Careers

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

Amazon ‘s Tax engine organisation is looking for a passionate and innovative science leader to take its science initiatives to new heights. Amazon Tax Engine platform backs all of the orders placed across Amazon e-commerce. We serve Amazon customers and sellers by correctly computing and collecting the tax amounts when an Amazon order is placed globally. We are responsible for correctly attributing products to the correct Tax categories applicable for the specific country, state and county, providing core calculation services that calculate taxes (sales tax and VAT) for all Amazon sales, physical and digital. Our challenges include staying on top of the complex and ever-changing global tax legislations as well as computing calculations correctly and quickly, thousands of times a second, with accuracy close to 100%. We use language models at scale for Tax classification of the diverse products in Amazon catalogue We have a growing portfolio of science problems that includes balance of predictive and generative AI -including language comprehension, causal reasoning and active learning. Key job responsibilities - Manage and mentor a talented team of senior Appleid Scientists and SDEs. - Improve process and methodologies pertaining to deliverables of the team. - Strike the right balance between experimentation and delivery for sustained impact and long term gains. - Partner with stakeholders and customers to build roadmap for new products and services.

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 foundation models for content understanding using state-of-the-art deep learning and multimodal learning techniques to analyze video, audio, and text. Build time sequence foundation models to understand and predict customer behavior patterns and viewing trajectories. Work closely with engineers and product managers to design, implement and launch solutions end-to-end across various Prime Video experiences. 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 foundation models, multimodal learning, and time series analysis. Publish your research findings in top conferences and journals. 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 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.

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. We are seeking a highly skilled and analytical Research Scientist. You will play an integral part in the measurement and optimization of Amazon Music marketing activities. You will have the opportunity to work with a rich marketing dataset together with the marketing managers. This role will focus on developing and implementing causal models and randomized controlled trials to assess marketing effectiveness and inform strategic decision-making. This role is suitable for candidates with strong background in consumer research, survey data models, causal inference, statistical analysis, and data-driven problem-solving, with the ability to translate complex data into actionable insights. As a key member of our team, you will work closely with cross-functional partners to optimize marketing strategies and drive business growth. Key job responsibilities Develop Causal Models Design, build, and validate causal models to evaluate the impact of marketing campaigns and initiatives. Leverage advanced statistical methods to identify and quantify causal relationships. Conduct Randomized Controlled Trials Design and implement randomized controlled trials (RCTs) to rigorously test the effectiveness of marketing strategies. Ensure robust experimental design and proper execution to derive credible insights. Statistical Analysis and Inference Perform complex statistical analyses to interpret data from experiments and observational studies. Use statistical software and programming languages to analyze large datasets and extract meaningful patterns. Data-Driven Decision Making Collaborate with marketing teams to provide data-driven recommendations that enhance campaign performance and ROI. Present findings and insights to stakeholders in a clear and actionable manner. Collaborative Problem Solving Work closely with cross-functional teams, including marketing, product, and engineering, to identify key business questions and develop analytical solutions. Foster a culture of data-informed decision-making across the organization. Stay Current with Industry Trends Keep abreast of the latest developments in data science, causal inference, and marketing analytics. Apply new methodologies and technologies to improve the accuracy and efficiency of marketing measurement. Documentation and Reporting Maintain comprehensive documentation of models, experiments, and analytical processes. Prepare reports and presentations that effectively communicate complex analyses to non-technical audiences.

Do you want to help shape the future of Amazon's physical retail presence? Worldwide Grocery Stores (WWGS), Location Strategy and Analytics team is looking for a Sr. Applied Scientist to join us in developing advanced forecasting models, optimization models, and analytical tools to support critical real estate and network planning decisions for Amazon's Worldwide Grocery business, including Whole Foods Market. Our team is responsible for developing predictive models and tools to support Real Estate and Topology analysts in making important decisions regarding our stores—including new store openings, relocations, closures, remodels, design, new formats, and more. We leverage statistical modeling, machine learning, and GenAI to build solutions for store sales forecasting, sales transfer effects, macrospace optimization, store network optimization, store network diffusion planning, and causal effects. As a Sr. Applied Scientist on our team, you will apply your deep technical expertise to tackle complex business problems and develop innovative solutions to improve our forecasting, decision-making capabilities, and MLOps. You will collaborate with a diverse team of scientists, economists, and business partners to identify opportunities, develop hypotheses, build internal products, and translate analytical insights into actionable recommendations for Executive Leadership. Key job responsibilities - Design and implement forecasting models and machine learning solutions to predict store performance and optimize our retail network. - Analyze large datasets to uncover insights and patterns related to store performance, customer behavior, and market dynamics. - Develop and own end-to-end solutions, tools and frameworks to scale our ML model development, MLOps, and data analysis. - Leverage GenAI models to enhance user interaction with our solutions, improve overall user experience, and build new features. - Present research findings and recommendations to scientists, business leaders, and executives. - Collaborate with cross-functional teams to drive adoption of models and insights. - Mentor junior scientists, providing technical guidance and supporting their professional growth. - Stay current on latest developments in relevant fields and propose innovative approaches. About the team We are a team of scientists passionate about leveraging data and advanced analytics to drive strategic decisions for Amazon's grocery business. Our work directly impacts Amazon's worldwide grocery store growth and development strategy. We foster a collaborative environment where team members are encouraged to think creatively, challenge assumptions, and pursue novel approaches to solving complex problems. Our team is at the forefront of applying a multitude of techniques - including GenAI - to improve our scientific solutions and products.

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 limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Senior Computational Scientist on our team, you will develop advanced computational methods to analyze complex, multi-modal datasets. You'll work with large-scale structured and unstructured data sources to build predictive models and uncover actionable insights. Our team rewards curiosity while maintaining a laser-focus on bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial environment. Key job responsibilities We're seeking an experienced Computational Scientist to develop innovative solutions for complex data challenges. In this role, you will design end-to-end computational pipelines to process and analyze multi-modal data. You'll develop algorithms that integrate diverse information sources to generate predictions and actionable insights. Building interpretable models that reveal underlying mechanisms and patterns will be central to your work. You'll collaborate with machine learning scientists and domain experts to ensure your approaches are both technically rigorous and practically impactful. You'll work with large-scale proprietary databases and scientific literature to identify meaningful signals. Establishing best practices for data integration, quality assessment, and validation will be important aspects of your role. You'll need deep expertise in computational methods and the ability to communicate complex concepts to diverse audiences while working in an early-stage, rapidly evolving environment. A day in the life You'll work with proprietary datasets and structured knowledge bases, developing computational analyses to understand how various factors influence key outcomes. You'll collaborate with Applied Scientists and Statisticians on predictive models. Regular interaction with domain experts will help translate your findings into practical insights. Given the nature of our work, you'll have significant autonomy in defining approaches and establishing new methodologies. About the team We represent Amazon’s ambitious vision to solve the world’s most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon’s scale and technological expertise. We operate with the agility of a startup while backed by Amazon’s resources and operational excellence. We’re looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.

We are looking for researchers who aim to build super-intelligent AI systems that leverage proof assistants to guide learning and reasoning. Our neuro-symbolic AI technology is applied across a wide range of science and engineering domains within Amazon, and you will join the team at the forefront of this research. As a Principal Applied Scientist, you will play a pivotal role in shaping the definition, vision, and development of product features from beginning to end. You will: - Define and implement new neuro-symbolic applications that employ scalable and efficient approaches to solve complex problems. - Work in an agile, startup-like development environment, where you are always working on the most important stuff. - Deliver high-quality scientific artifacts. About the team We work closely with academia. Our team includes an Amazon Scholar in mathematics, and we maintain active research collaborations with faculty at leading CS departments (MIT, Berkeley, CMU).

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! Amazon continues to develop its advertising program. Ads run in our Stores (including Consumer Stores, Books, Amazon Business, Whole Foods Market, and Fresh) and Media and Entertainment publishers (including Fire TV, Fire Tablets, Kindle, Alexa, Twitch, Prime Video, Freevee, Amazon Music, MiniTV, Audible, IMDb, and others). In addition to these first-party (1P) publishers, we also deliver ads on third-party (3P) publishers. We have a number of ad products, including Sponsored Products and Sponsored Brands, display and video products for smaller brands, including Sponsored Display and Sponsored TV. We also operate ad tech products, including Amazon Marketing Cloud (a clean-room for advertisers), Amazon Publisher Cloud (a clean-room for publishers), and Amazon DSP (an enterprise-level buying tool that brings together our ad tech for buying video, audio, and display ads). We are seeking an experienced Applied Scientist passionate about understanding shopping journeys spanning across ad products and publishers. Key job responsibilities This role is focused on developing core models that will be the foundational to Full Funnel Campaigns. You will regularly engage with product managers and technical program managers, who will partner with you to productize your work.