Careers

The Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers on a mission to develop a fault-tolerant quantum computer. Throughout your internship 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 Quantum Computing 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 Quantum Research Science and Applied Science Internships in Santa Clara, CA and Pasadena, CA. We are particularly interested in candidates with expertise in any of the following areas: superconducting qubits, cavity/circuit QED, quantum optics, open quantum systems, superconductivity, electromagnetic simulations of superconducting circuits, microwave engineering, benchmarking, quantum error correction, fabrication, etc. Key job responsibilities In this role, you will work alongside global experts to develop and implement novel, scalable solutions that advance the state-of-the-art in the areas of quantum computing. You will tackle challenging, groundbreaking research problems, 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. 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. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Amazon Ads is building Ads Agent, an AI-powered agent that understands advertiser intent, reasons over campaign strategy, and executes across the full Amazon Ads portfolio. If you want to work at the frontier of agentic AI and large language models while directly impacting a multi-billion dollar business, this is your team. We are seeking an experienced Applied Scientist passionate about building intelligent agents that reason, plan, and act across complex advertising workflows. Ads Agent is an AI agent that simplifies how advertisers plan, launch, and optimize campaigns. Powered by AI, Ads Agent works alongside advertisers to automate time-consuming tasks, like identifying targeting segments, adjusting pacing across hundreds of campaigns, and generating SQL queries for advanced analytics. It also provides data-driven recommendations and simplifies analysis—all while providing transparency and control. With a broad mandate to experiment and innovate, we need applied scientists to define and build the future of advertising. Key job responsibilities - Design, build, and evaluate agentic systems that plan multi-step workflows, invoke tools, and take autonomous actions across Amazon Ads products on behalf of advertisers. - Define evaluation frameworks and benchmarks for agent reliability, correctness, safety, and advertiser satisfaction. - Analyze agent behavior through deep data analysis and rigorous A/B experimentation to identify failure modes, measure effectiveness, and derive business insights. - Partner with engineers, product managers, and UX designers to ship end-to-end agent experiences that are scalable, efficient, and reliable at Amazon scale. About the team We are a small, fast-moving team building a unified AI-native interface to all of Amazon Advertising. We sit at the intersection of large language models, agentic AI, and one of the world's most complex advertising ecosystems. If you want to shape how millions of advertisers interact with Amazon Ads, come build with us.

We are seeking a Senior Applied Scientist to join the Alexa Availability team within Alexa Excellence. This role leads the research and development of machine learning and statistical models that power Alexa's reliability at massive scale — serving hundreds of millions of customers globally. The ideal candidate will tackle complex, ambiguous problems spanning time series multivariate modeling, statistical anomaly detection, LLM-based operational intelligence, and adaptive threshold systems. They will design production-grade ML solutions, establish rigorous evaluation frameworks, and ensure AI systems are grounded, reliable, and free from systematic bias — leveraging techniques such as RAG, confidence scoring, knowledge graph integration, and counterfactual testing. This scientist will partner with engineers, product managers, and operations leaders to translate scientific innovation into production systems that directly impact Alexa's availability worldwide. They will drive the scientific agenda for the team, mentor fellow scientists, and influence the broader Alexa Excellence organization through technical leadership and cross-team collaboration. Key Focus Areas: Anomaly detection and predictive failure modeling Cross-service correlation and LLM-driven operational intelligence Production ML at the intersection of large-scale distributed systems and applied science Model reliability, hallucination mitigation, and grounding for operational AI Key job responsibilities As a Senior Applied Scientist on the Alexa Availability team, you will lead the research and development of machine learning and statistical models that power Alexa's reliability at scale. You will work on some of the most complex and ambiguous problems in the space — from time series multivariate modeling and statistical anomaly detection to LLM-based operational intelligence and adaptive threshold systems. A day in the life You will design and implement production-grade ML solutions, establish rigorous model evaluation frameworks, and ensure our LLM-powered systems are grounded, reliable, and free from systematic bias. You will apply techniques such as Retrieval-Augmented Generation (RAG), confidence scoring, knowledge graph integration, and counterfactual testing to ensure our AI systems make trustworthy operational decisions at scale. You will partner closely with software engineers, product managers, and operations leaders to translate scientific innovation into production systems that directly impact Alexa's availability for customers worldwide. You will drive the scientific agenda for your team, mentor fellow scientists, and influence the broader Alexa Excellence organization through your technical leadership and cross-team collaboration. About the team The Alexa Excellence team is at the heart of delivering a world-class Alexa experience to hundreds of millions of customers globally. Within Alexa Excellence, the Alexa Availability team is responsible for ensuring Alexa is always on, always responsive, and always reliable. We own the systems, signals, and science that detect, diagnose, and drive resolution of availability issues at scale — before customers ever notice. We are building the next generation of intelligent availability solutions powered by machine learning, large language models, and advanced statistical modeling. Our work spans anomaly detection, predictive failure modeling, cross-service correlation, and LLM-driven operational intelligence — all operating at the scale and reliability bar that Alexa demands. We operate at the intersection of large-scale distributed systems, applied machine learning, and operational excellence, and we are looking for scientists who can bring both deep technical rigor and a bias for production impact.

Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Alexa's international products and services. Key job responsibilities As an Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our international customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Set up experimentation frameworks for agile model analysis and A/B testing. * Collaborate with partner teams on LLM evaluation frameworks and post-training methodologies. * Contribute to end-to-end delivery of solutions from research to production, including reusable science components. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.

The Amazon Experience and Technology (AET) team provides technology and services that Amazon’s entire global workforce, over 1M people and counting, relies on every day. We operate at the intersection of technology and empathy, reimagining HR conventions. Our customers are our colleagues—and we’re innovating for them. As a survey scientist you will you will design and carry out surveys to address business questions; analyze survey and other forms of data with regression models; perform weighting and multiple imputation to reduce bias due to nonresponse. You will conduct methodological and statistical research to understand the quality of survey data. You will work with economists, engineers, and computer scientists to select samples, draft and test survey questions, calculate nonresponse adjusted weights, and estimate regression models on large scale data. You will evaluate, diagnose, understand, and surface drivers and moderators for key research streams, including (but are not limited to) attrition, engagement, productivity, inclusion, and Amazon culture. Key job responsibilities * Design a scalable global content development and validation strategy to drive more effective decisions and improve the employee experience across all of Amazon * Conduct psychometric and econometric analyses to evaluate integrity and practical application of survey questions and data * Identify research streams to evaluate how to mitigate or remove sources of measurement error * Drive effective collaborations across multi-disciplinary research and product teams * Manage full life cycle of large-scale research programs (Develop strategy, gather requirements, manage and execute)

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers, and is becoming the conversational AI interface for Amazon services with the launch of Alexa for Shopping on Amazon.com and Amazon mobile app. At Alexa Ads, we are creating industry's first and most advanced Agentic Advertising products to drive Agentic Commerce. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa Agentic/Conversational Ads and Personalization. In this role, you will build machine learning models that seamlessly and naturally integrate relevant advertising into the Alexa experience while deeply personalizing user interactions. You will work closely with other scientists, engineers, and product managers to take models from conception to production. Key job responsibilities Design, develop, and evaluate innovative deep learning and GenAI models for natural language processing (NLP), recommendation systems, and personalization. Conduct hands-on data analysis and build scalable ML pipelines. Design and run A/B experiments to measure the impact of new models on customer experience and ad performance. Collaborate with software development engineers to deploy models into high-scale, real-time production environments. About the team We are building a new science team in Bangalore to solve some of the most impactful problems in computational advertising. This isn't about tweaking existing models as we are rethinking how ads are ranked, priced, and personalized across voice-first and screen-first surfaces. These are problems that don't have textbook solutions. Key points to note about the team: 🧪 Greenfield team - you are not joining a mature org with rigid processes. You will shape the science roadmap, pick the problems, and define the culture from day one. 📈 Direct business impact — your models directly drive revenue. No yearly cycles to see if your work matters. 🌏 Global scope, local autonomy — collaborate with scientists and engineers across Seattle, Sunnyvale, and Bangalore, but own your problem space end-to-end. 🎓 Ship AND Publish: We encourage top-tier publications (NeurIPS, ACL, EMNLP, KDD, ICML, WWW) while ensuring your research hits production.

The Amazon Search team creates strong customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, our services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Amazon has grown rapidly and will continue to do so in foreseeable future. Providing a high quality search experience is a unique challenge as Amazon expands to new customers, countries, categories, and product lines. We are seeking a strong applied scientists to join the Vertical Search Relevance India team. This team’s charter is to increase the pace at which Amazon expands and improve the search experience at launch. In practice, we aim to invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models. Key job responsibilities Key job responsibilities * Build machine learning models for Product Search. * Develop new ranking features and techniques building upon the latest results from the academic research community. * Propose and validate hypothesis to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system. * Focus on identifying and solving customer problems with simple and elegant solutions. * Design, develop, and implement production level code that serves billions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment. * Collaborate with other engineers and related teams within A9.com and Amazon.com to find technical solutions to complex design problems. * Take ownership. Understand the needs of various search teams, distill those into coherent projects, and implement them with an eye on long-term impact. * Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects. * Be ambitious. Find and eagerly tackle hard problems. * Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to the latest technologies and vast technical tools and resources of Amazon and will need to learn how to use them effectively. * Be customer focused. Work backwards from customer problems, figure out elegant solutions, and implement them for speed and scalability.

Our team in Amazon Robotics builds robotic systems that perform contact-rich manipulation tasks safely and reliably in complex, unstructured environments — at Amazon scale. Our scientists and engineers push the boundaries of robotic manipulation to handle enormous object diversity, bringing deep expertise across planning, control, perception, and machine learning. We learn from real-world data at a scale that few teams in robotics can access. We are seeking an experienced Senior Applied Scientist to join our Motion Behaviors team. You will drive the development of learned controllers and manipulation behaviors, applying techniques like reinforcement learning and behavior cloning to robots operating in Amazon fulfillment centers. These problems remain unsolved at scale: our robots must improve continuously in environments where simulation alone is insufficient. You will make principled decisions about when learned approaches should replace engineered solutions, and how to select behaviors based on estimated risk. You will collaborate across disciplines and leverage rich operational data to continuously improve system performance. Key job responsibilities • Drive the development of learned controllers and manipulation behaviors, from research prototyping through deployment on production robots. • Research, design, and implement motion planning, control, and decision-making algorithms that improve the performance of deployed systems. • Design and deploy learning pipelines that take policies from simulation training to reliable, real-time execution on physical robots. • Develop models that predict manipulation outcomes and inform behavior selection under uncertainty. • Own the development of scalable, real-time implementations — writing production-quality code and setting engineering standards for the team. • Leverage operational data from deployed systems to systematically identify failure modes and drive policy improvements. • Mentor junior scientists and engineers, raising the bar for applied science rigor and engineering quality. • Represent Amazon in academia through publications and scientific presentations. A day in the life Amazon offers a full range of benefits for you and eligible family members, including domestic partners. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

Do you want to work on Reinforcement Learning (RL) post-training of frontier Large Language Models (LLMs) to revolutionize customer service? Come join the world class researchers and academics in the AWS AI endeavor, and develop the science that powers countless new businesses in cloud computing! AWS, the world-leading provider of cloud services. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and journals. The scientific topics you are going to work on include, but are not limited to: LLM post-training to improve capabilities particularly for instruction following, reasoning over long context, and tool use, etc. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. * Define and implement new automated reasoning features that employ scalable and efficient approaches to solve complex problems using neural learning and symbolic/formal reasoning * Apply software engineering best practices to ensure a high standard of quality for all team deliverables * Work in an agile, startup-like development environment * Deliver high-quality scientific artifacts * Work with the team to help drive business decisions About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.