Careers

Amazon Advertising drives billions of ad impressions and millions of clicks daily, powering discovery and sales for advertisers across Amazon's Retail and Marketplace businesses. The Ads Marketing Decision Science team sits at the intersection of data science and marketing strategy. We build intelligent, data-driven systems that analyze advertiser behavior at large scale to deliver the right guidance to the right advertiser at the right time. Our work spans behavioral modeling, content intelligence, automated decision systems, and GenAI applications, enabling personalized marketing experiences that help advertisers make smarter advertising decisions and grow their business on Amazon. We are looking for a Data Scientist who brings strong fundamentals in machine learning, causal inference, and statistical modeling to solve real advertiser problems. You will build predictive models, design experiments, develop segmentation frameworks, and leverage GenAI capabilities where applicable, taking solutions end-to-end from proof-of-concept to production at scale. You will partner closely with scientists, engineers, and product managers on a daily basis to prototype rapidly, ensure data integrity in production systems, and deliver measurable advertiser impact. If you are passionate about solving real-world problems with cutting-edge science, come join us as we innovate and make history. Key job responsibilities • Define and execute data science solutions end-to-end, from problem framing through production deployment. • Build machine learning models (classification, regression, clustering, ranking) for advertiser segmentation, propensity modeling, and recommendations. • Apply causal inference and experimentation methods (A/B testing, difference-in-differences, propensity score matching) to measure the impact of marketing interventions. • Analyze large-scale advertiser behavioral data to identify trends, surface growth opportunities, and support optimal decision making. • Collaborate with colleagues across science and engineering disciplines for fast turnaround proof-of-concept prototyping at scale. • Establish and drive data hygiene best practices to ensure coherence and integrity of data feeding into production ML/AI solutions. • Leverage GenAI and LLM capabilities to enhance science products where applicable A day in the life You will solve real-world problems by analyzing large volumes of advertiser data, building predictive models, designing experiments, and measuring business impact. You will prototype rapidly, validate ideas with data, and partner with engineers to productize and scale successful solutions. You will collaborate daily with scientists, engineers, and product managers across the advertising organization, working in a cross-functional, fast-paced environment where data drives decisions and helps advertisers grow. About the team We are a team of Applied Scientists, Research Scientists, Data Scientists, and Business Intelligence Engineers with deep expertise in ML, NLP, Gen-AI, RL, and causal inference, from a diverse range of backgrounds. We partner closely with strong engineers, product managers, and sales leaders who bring ads-industry depth and experience building scalable modeling and software solutions.

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.

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE We are seeking a data scientist builder to join the Audible economics team. Our group of economists, data scientists, and analysts tackles a wide range of questions, including pricing, experimentation science, data-driven product strategy/optimizations, internal productivity/incentives, audience science, and impact/ROI measurement. The ideal candidate will enjoy wearing many hats, possess an economist's mindset and a strong ability to effectively translate business questions into tractable quantitative frameworks, and excel at leveraging AI to build and scale robust, interpretable, and production-ready models/systems/tools. We're looking for someone who automates the repetitive, builds tools that force-multiply the team's output/influence, and treats AI as a core part of their workflow - not a side project. If you are passionate about leveraging data to shape the future of digital media, we encourage you to apply and be a part of our dynamic team. As a Data Scientist, you will... - Collaborate with economists, analysts, and other data scientists to build and scale econometric/ML models and quantitative tools - owning end-to-end scoping, data pipelining, feature engineering, model development/refinement, production-grade deployment, impact measurement, and adoption - Research and evaluate emerging tools and techniques (AI-driven and otherwise), and identify novel data sources to leverage in quantitative work – both from within Audible/Amazon and from 3P sources - Collaborate closely with Product, Content, and Marketing partners to drive broad impact and ensure that solutions are integrated into cross-functional workflows and executive decision-making - Represent the team in a range of settings - from reviews with senior Amazon scientists to reviews with senior Audible/Amazon business leaders - Mentor junior scientists and raise the bar for a new generation of scalable, AI-enabled science/analytical work, both within Audible and across the broader Amazon community ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home. Key job responsibilities

Are you passionate about giving customers the richest, most inspiring experience in their shopping journey? Do you like to dive deep to understand how customer-centric solutions drive measurable results? Do you enjoy working closely with the business and software engineers to design rigorous experiments, build the data infrastructure behind them, and translate results into decisions? You are in the right place! Come join our Prime & Marketing Analytics and Science (PRIMAS) team, where your work will directly impact millions of customers. The EU Marketing & Prime organization is looking for a Data Scientist to join the PRIMAS team. This role sits at the intersection of applied statistics and large-scale analytics — you'll design experiments and causal models, and also own the data pipelines, metrics, and reporting infrastructure that make those results usable across the business. The PRIMAS team provides a comprehensive understanding of customer segments, affinities, and lifetime value. We use data science tools and advanced statistical techniques to study customer purchase and engagement behaviors, and generate actionable insights on where, when, and how we deliver products and programs to customers. We help increase customer engagement, sales, and marketing efficiency, and our systems are built entirely in-house on automated large-scale analytics infrastructure. You will design, launch, and measure experiments across marketing channels (SEM/SEO, Affiliates, Display, Social, Mobile, Email, Onsite, etc.), engagement products, and customer segments. You will improve our understanding of customer behavior, run rigorous power and minimum detectable effect (MDE) analyses to size experiments correctly, and build the causal and conversion models that value and target our marketing — then build the pipelines and dashboards that keep those signals flowing reliably to stakeholders and downstream systems. You will work at the forefront of consumer analytics, tackling some of the hardest measurement problems in the industry alongside strong scientists, statisticians, and software engineers. Key job responsibilities 1. Design and implement scalable, statistically rigorous experiments (A/B, geo, holdout, quasi-experiments) to measure marketing incrementality across channels. 2. Perform power analysis and minimum detectable effect (MDE) calculations to determine experiment sample sizes, durations, and design trade-offs before launch. 3. Build causal and treatment-effect models that produce conversion and valuation signals consumed by downstream bidding and budgeting systems. 4. Building the ETL, metric definitions, and datasets that make results scalable, extensible, and repeatable rather than one-off analyses. 5. Develop measurement frameworks that quantify the true, platform-independent contribution of marketing over time, and build the dashboards and reporting that keep those metrics visible to the business. 6. Apply statistical, mathematical, and machine learning techniques to solve ambiguous business problems where the right approach isn't obvious. 7. Analyze experiment results for validity — inspecting distributions, checking for sample ratio mismatch, exploring covariate balance, and tracking down the source of anomalies. 8. Communicate experiment design, results, and trade-offs clearly to business and leadership audiences, including inputs into business reviews, and influence decisions and technical direction across teams. 9. Establish scalable, repeatable processes and best practices for experiment design, data modeling, and analysis.

Amazon Advertising Trust is on a mission to redefine how trust is enforced at internet scale, and we are looking for exceptional scientists to help lead the way. We are building systems that reason about advertising content the way a trained human would, at a industry leading volume and speed, and that keep working when the rules change underneath them. At Ads Trust Science we leverage machine learning, generative AI, and large-scale retrieval to solve some of the most complex decision problems for ads worldwide. Every ad shown across Amazon's owned-and-operated properties and third-party networks, in every format and every global marketplace, depends on decisions our systems make. We are just getting started. As a Senior Applied Scientist you will be at the forefront of this work. You will own science problems end to end, bridging the gap between research and production impact. You will not be handed a specification. You will be given a customer problem, a system that partly solves it, and the latitude to decide what to build next. This is a unique opportunity to work at the intersection of multimodal understanding, large language models, and large-scale retrieval, on a problem where the science is genuinely unsettled. You will work alongside scientists whose models run in front of hundreds of millions of customers, at a scale that changes which approaches are even possible. A day in the life - Ship a model into production, then find and document where it fails once real traffic reaches it. - Drive the technical discussion, inside your team and with partner teams, on how to close that gap. - Bring a fresh angle to a problem that is not yours and help a peer get further than they would have alone, building trust across the team in the process. - Mentor while staying hands-on. At this level the design and the code are both yours. About the team Ads Trust Science is a group of scientists who would rather change what the team measures than optimise the wrong number. We value curiosity, rigour, and a bias for action. We expect people to disagree with evidence, to say clearly what did not work, and to iterate quickly toward the solutions that matter.

Do you enjoy solving challenging problems and driving innovation in research? Do you want to develop scalable models and apply machine learning techniques to guide real-world decisions? We are looking for builders, innovators, and entrepreneurs who want to bring their ideas to reality and improve the lives of millions of customers. As a Research Science Intern, you will apply advanced statistical techniques and emerging AI/ML technologies to solve complex problems, implement prototypes, and work with massive datasets. You'll find yourself at the forefront of innovation, shaping the future of Amazon's products, services, and operations. Imagine waking up each morning, fueled by the excitement of solving intricate problems that have a direct impact on Amazon's excellence. Your day might begin by collaborating with cross-functional teams, exchanging ideas and insights to develop innovative solutions. You'll immerse yourself in a world of data, leveraging your expertise in areas such as optimization, machine learning, statistical modeling, and algorithmic research to uncover hidden patterns and drive meaningful impact. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research, and mentorship from industry leaders. This immersive experience will sharpen your technical skills and cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Amazon has positions available for Research Science Internships in, but not limited to, Bellevue, WA; Boston, MA; Cambridge, MA; New York, NY; Santa Clara, CA; Seattle, WA; Sunnyvale, CA, Arlington, VA Key job responsibilities • Conduct research activities including data collection, analysis, and interpretation under the guidance of senior researchers • Develop and test hypotheses using appropriate scientific methodologies and computational tools • Document findings, maintain detailed research records, and prepare reports summarizing results and insights • Collaborate with team members to troubleshoot challenges and refine experimental approaches • Participate in team meetings and present progress updates on assigned research projects A day in the life As a Research Science Intern, you'll immerse yourself in hands-on scientific work, collaborating with our research team on projects that span data analysis, experimental design, and computational modeling. Your day might include conducting literature reviews, running simulations, analyzing datasets, and participating in team discussions where your insights contribute to ongoing research initiatives. You'll have opportunities to present findings, learn from mentors, and develop practical skills in a supportive research environment that values curiosity and collaborative problem-solving.

Shape the Future of Visual Intelligence Are you passionate about pushing the boundaries of computer vision and shaping the future of visual intelligence? Join Amazon and embark on an exciting journey where you'll develop cutting-edge algorithms and models that power our groundbreaking computer vision services, including Amazon Rekognition, Amazon Go, Visual Search, and more! At Amazon, we're combining computer vision, mobile robots, advanced end-of-arm tooling, and high-degree of freedom movement to solve real-world problems at an unprecedented scale. As an intern, you'll have the opportunity to build innovative solutions where visual input helps customers shop, anticipate technological advances, work with leading-edge technology, focus on highly targeted customer use-cases, and launch products that solve problems for Amazon customers worldwide. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available for Computer Vision Applied Science Internships in, but not limited to, Arlington, VA; Boston, MA; Cupertino, CA; Minneapolis, MN; New York, NY; Portland, OR; Santa Clara, CA; Seattle, WA; Bellevue, WA; Santa Clara, CA; Sunnyvale, CA. Key job responsibilities We are particularly interested in candidates with expertise in: Vision - Language Models, Object Recognition/Detection, Computer Vision, Large Language Models (LLMs), Programming/Scripting Languages, Facial Recognition, Image Retrieval, Deep Learning, Ranking, Video Understanding, Robotics In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas of visual intelligence. You will tackle challenging, groundbreaking research problems to help build solutions where visual input helps the customers shop, anticipate technological advances, work with leading edge technology, focus on highly targeted customer use-cases, and launch products that solve problems for Amazon customers. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems, and to communicate research findings clearly. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. Leverage AI-powered tools where applicable to accelerate research, experimentation, and prototyping. Critically review and validate outputs from AI tools and automated systems. A day in the life - Collaborate with Amazon scientists and cross-functional teams to develop and deploy cutting edge computer vision solutions into production. - Dive into complex challenges, leveraging your expertise in areas such as Vision-Language Models, Object Recognition/Detection, Large Language Models (LLMs), Facial Recognition, Image Retrieval, Deep Learning, Ranking, Video Understanding, and Robotics. - Contribute to technical white papers, create technical roadmaps, and drive production-level projects that will support Amazon Science. - Embrace ambiguity, strong attention to detail, and a fast-paced, ever-changing environment as you own the design and development of end-to-end systems. - Engage in knowledge-sharing, mentorship, and career-advancing resources to grow as a well-rounded professional.

Are you a brilliant mind seeking to push the boundaries of what's possible with intelligent robotics? Join our elite team of researchers and engineers - led by Pieter Abeel, Rocky Duan, and Peter Chen - at the forefront of applied science, where we're harnessing the latest advancements in large language models (LLMs) and generative AI to reshape the world of robotics and unlock new realms of innovation. As an Applied Science Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge robotics technologies. You'll dive deep into exciting research projects at the intersection of AI and robotics. This internship is not just about executing tasks – it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning to tackle real-world problems and deliver impactful solutions. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied robotics and AI, where your contributions will shape the future of intelligent systems and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Must be eligible and available for a full-time (40h/ week) 12 week internship between May 2026 and September 2026. Amazon has positions available in San Francisco, CA and Seattle, WA. The ideal candidate should possess: - Strong background in machine learning, deep learning, and/or robotics - Publication record at science conferences such as NeurIPS, CVPR, ICRA, RSS, CoRL, and ICLR. - Experience in areas such as multimodal LLMs, world models, image/video tokenization, real2Sim/Sim2real transfer, bimanual manipulation, open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, and end-to-end vision-language-action models. - Proficiency in Python, Experience with PyTorch or JAX - Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a team Apply now and embark on an extraordinary journey of discovery and innovation! Key job responsibilities Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and generative AI for robotics Tackle challenging, groundbreaking research problems on production-scale data, with a focus on robotic perception, manipulation, and control Collaborate with cross-functional teams to solve complex problems, and to communicate research findings clearly, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment, and communicate effectively with diverse stakeholders Leverage AI-powered tools where applicable to accelerate research, experimentation, and prototyping. Critically review and validate outputs from AI tools and automated systems.

Are you a brilliant mind seeking to push the boundaries of what's possible with intelligent robotics? Join our elite team of researchers and engineers - led by Pieter Abeel, Rocky Duan, and Peter Chen, where we're harnessing the latest advancements in large language models (LLMs) and generative AI to reshape the world of robotics and unlock new realms of innovation. As an Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge robotics technologies. You'll dive deep into exciting research projects at the intersection of AI and robotics. This internship is not just about executing tasks – it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning to tackle real-world problems and deliver impactful solutions. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied robotics and AI, where your contributions will shape the future of intelligent systems and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available in San Francisco, CA. The ideal candidate should possess: - Strong background in machine learning, deep learning, and/or robotics - Publication record at science conferences such as NeurIPS, CVPR, ICRA, RSS, CoRL, and ICLR. - Experience in areas such as multimodal LLMs, world models, image/video tokenization, real2Sim/Sim2real transfer, bimanual manipulation, open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, and end-to-end vision-language-action models. - Proficiency in Python, Experience with PyTorch or JAX - Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a team Apply now and embark on an extraordinary journey of discovery and innovation! Key job responsibilities - Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and generative AI for robotics - Tackle challenging, groundbreaking research problems on production-scale data, with a focus on robotic perception, manipulation, and control - Collaborate with cross-functional teams to solve complex problems, and to communicate research findings clearly, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning - Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment, and communicate effectively with diverse stakeholders Leverage AI-powered tools where applicable to accelerate research, experimentation, and prototyping. Critically review and validate outputs from AI tools and automated systems.

Unleash Your Potential as an AI Trailblazer At Amazon, we're on a mission to revolutionize the way people discover and access information. Our Applied Science team is at the forefront of this endeavor, pushing the boundaries of recommender systems and information retrieval. We're seeking brilliant minds to join us as interns and contribute to the development of cutting-edge AI solutions that will shape the future of personalized experiences. As an Applied Science Intern focused on Recommender Systems and Information Retrieval in Machine Learning, you'll have the opportunity to work alongside renowned scientists and engineers, tackling complex challenges in areas such as deep learning, natural language processing, and large-scale distributed systems. Your contributions will directly impact the products and services used by millions of Amazon customers worldwide. Imagine a role where you immerse yourself in groundbreaking research, exploring novel machine learning models for product recommendations, personalized search, and information retrieval tasks. You'll leverage natural language processing and information retrieval techniques to unlock insights from vast repositories of unstructured data, fueling the next generation of AI applications. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Must be eligible and available for a full-time (40h / week) 12 week internship between May 2026 and September 2026 Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA. Key job responsibilities We are particularly interested in candidates with expertise in: Knowledge Graphs and Extraction, Programming/Scripting Languages, Time Series, Machine Learning, Natural Language Processing, Deep Learning,Neural Networks/GNNs, Large Language Models, Data Structures and Algorithms, Graph Modeling, Collaborative Filtering, Learning to Rank, Recommender Systems In this role, you'll collaborate with brilliant minds to develop innovative frameworks and tools that streamline the lifecycle of machine learning assets, from data to deployed models in areas at the intersection of Knowledge Management within Machine Learning. You will conduct groundbreaking research into emerging best practices and innovations in the field of ML operations, knowledge engineering, and information management, proposing novel approaches that could further enhance Amazon's machine learning capabilities. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex problems, and to communicate research findings clearly. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. Leverage AI-powered tools where applicable to accelerate research, experimentation, and prototyping. Critically review and validate outputs from AI tools and automated systems. A day in the life - Design, implement, and experimentally evaluate new recommendation and search algorithms using large-scale datasets - Develop scalable data processing pipelines to ingest, clean, and featurize diverse data sources for model training - Conduct research into the latest advancements in recommender systems, information retrieval, and related machine learning domains - Collaborate with cross-functional teams to integrate your innovative solutions into production systems, impacting millions of Amazon customers worldwide - Communicate your findings through captivating presentations, technical documentation, and potential publications, sharing your knowledge with the global AI community