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Research Scientist, Materials Team, AWS Center for Quantum Computing
US, CA, Pasadena
The Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians on a mission to develop a fault-tolerant quantum computer. You will be joining a team located in Pasadena, CA that conducts materials research to improve the performance of superconducting quantum processors. We seek a Quantum Research Scientist to investigate how material defects affect qubit performance. In this role, you will combine expertise in numerical simulations and materials characterization to study materials loss mechanisms such as two-level systems, quasiparticles, vortices, etc. Key job responsibilities Provide subject matter expertise on integrated experimental and computational studies of materials defects Develop and use computational tools for large-scale simulations of disordered structures Develop and implement multi-technique materials characterization workflows for thin films and devices, with a focus on the surfaces and interfaces Identify material properties that can be a reliable proxy for the performance of superconducting resonators and qubits Communicate findings to teammates, the broader CQC team and, when appropriate, publish findings in scientific journals A day in the life At the AWS CQC, we understand that developing quantum computing technology is a marathon, not a sprint. The work/life integration within our team encourages a culture where employees work hard and also have ownership over their downtime. We are committed to the growth and development of every employee at the AWS CQC, and that includes our research scientists. You will receive management and mentorship from within the team that is geared toward career growth, and also have the opportunity to participate in Amazon's mentorship programs for scientists and engineers. Working closely with other quantum research scientists in other disciplines – like design, measurement and cryogenic hardware – will provide opportunities to dive deep into an education on quantum computing. About the team Our team contributes to the fabrication of processors and other hardware that enable quantum computing technologies. Doing that necessitates the development of materials with tailored properties for superconducting circuits. Research Scientists and Engineers on the Materials team operate deposition and characterization systems in order to develop and optimize thin film processes for use in these devices. They work alongside other Research Scientists and Engineers to help deliver the fabricated devices for quantum computing experiments. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a U.S export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility. About the team Diverse Experiences AWS 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. 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a U.S export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.
Sr Data Scientist , Annapurna Labs, ML Acceleration Power Architecture
US, CA, Cupertino
We are seeking a highly skilled Data Scientist to join our Machine Learning Architecture team, focusing on power and performance optimization for ML acceleration workloads across Amazon's global data center infrastructure. This role combines advanced data science techniques with deep technical understanding of ML hardware acceleration to drive efficiency improvements in training and inference workloads at massive scale. Key job responsibilities ata Analysis & Optimization * Analyze power consumption and performance metrics across all Amazon data centers for machine learning acceleration workloads * Develop predictive models and statistical frameworks to identify optimization opportunities and performance bottlenecks * Create automated monitoring and alerting systems for power and performance anomalies Strategic Planning & Deployment Guidance * Provide data-driven recommendations for server deployments and capacity planning decisions across Amazon's global data center network * Develop optimization scenarios and business cases to improve capacity delivery efficiency to customers worldwide * Support strategic decision-making through comprehensive analysis of power, performance, and cost trade-offs Cross-Functional Collaboration * Partner with software engineering teams to optimize ML frameworks, drivers, and runtime systems * Collaborate with hardware engineering teams to influence chip design, server architecture, and cooling system optimization * Work closely with data center operations teams to implement and validate optimization strategies Research & Development * Conduct applied research on emerging ML acceleration technologies and their power/performance characteristics * Develop novel methodologies for measuring and improving energy efficiency in large-scale ML workloads * Publish findings and contribute to industry best practices in sustainable ML infrastructure
Sr. Applied Scientist, SSG Science
IN, KA, Bengaluru
Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History. Key job responsibilities What will you do? - Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms - Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques - Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine - Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics - Train custom Gen AI models that beat SOTA and paves path for developing production models - Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices - Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys.
Applied Scientist, RBS Tech
IN, KA, Bengaluru
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 independently 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.
Applied Scientist II, RBS Tech
IN, KA, Bengaluru
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.
Senior Applied Scientist, Sponsored Products and Brands Off-Search
US, WA, Seattle
About Sponsored Products and Brands The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-art 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 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 various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value.
Applied Scientist, Books Recommendations
US, WA, Seattle
Passionate about books? The Amazon Books personalization team is looking for a talented Applied Scientist II to help develop and implement innovative science solutions to make it easier for millions of customers to find the next book they will love. In this role you will: - Collaborate within a dynamic team of scientists, economists, engineers, analysts, and business partners. - Utilize Amazon's large-scale computing and data resources to analyze customer behavior and product relationships. - Contribute to building and maintaining recommendation models, and assist in running A/B tests on the retail website. - Help develop and implement solutions to improve Amazon's recommendation systems. Key job responsibilities The role involves working with recommender systems that combine Natural Language Processing (NLP), Reinforcement Learning (RL), graph networks, and deep learning to help customers discover their next great read. You will assist in developing recommendation model pipelines, analyze deep learning-based recommendation models, and collaborate with engineering and product teams to improve customer-facing recommendations. As part of the team, you will learn and contribute across these technical areas while developing your skills in the recommendation systems space. A day in the life In your day-to-day role, you will contribute to the development and maintenance of recommendation models, support the implementation of A/B test experiments, and work alongside engineers, product teams, and other scientists to help deploy machine learning solutions to production. You will gain hands-on experience with our recommendation systems while working under the guidance of senior scientists. About the team We are Books Personalization a collaborative group of 5-7 scientists, 2 product leaders, and 2 engineering teams that aims to help find the right next read for customers through high quality personalized book recommendation experiences. Books Personalization is a part of the Books Content Demand organization, which focuses on surfacing the best books for customers wherever they are in their current book journey.
2026 Data Scientist Internship , Amazon University Talent Acquisition
GB, London
Are you a MS student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for a customer obsessed Data Scientist Intern who can innovate in a business environment, building and deploying machine learning models to drive step-change innovation and scale it to the EU/worldwide. If this describes you, come and join our Data Science teams at Amazon for an exciting internship opportunity. If you are insatiably curious and always want to learn more, then you’ve come to the right place. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science Key job responsibilities As a Data Science Intern, you will have following key job responsibilities: • Work closely with scientists and engineers to architect and develop new algorithms to implement scientific solutions for Amazon problems. • Work on an interdisciplinary team on customer-obsessed research • Experience Amazon's customer-focused culture • Create and Deliver Machine Learning projects that can be quickly applied starting locally and scaled to EU/worldwide • Build and deploy Machine Learning models using large data-sets and cloud technology. • Create and share with audiences of varying levels technical papers and presentations • Define metrics and design algorithms to estimate customer satisfaction and engagement A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, France, Germany, Ireland, Israel, Italy, Luxembourg, Netherlands, Poland, Romania, Spain and the UK). Please note these are not remote internships.
2026 Applied Scientist Intern, Amazon University Talent Acquisition
IL, Tel Aviv
Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note these are not remote internships.
2026 Applied Scientist Intern, Amazon University Talent Acquisition
GB, London
Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK). Please note these are not remote internships.
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