referral and fulfillment fees on seller and customer behavior. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The Selling Partner Fees team owns the end-to-end fees experience for two million active third party sellers. We own the fee strategy, fee seller experience, fee accuracy and integrity, fee science and analytics, and we provide scalable technology to monetize all services available to third-party sellers. Within the Science team, our goal is to understand the impact of changing fees on Seller (supply) and Customers (demand) behavior (e.g. price changes, advertising strategy changes, introducing new selection etc.) as well as using this information to optimize our fee structure and maximizing long term-growth and profitability.

Interested to build the next generation Financial systems that can handle billions of dollars in transactions? Interested to build highly scalable next generation systems that could utilize Amazon Cloud? Massive data volume + complex business rules in a highly distributed and service oriented architecture, a world class information collection and delivery challenge. Our challenge is to deliver the software systems which accurately capture, process, and report on the huge volume of financial transactions that are generated each day as millions of customers make purchases, as thousands of Vendors and Partners are paid, as inventory moves in and out of warehouses, as commissions are calculated, and as taxes are collected in hundreds of jurisdictions worldwide. Key job responsibilities • Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference. • Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes • Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection. • Use machine learning and analytical techniques to create scalable solutions for business problems. • Identify new areas where machine learning can be applied for solving business problems. • Partner with developers and business teams to put your models in production. • Mentor other scientists and engineers in the use of ML techniques. A day in the life • Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference. • Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes • Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection. • Use machine learning and analytical techniques to create scalable solutions for business problems. • Identify new areas where machine learning can be applied for solving business problems. • Partner with developers and business teams to put your models in production. • Mentor other scientists and engineers in the use of ML techniques. About the team The FinAuto TFAW(theft, fraud, abuse, waste) team is part of FGBS Org and focuses on building applications utilizing machine learning models to identify and prevent theft, fraud, abusive and wasteful(TFAW) financial transactions across Amazon. Our mission is to prevent every single TFAW transaction. As a Machine Learning Scientist in the team, you will be driving the TFAW Sciences roadmap, conduct research to develop state-of-the-art solutions through a combination of data mining, statistical and machine learning techniques, and coordinate with Engineering team to put these models into production. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.

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! Key job responsibilities - Develop ML models for various recommendation & search systems using deep learning, online learning, and optimization methods - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals A day in the life We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.

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 exclusive access to coverage of live sports. All customers regardless of whether they have a Prime membership or not, can access programming from subscriptions such as Apple TV, Peacock Premium Plus, HBO Max, FOX One, Crunchyroll and MGM+, as well as more than 900 free ad-support (FAST) Channels, rent or buy titles, and 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.

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! Key job responsibilities - Develop ML models for various recommendation & search systems using deep learning, online learning, and optimization methods - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals A day in the life We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.

The Ads Measurement Science team within Amazon Ads' Measurement, AdTech, and Data Science (MADS) organization serves a centralized role developing solutions for a multitude of performance measurement products to measure the full impact of advertiser spend, including both online and offline sales impacts across all timeframes. It delivers actionable insights for advertisers to optimize media portfolios. We also build science solutions for AI and AI-powered tools that unlock new insights and automate high-effort customer workflows for ad measurement, such as custom query and report generation based on natural language user requests. We leverage new technologies including Generative AI, machine learning, causal inference, natural Language Processing (NLP), and Computer Vision (CV) to drive these innovations. A key focus of this role is Modeled Attribution, Amazon's privacy-compliant measurement system serving millions of advertisers and processing billions of events monthly across global marketplaces. We apply state-of-the-art machine learning and GenAI techniques to generate accurate measurement when user identity is unavailable, representing Amazon's technical response to industry-transforming privacy regulations and platform changes. As a Senior Applied Scientist (Applied Scientist III) on the team, you will lead the development of measurement solutions end-to-end from inception to production. You will define the technical vision for complex measurement initiatives that span multiple teams. You will drive scientific innovation at scale while influencing business and engineering strategies. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. Key job responsibilities * Innovate on state-of-the-art ads measurement solutions leveraging artificial intelligence, causal inference, natural language processing, computer vision, and large language models * Directly contribute to the end-to-end delivery of production solutions through careful designs and owning implementation of significant portions of critical-path code * Lead the decomposition of problems and development of roadmaps to execute on it * Set an example for others with exemplary analyses; maintainable, extensible code; and simple, effective solutions * Influence team business and engineering strategies * Communicate clearly and effectively with stakeholders to drive alignment and build consensus on key initiatives * Foster collaborations among scientists and engineers to move fast and broaden impact * Actively engage in the development of others, both within and outside of the team * Regularly engage with the broader science community with presentations, publications, and patents About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.

The Ads Measurement Science team within Amazon Ads' Measurement, AdTech, and Data Science (MADS) organization serves a centralized role developing solutions for a multitude of performance measurement products to measure the full impact of advertiser spend, including both online and offline sales impacts across all timeframes. It delivers actionable insights for advertisers to optimize media portfolios. We also build science solutions for AI and AI-powered tools that unlock new insights and automate high-effort customer workflows for ad measurement, such as custom query and report generation based on natural language user requests. We leverage new technologies including Generative AI, machine learning, causal inference, natural Language Processing (NLP), and Computer Vision (CV) to drive these innovations. A key focus of this role is Modeled Attribution, Amazon's privacy-compliant measurement system serving millions of advertisers and processing billions of events monthly across global marketplaces. We apply state-of-the-art machine learning and GenAI techniques to generate accurate measurement when user identity is unavailable, representing Amazon's technical response to industry-transforming privacy regulations and platform changes. As an Applied Scientist II on the team, you will develop modeled measurement solutions end-to-end from inception to production. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. Your work will directly enable advertisers to continue optimizing their campaigns effectively as the digital ecosystem undergoes significant privacy-driven changes, and provide event-level attribution signals that empower ad optimization teams to enhance campaign performance and monetization on traffic without identity. Key job responsibilities * Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems * Disambiguate problems to propose clear evaluation frameworks and success criteria * Develop modeled attribution solutions using deep learning, transformers, and large language models to fill measurement gaps in privacy-constrained environments * Work autonomously, write high-quality technical documentation and present findings to both technical and business stakeholders * Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production * Partner closely with other scientists to deliver large, multi-faceted technical projects * Share and publish works with the broader scientific community through meetings and conferences * Communicate clearly to both technical and non-technical audiences * Partner with engineers to optimize model performance, reduce latency, and ensure operational excellence for systems serving millions of customers * Contribute to the team's scientific direction by proposing novel approaches to measurement challenges * Mentor junior scientists and participate in the hiring process to raise the team's technical bar About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. Our work combines rigorous scientific experimentation with practical engineering. We publish at top-tier conferences while building production systems that process trillions of events annually. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Demand Utilization team with Sponsored Products and Brands owns finding the appropriate ads to surface to customers when they search for products on Amazon. We strive to understand our customers’ intent and identify relevant ads which enable them to discover new and alternate products. This also enables sellers on Amazon to showcase their products to customers, which may at times be buried deeper in the search results. Our systems and algorithms operate on one of the world's largest product catalogs, matching shoppers with products - with a high relevance bar and strict latency constraints. We are a team of machine learning scientists and software engineers working on complex solutions to understand the customer intent and present them with ads that are not only relevant to their actual shopping experience, but also non-obtrusive. This area is of strategic importance to Amazon Retail and Marketplace business, driving long term-growth. We are looking for an Applied Scientist III, with a background in Machine Learning to optimize serving ads on billions of product pages. The solutions you create would drive step increases in coverage of sponsored ads across the retail website and ensure relevant ads are served to Amazon's customers. You will directly impact our customers’ shopping experience while helping our sellers get the maximum ROI from advertising on Amazon. You will be expected to demonstrate strong ownership and should be curious to learn and leverage the rich textual, image, and other contextual signals. This role will challenge you to utilize innovative machine learning techniques in the domain of predictive modeling, natural language processing (NLP), deep learning, reinforcement learning, query understanding, vector search (kNN) and image recognition to deliver significant impact for the business. Ideal candidates will be able to work cross functionally across multiple stakeholders, synthesize the science needs of our business partners, develop models to solve business needs, and implement solutions in production. In addition to being a strongly motivated IC, you will also be responsible for mentoring junior scientists and guiding them to deliver high impacting products and services for Amazon customers and sellers. 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 Key job responsibilities As an Applied Scientist III on this team, you will: - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - 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. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in deploying 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.

Are you passionate about leveraging data to deliver actionable insights that impact daily marketing activities at Amazon? The Customer Targeting team in Amazon is seeking an Applied Scientist to join our team to develop models for optimizing the performance of Amazon’s marketing initiatives across channels and advertising formats. You have experience applying modern machine learning methods to answer key business questions, make strategic and tactical recommendations for change, and work with business leaders to drive these to production. You are entrepreneurial and able to work in a highly collaborative environment. This role requires an individual with strong quantitative modeling skills and experience using statistical methods. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment. You will be expected to: - Leverage knowledge of statistics and optimization to frame decision-making problems for determining marketing spends across channels. - Predict future customer behavior and business conditions through machine learning and predictive modeling. - Use analytical and predictive techniques to build models for optimizing targeting. - Present proposals and results in a clear manner backed by data and coupled with actionable conclusions.