Careers

Do you want to lead the Ads industry and redefine how we measure the effectiveness of Amazon Ads business? Are you passionate about causal inference, Deep Learning/DNN, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation? If so, come join Amazon Ads to be an Economist leader within our Advertising Incrementality Measurement science team! Our work builds the foundations for providing customer-facing experimentation tools, furthering internal research & development on Econometrics, and building out Amazon's advertising measurement offerings. Incrementality is a lynchpin for the next generation of Amazon Advertising measurement solutions and this role will play a key role in the release and expansion of these offerings. Key job responsibilities As an Economist leader within the Advertising Incrementality Measurement (AIM) science team, you are responsible for defining and executing on key workstreams within our overall causal measurement science vision. In particular, you can lead the development of experimental methodologies to measure ad effectiveness, and also build observational models that lay the foundations for understanding the impact of individual ad touchpoints for billions of daily ad interactions. You will work on a team of Applied Scientists, Economists, and Data Scientists, alongside a dedicated Engineering team, to work backwards from customer needs and translate product ideas into concrete science deliverables. You will be a thought leader for inventing scalable causal measurement solutions that support highly accurate and actionable insights--from defining and executing hundreds of thousands of RCTs, to developing an exciting science R&D agenda. You will be working with massive data and industry-leading partner scientists, while also interfacing with leadership to define our future vision. Your work will help shape the future of Amazon Advertising. About the team AIM is a cross disciplinary team of engineers, product managers, economists, data scientists, and applied scientists with a charter to build scientifically-rigorous causal inference methodologies at scale. Our job is to help customers cut through the noise of the modern advertising landscape and understand what actions, behaviors, and strategies actually have a real, measurable impact on key outcomes. The data we produce becomes the effective ground truth for advertisers and partners making decisions affecting millions in advertising spend.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through novel 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 ecosystem. 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. Key job responsibilities As an Applied Scientist on our team, you will * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build recommendation systems that leverage generative models to develop and improve campaigns. * You invent and design new solutions for scientifically-complex problem areas and/or opportunities in new business initiatives. * You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses; * Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Stay up-to-date with advancements and the latest modeling techniques in the field About the team We are on a mission to make Amazon the best in class destination for shoppers to discover, engage, and purchase relevant products, from brands that are relevant to them. In this role, you will design and implement Gen AI solutions that help millions of advertisers create more effective ad campaigns with intelligent recommendations, while improving the overall experience at Amazon's global scale.

Do you want to shape the next generation of AI-driven customer experiences for Amazon’s most ground-breaking products? Join us and help invent the future of shopping. We are seeking a passionate, innovative, and highly skilled Applied Scientist with expertise in AI, Agentic LLMs, Generative AI, Machine Learning, and NLP to help build LLM-powered solutions for Amazon’s BuyForMe product, which enables Amazon customers to discover and purchase products from any merchants. Our team develops science and agentic AI capabilities that power a seamless, end-to-end shopping experience for Amazon customers. We build and advance technologies such as agentic frameworks, LLM fine-tuning, reinforcement learning, prompt engineering, RAG, MCP, and automated benchmarking to improve pre-purchase, in-purchase, and post-purchase workflows. Key job responsibilities As an Applied Scientist on our team, you will: Invent, implement, and evaluate state-of-the-art models and agentic systems that directly impact customer experience. Conduct research that may lead to publications, patents, or cross-Amazon technical influence. Collaborate with engineers, product managers, and other scientists to translate business challenges into scalable science solutions. Run experiments with real customer data and validate hypotheses in a high-impact product environment. Drive excellence in model performance, safety, reliability, and evaluation frameworks.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC., Offered Position: Research Scientist II Job Location: San Francisco, California Job Number: AMZ9674001 Position Responsibilities: Design research studies to obtain scientific information. Develop theories or models of physical phenomena encountered in quantum computing, superconducting qubit device physics, materials or process development and characterization. Collaborate with others to determine design specifications, including of superconducting quantum processor chips, microwave chip packages, and associated electrical and mechanical components. Develop scientific or mathematical models to predict physical device behavior and performance, and verify the implementation of computational models. Apply mathematical principles or statistical approaches to solve problems, for example to validate modeling predictions under experimental uncertainty using statistical methods. Operate laboratory or field equipment and scientific instrumentation for device fabrication, device characterization, or advanced materials research. Develop new algorithms or methods for designing, simulating, or measuring quantum computers. Develop performance metrics or standards related to quantum information technology. Recommend technical design or process changes to improve quality or performance of superconducting quantum processors and efficiency of their design, manufacture, and testing. Collaborate on research activities with scientists or technical specialists. Prepare scientific or technical reports or presentations and present research results to others. 40 hours / week, 8:00am-5:00pm, Salary Range $168,126/year to $212,800/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Sr. Applied Scientist in Robot Perception, you will be at the forefront of this transformation. You will develop and deploy state-of-the-art perception algorithms that enable robots to truly understand and interact with the physical world — bridging the gap between theoretical research and real-world impact. Bringing deep expertise in Computer Vision and a nuanced understanding of the capabilities and limitations of modern Vision-Language Models (VLMs), you will innovate boldly and push the boundaries of what's possible. Our vision for the Perception layer is ambitious: to enable seamless, intelligent interaction between the user, the robot, and its environment. This is a rare opportunity to work at the intersection of deep learning, large language models, and robotics — contributing to research that doesn't just advance the field, but reshapes it. You will collaborate with world-class teams pioneering breakthroughs in dexterous manipulation, locomotion, and human-robot interaction, all at an unprecedented scale. Join us in building intelligent robotic systems that will define the future of automation and human-robot collaboration. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our Industrial Robotics Group is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.

This position is based in Bangalore, India The Last Mile team helps get packages from delivery stations to a customer’s doorstep. To provide new innovations for customers, awe are inventing the next-generation smart delivery operation. We are combining innovative mobile and IoT technologies, data streams (video, vehicle telematics, location, and presence), together with machine learning models and algorithms – all to create solutions that allow us to deliver faster, and with more confidence. Playing a key role in the Last Mile Driver Experience team, as a Applied Scientist you will be responsible for building machine learning models and algorithms in areas including mapping and location, pattern detection in sensor data, and computer vision. Using your research, you will work with your engineering and product management peers to drive designs from ideation through development and into production. You will bring your experience of research for similar products and solutions, preferably in consumer or industrial verticals. This role requires autonomy and an ability to deliver results, often within the ambiguity of building a v1 product. You will need to work efficiently to build the right things with limited guidance, raising the bar to create an amazing experience for our customers.

AWS GameTech Cortex is seeking an experienced Applied Scientist to join our team that specializes in full stack data solutions for games. In this role, you will drive the development and deployment of machine learning solutions that directly impact how game developers build, operate, and optimize their games on AWS. You will work at the intersection of gaming, data science, and cloud infrastructure to solve complex problems in areas such as player behavior prediction, game performance optimization, content recommendation, and anti-cheat systems. As a senior member of the team, you will lead the design and implementation of ML models and algorithms that process massive-scale gaming data. You will collaborate with game studios, AWS service teams, and product managers to identify high-impact opportunities and translate them into scalable ML solutions. Your work will influence the gaming experiences of millions of players worldwide while helping game developers make data-driven decisions. The ideal candidate combines deep expertise in machine learning with a passion for gaming and the ability to deliver production-ready solutions. You will mentor junior scientists, establish best practices for ML development, and contribute to the technical direction of the team. Key job responsibilities Design, develop, and deploy machine learning models and algorithms that solve critical problems for game developers, including player analytics, game performance optimization, content personalization, and fraud detection Lead end-to-end ML projects from problem definition through production deployment, ensuring solutions are scalable, maintainable, and deliver measurable business impact Analyze large-scale gaming datasets to identify patterns, extract insights, and develop predictive models that improve game operations and player experience Collaborate with game studios and AWS service teams to understand their challenges, define requirements, and deliver ML solutions that integrate seamlessly with their workflows Establish and promote best practices for ML development, experimentation, and deployment within the team, including model evaluation, A/B testing, and monitoring Mentor and provide technical guidance to junior applied scientists and engineers, fostering a culture of innovation and technical excellence Stay current with the latest research in machine learning, gaming analytics, and related fields, and apply relevant advances to solve customer problems Communicate complex technical concepts and results to both technical and non-technical audiences, including senior leadership Contribute to the technical strategy and roadmap for ML capabilities in AWS GameTech About the team AWS GameTech Cortex is an applied science & ML team, that specializes in full stack data solutions for games.

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining advertising through generative AI, transforming how millions of customers discover products and engage with brands across Amazon.com and beyond. We bridge human creativity with artificial intelligence across the full advertising lifecycle—from ad creation and optimization to performance analysis and customer insights. Within SPB, the Off-Search team builds ad experiences across surfaces beyond Search—product detail pages, the homepage, and store-in-store pages. Our team is specifically focused on ad and experience expansion on Homepage: growing the number of ad placements, introducing new widget formats, and delivering richer, more personalized ad experiences that integrate naturally with the shopping journey. We partner with Amazon Stores to ensure ads complement organic recommendations—new arrivals, deals, basket-building content, and fast-delivery options—while adapting to shopper preferences, seasonal moments, and diverse page layouts. We operate full stack, from backend retrieval and auction systems to the shopper-facing experience layer. If you're energized by solving complex challenges at the intersection of ads, personalization, and customer experience, join us in shaping the future of advertising on Amazon's most visited surface. Key job responsibilities This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our Homepage team is at the center of this mission, leveraging large language models (LLMs) to build a new generation of personalized ad experiences that understand shopper intent, adapt to individual preferences, and deliver contextually relevant creatives in real time. Beyond Homepage, we are designing these experiences as reusable building blocks that can scale across other pages on Amazon—detail pages, browse, store-in-store, and emerging surfaces—so that innovation on one page accelerates growth everywhere. We operate full stack, from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences, working in close partnership with Amazon Stores to integrate advertising seamlessly alongside organic content like new arrivals, basket-building recommendations, and fast-delivery options. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we're helping businesses grow on Amazon.com and beyond!

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. Key job responsibilities We are looking for an Applied Science Manager to lead the Amazon Sponsored Agent (ASA) team within Sponsored Products and Brands (SPB). ASA is new agentic service that enables publishers and apps to monetize their AI experiences with conversational and agentic ads. This team owns the core ASA platform that serves contextual ads across 1P surfaces (Alexa+, Amazon.com) and 3P publisher integrations, delivering AI-native ad formats including Sponsored Collections, Sponsored Brand Agents, and Commercial Insights that seamlessly integrate into conversational experiences. As an Applied Science Manager, you will innovate and design new conversational ad experiences that transform how customers discover and engage with products on conversational surfaces. You will lead a team of applied scientists and engineers to build and scale ASA's multi-agent system architecture for conversational commerce. You will own the science roadmap for contextual ad serving, conversation understanding, and commercial insights generation that help publishers monetize their AI chat experiences and unlock opportunities to scale Amazon's advertising business into new conversational surfaces. This role requires strong technical depth in NLP, LLMs, multi-agent systems, and information retrieval, combined with product innovation skills to envision and prototype new advertising experiences for conversational AI. You will manage and grow a science team, set research direction, and influence product strategy. You will work across organizational boundaries with engineering, product, and business teams to translate science investments and innovative product concepts into measurable business impact.

We are building the next generation of personalized shopping experiences at Amazon through deep understanding of our customer's intent and our product catalog. We aim to create an experience akin to that of a talented personal shopping assistant — a partner that is knowledgeable, understands your preferences, and helps you find the right solution for your needs. As a Sr. Mgr of Applied Science on the team, you will help lead a large multidisciplinary team. You will have a breadth of problems to work on, ranging from developing state of the art LLM-based techniques to reason about customers and products, developing deep learned transformer-based models to understand and abstract customer intent signals and representations, building large-scale real-time multi-task ranking systems, and more. You will build AI primative systems to empower teams across the company to build recommendations experiences, while also having a direct connection to millions of customers through our own customer facing features every day. Come join us in the journey! Key job responsibilities * Own and drive the science and engineering vision and roadmap across multiple teams, setting a cohesive technical agenda that connects research investments to production systems and measurable customer outcomes * Lead a combined organization of applied scientists and software engineers, building a culture of scientific rigor, engineering excellence, and rapid experimentation * Architect and deliver end-to-end ML systems at Amazon scale — from model research and training through real-time serving infrastructure — for ranking, intent understanding, and personalization across all customers and countries * Drive engineering best practices across the org, ensuring production systems meet Amazon's bar for reliability, latency, and operational excellence * Advance the state of the art in applied ML/AI, contributing to the broader scientific community * Mentor and grow applied scientists and engineers at all levels, developing the next generation of technical leaders in the org * Represent the organization in leadership forums, influencing cross-org strategy and investment decisions across both science and engineering About the team Our mission is to delight every Amazon customer with a personalized shopping experience tailed to their intent. We achieve our mission through investments in UX, Science, and Systems with the purpose of delivering the future of shopping on Amazon. We are seeking a Principal Applied Scientist to lead the science charter across the recommendations and intent identification space. About our organization: Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for ...", “Customers who bought this item also bought”, and “Frequently bought together”. Amazon’s internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow.