Careers

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.

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.

Are you passionate about robotics and research? Do you want to solve real customer problems through innovative technology? Do you enjoy working on scalable research and projects in a collaborative team environment? Do you want to see your science solutions directly impact millions of customers worldwide? At Amazon, we hire the best minds in technology to innovate and build on behalf of our customers. Customer obsession is part of our company DNA, which has made us one of the world's most beloved brands. We’re looking for current PhD students with a passion for robotic research and applications to join us as Robotics Applied Scientist II Intern/Co-ops in 2026 to shape the future of robotics and automation at an unprecedented scale across. For these positions, our Robotics teams at Amazon are looking for students with a specialization in one or more of the research areas in robotics such as: robotics, robotics manipulation (e.g., robot arm, grasping, dexterous manipulation, end of arm tools/end effector), autonomous mobile robots, mobile manipulation, movement, autonomous navigation, locomotion, motion/path planning, controls, perception, sensing, robot learning, artificial intelligence, machine learning, computer vision, large language models, human-robot interaction, robotics simulation, optimization, and more! We're looking for curious minds who think big and want to define tomorrow's technology. At Amazon, you'll grow into the high-impact engineer you know you can be, supported by a culture of learning and mentorship. Every day brings exciting new challenges and opportunities for personal growth. By applying to this role, you will be considered for Robotics Applied Scientist II Intern/Co-op (2026) opportunities across various Robotics teams at Amazon with different robotics research focus, with internship positions available for multiple locations, durations (3 to 6+ months), and year-round start dates (winter, spring, summer, fall). Amazon intern and co-op roles follow the same internship structure. "Intern/Internship" wording refers to both interns and co-ops. Amazon internships across all seasons are full-time positions, and interns should expect to work in office, Monday-Friday, up to 40 hours per week typically between 8am-5pm. Specific team norms around working hours will be communicated by your manager. Interns should not have conflicts such as classes or other employment during the Amazon work-day. Applicants should have a minimum of one quarter/semester/trimester remaining in their studies after their internship concludes. The robotics internship join dates, length, location, and prospective team will be finalized at the time of any applicable job offers. In your application, you will be able to provide your preference of research interests, start dates, internship duration, and location. While your preference will be taken into consideration, we cannot guarantee that we can meet your selection based on several factors including but not limited to the internship availability and business needs of this role. About the team The Personal Robotics Group is pioneering intelligent robotic products that deliver meaningful customer experiences. We're the team behind Amazon Astro, and we're building the next generation of robotic systems that will redefine how customers interact with technology. Our work spans the full spectrum from advanced hardware design to sophisticated software and control systems, combining mechanical innovation, software engineering, dynamic systems modeling, and intelligent algorithms to create robots that are not just functional, but delightful. This is a unique opportunity to shape the future of personal robotics working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. Join us if you're passionate about creating the future of personal robotics, solving complex challenges at the intersection of hardware and software, and seeing your innovations deliver transformative customer experiences.

The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Science Manager with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to lead a team ensuring the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Science Manager will lead and mentor a team of Applied Scientists who develop comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. The manager will guide the team in designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that align with core scientist team developing Amazon Nova models. The Applied Science Manager will oversee expert-level manual audits, meta-audits to evaluate auditor performance, and provide coaching to uplift overall quality capabilities across the team. A critical aspect of this role involves managing the development and maintenance of LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Science Manager will also oversee the configuration of data collection workflows and ensure effective communication of quality feedback to stakeholders. The manager will have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. The Applied Science Manager will be responsible for recruiting, hiring, and developing team members, conducting performance reviews, setting clear expectations and growth plans, and fostering a culture of scientific excellence and innovation. The manager will communicate with senior leadership, cross-functional technical teams, and customers to collect requirements, describe product features and technical designs, and articulate product strategy. A day in the life An Applied Science Manager with the AGI team will lead quality solution design, guide root cause analysis on data quality issues, drive research into new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. The manager will work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice. The manager will also conduct regular 1:1s with team members, provide mentorship and coaching, and ensure the team delivers high-impact results aligned with organizational goals.

Are you interested in a unique opportunity to advance the accuracy and efficiency of Artificial General Intelligence (AGI) systems? If so, you're at the right place! We are the AGI Autonomy organization, and we are looking for a driven and talented Member of Technical Staff to join us to build state-of-the art agents. As an MTS on our team, you will design, build, and maintain a Spark-based infrastructure to process and manage large datasets critical for machine learning research. You’ll work closely with our researchers to develop data workflows and tools that streamline the preparation and analysis of massive multimodal datasets, ensuring efficiency and scalability. We operate at Amazon's large scale with the energy of a nimble start-up. If you have a learner's mindset, enjoy solving challenging problems and value an inclusive and collaborative team culture, you will thrive in this role, and we hope to hear from you. Key job responsibilities * Develop and maintain reliable infrastructure to enable large-scale data extraction and transformation. * Work closely with researchers to create tooling for emerging data-related needs. * Manage project prioritization, deliverables, timelines, and stakeholder communication. * Illuminate trade-offs, educate the team on best practices, and influence technical strategy. * Operate in a dynamic environment to deliver high quality software.

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 an Applied Scientist to join us in developing advanced forecasting models, optimization models, and analytical tools to support critical real estate and store 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 an Applied Scientist on our team, you will apply your technical and analytical skills to tackle complex business problems and develop innovative solutions to improve our forecasting and decision-making capabilities. 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 end-to-end solutions, tools and frameworks to scale our ML model development 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. - 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.

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? If so, the WW Amazon Logistics, Business Analytics team is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner. We are looking for an enthusiastic, customer obsessed, Applied Scientist with good analytical skills to help manage projects and operations, implement scheduling solutions, improve metrics, and develop scalable processes and tools. The primary role of an Operations Research Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on how the final phase of delivery is done at Amazon. Candidates will be a high potential, strategic and analytic graduate with a PhD in (Operations Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of operations research, and the ability to use data and research to make changes. This role requires robust program management skills and research science skills in order to act on research outcomes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment. Responsibilities may include: - Develop input and assumptions based preexisting models to estimate the costs and savings opportunities associated with varying levels of network growth and operations - Creating metrics to measure business performance, identify root causes and trends, and prescribe action plans - Managing multiple projects simultaneously - Working with technology teams and product managers to develop new tools and systems to support the growth of the business - Communicating with and supporting various internal stakeholders and external audiences

Ever wonder how you can keep the world’s largest selection also the world’s safest and legally compliant selection? Then come join a team with the charter to monitor and classify the billions of items in the Amazon catalog to ensure compliance with various legal regulations. The Classification and Policy Platform team is looking for Applied Scientists to build technology to automatically monitor the billions of products on the Amazon platform. The software and processes built by this team are a critical component of building a catalog that our customers trust. You will have an opportunity to work with machine learning algorithms on large datasets. You will need to build Amazon scale applications running on Amazon Cloud that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data. We are looking for highly motivated applied scientists interested in delivering the next level of innovation to product search for Amazon. As an Applied Scientist on the CPP team, you will be responsible for working across backend, client, business development, and data engineering teams to coordinate deep-dives, inform roadmaps, visualize metrics, and create predictive models to determine how we can best serve our customers. Responsibilities include: - Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understanding - Conducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essential - Working closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps - Communicating effectively with management as well as with colleagues from science, engineering, and business backgrounds - Being a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers The successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, a start-up mentality, excellent project management skills, and great communication skills. Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information.

Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As an Applied Scientist, you'll be at the forefront of developing breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive independent research initiatives in areas such as perception, manipulation, science understanding, locomotion, manipulation, sim2real transfer, multi-modal foundation models and multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You'll have access to Amazon's vast computational resources, enabling you to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Drive independent research initiatives across the robotics stack, including robotics foundation models, focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Lead full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to the team's technical strategy and help shape our approach to next-generation robotics challenges A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges - Lead technical initiatives from conception to deployment, working closely with robotics engineers to integrate your solutions into production systems - Participate in technical discussions and brainstorming sessions with team leaders and fellow scientists - Leverage our massive compute cluster and extensive robotics infrastructure to rapidly prototype and validate new ideas - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.