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Careers

At Amazon, we believe that scientific innovation is essential to being the most customer-centric company in the world. Our scientists' ability to have an impact at scale allows us to attract some of the brightest minds across diverse fields including artificial intelligence, robotics, computer vision, economics, and sustainability. Join us in pioneering solutions to complex challenges that not only delight our customers but also help define the future of technology.
  • The program is designed for academics from universities around the globe who want to work on large-scale technical challenges while continuing to teach and conduct research at their universities.
  • The program offers recent PhD graduates an opportunity to advance research while working alongside experienced scientists with backgrounds in industry and academia.
  • Our internship roles span research areas to provide hands-on experience working alongside world-class scientists and engineers to advance the state of the art in your field.
719 results found
  • US, WA, Seattle
    Job ID: 10483669
    (Updated 9 days ago)
    Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at https://www.amazon.com/music. Key job responsibilities As an Applied Scientist, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical 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. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Other responsibilities include: - Collaborate with scientists, engineers, and product managers to define and frame business problems as ML or optimization tasks. - Build, train, and evaluate models using large, complex datasets. - Implement scalable data pipelines and model-serving systems. - Analyze experimental results, draw insights, and refine models to improve accuracy and robustness. - Communicate findings and recommendations to technical and non-technical audiences. - Continuously learn and apply new algorithms and techniques to improve existing systems. A day in the life Everyone on our team has a meaningful impact on product features, new directions in music streaming, and customer engagement. We are looking for new team members across a variety of job functions including software engineering/development, marketing, design, ops and more. Come join us as we make history by launching exciting new projects in the coming year. About the team The Amazon Music – Catalog [MusicIQ] Team develops sophisticated models for understanding music across multiple dimensions: sonic, thematic, cultural, lyrical, etc. This team aims to unify this deep music knowledge that will power intelligent music experiences across Amazon Music. Ultimately, the goal of our team is to delivery a musically credible experience, which will help grow engagement across all customers, but also delight the fans!
  • US, WA, Seattle
    Job ID: 10475203
    (Updated 12 days ago)
    The Amazon Smart Vehicles (ASV) science team is seeking a passionate and skilled Applied Scientist with extensive expertise in advanced LLM technologies. This role involves innovating in rapidly evolving areas of AI research, focusing on creating personalized services to enhance drivers' and passengers' experiences. Your work will aim to simplify their lives, keep them informed, entertained, productive, and safe on the road, with direct application to prominent Amazon products. If you have extensive expertise in LLMs, natural language processing, and machine learning, along with experience in high-performing research teams, this could be the perfect opportunity for you. Our dynamic and fast-paced environment demands a high level of independence in decision-making and the ability to drive ambitious research initiatives through to production. You will collaborate closely with other science and engineering teams, as well as business stakeholders, to ensure your contributions are both impactful and delivered with maximum efficiency. Key job responsibilities - Leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI) - Work with talented peers to lead the development of novel algorithms and modeling techniques to advance the state of the art with LLMs - Collaborate with other science and engineering teams as well as business stakeholders to maximize the velocity and impact of your contributions About the team This is an exciting moment to lead in AI research. As part of the Amazon Smart Vehicles science team, you have the opportunity to shape the future by enhancing information-driven experiences for Amazon customers around the globe. Your work will directly influence customers through innovative products and services powered by language and multimodal technology!
  • (Updated 19 days ago)
    Join us at the forefront of Amazon's sustainability initiatives to work on environmental and social advancements that support Amazon's long-term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people who are passionate about making a meaningful impact on communities and the environment while helping shape the future of sustainable business practices. The Worldwide Sustainability (WWS) organization capitalizes on Amazon's scale and speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally and drive solutions that enable our customers, businesses, and the world to become more sustainable. Through innovative programs and strategic partnerships, we're creating lasting positive change in the communities where we operate while advancing Amazon's commitment to environmental stewardship and social responsibility. We are looking for a robotics scientist to build and operate the first autonomous materials discovery laboratory at Amazon. This role combines deep robotics expertise (motion planning, control, platform integration) with modern Physical AI approaches (vision-language-action models, sim-to-real transfer, agentic orchestration). You will design autonomous experimental workflows that integrate dexterous robotic platforms, analytical instruments, and AI-driven hypothesis generation into a closed-loop discovery pipeline — where foundation models drive hypothesis generation and experimental planning, validated on real hardware under real chemistry. This is not a pure research role. You will work directly with physical robots, laboratory instruments, and deployment pipelines. The work is expected to be published, but the primary measure of success is a working autonomous platform that generates scientific results. Materials science expertise is not required — the team includes domain scientists. What matters is strong AI and robotics foundations, scientific curiosity, and the drive to ship. Key job responsibilities - Develop, train, and benchmark robotic manipulation policies for materials synthesis and characterization using modern policy architectures (VLA architectures, diffusion policies). - Design and execute sim-to-real transfer strategies including domain randomization, physics parameter tuning, and visual domain adaptation for laboratory robotic systems. - Integrate robotic platforms and laboratory instruments into automated workflows via APIs (SiLA 2, or equivalent), building real-time data pipelines for multimodal experimental outputs. - Architect policy training pipelines combining teleoperation data, synthetic demonstrations, reinforcement learning, and imitation learning for dexterous lab manipulation. - Build production-grade agentic runtime systems — failure detection, retry logic, exception handling, and human-handoff protocols — for unattended experimental sessions. - Design and execute autonomous experimental campaigns applying active learning, Bayesian optimization, or RL to drive iterative materials discovery. - Drive technical design reviews and set scientific direction for the autonomous lab platform. A day in the life You build the Physical AI systems that power robotics in autonomous science lab, one where foundation models generate hypotheses, robots execute experiments, and closed-loop optimization discovers materials that did not exist yesterday. You train manipulation policies in simulation, transfer them to a physical cobot, and watch real chemistry validate (or invalidate) an AI-generated theory. The signal here is not a metric on a dashboard; it is a synthesizing and testing novel material with measurable sustainability impact. If you want your research to have physical weight, this is the lab. About the team Sustainability Science and Innovation (SSI) is a multi-disciplinary research team within WW Sustainability combining science, ML, economics, and engineering. The autonomous laboratory is a new capability being built from the ground up. You will work alongside computational materials scientists, chemists, and ML engineers — with access to AWS-scale compute and Amazon's supply chain for hardware. The work targets sustainability outcomes across packaging, building materials, and alternative fuels.
  • (Updated 8 days ago)
    The R2L team is responsible for building the next generation supply chain for Amazon’s world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes! R2L Science & AI team sits under R2L and is a central team for all Data Science/AI related asks. We are looking for an experienced and curious data scientist with effective superior analytical skills to inform the data science charter of the team. Key job responsibilities We are looking for an experienced and curious data scientist with effective superior analytical skills to inform the data science charter of the team. This position is critical in helping us learn more about our data and finding opportunities to delight customers with data driven insights and machine learning models. The Data Science and Analytics team owns data science, data engineering, and business intelligence. You will be supporting multiple business and technical stakeholders with high velocity analytics. This role is uniquely positioned in the team as we have a growing need for looking around corners, prioritizing opportunities using data driven insights, and finding solutions to these opportunities using different machine learning techniques and causal inference models. You will be diving deep in our data and have a strong bias for action to quickly produce high quality data analyses with clear findings and recommendations. As part of our journey to learn about our data, some opportunities may be a dead end and you will be balancing unknowns with delivering results for our customers. A day in the life 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! Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. 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 Learn more about our benefits here: https://amazon.jobs/en/internal/benefits/us-benefits-and-stock
  • US, WA, Seattle
    Job ID: 10464441
    (Updated 19 days ago)
    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. As for Brand Stores (e.g., amazon.com/lego and 1MM+ more), we are the exclusive destination for brand owners to showcase their content and product catalog through custom creative, seamlessly integrated with Amazon Stores and ads products, attracting millions of daily visits. We're reinventing how brands and shoppers connect. Using generative AI, we're building the next generation of brand-centric storefronts, reimagining store creation, optimization, performance analysis, and customer insights through state-of-the-art GenAI technologies. As a Senior Applied Scientist on the team, you'll own the science strategy and hands-on development of AI-powered brand experiences at Amazon scale. You'll operate at the intersection of frontier research and high-impact production systems, with the autonomy to shape what we build, how we build it, and where we invest next. This role combines science leadership, technical depth, product intuition, and business acumen. #GenAI Key job responsibilities If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, this is the role. * Build intelligent systems for Brand Stores. Develop AI-powered solutions leveraging generative models to optimize both advertiser and shopper experiences, measurably improving Brand Store performance. * Define a multi-year science vision and roadmap. Translate customer needs into actionable plans for applied scientists and engineering teams, blending science leadership, technical depth, product intuition, and business acumen. * Architect ahead of the GenAI curve. Anticipate where generative AI is heading over a multi-year horizon and position solutions to capitalize on compounding advances. * Experiment rigorously. Design and run A/B experiments grounded in deep data analysis to validate hypotheses and quantify impact. * Communicate with clarity. Translate complex technical ideas into compelling narratives for both technical and non-technical audiences. About the team 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. The Brand Stores team within Sponsored Products and Brands is chartered to create agentic brand store building experience, automating brand store creation, personalization, and optimization across global marketplaces, serving millions of brand owners world-wide.
  • The Shopping Convo Foundations Team - Pre-purchases Science is looking for an Applied Scientist with expertise in Artificial Intelligence and Machine Learning to drive scientific innovation that expands Amazon's product catalogue. Our goal is to leverage AI/ML solutions to enhance catalogue coverage with high precision. In this role, you will research and develop novel machine learning approaches to solve complex catalogue expansion and product attribute challenges. You will design and develop state-of-the-art ML models, conduct rigorous experimentation, and translate scientific breakthroughs into production-ready solutions. You will work closely with ML Engineers and Software Development Engineers to optimize model performance, ensure scalability, and deploy low-latency solutions at Amazon scale.
  • (Updated 28 days ago)
    Do you want to create the greatest-possible worldwide impact in Robotics? Amazon has the world's most exciting treasure trove of robotics challenges. At Amazon Robotics we build high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans—at Amazon scale. Amazon Robotics invents and scales AI systems for robotics in fulfillment. Our mission is to enable robots to interact safely, efficiently, and fluently high density real-world fulfillment centers. Our AI solutions enable robots to learn from their own experiences, from each other, and from humans to build intelligence that feeds itself. We hire and develop subject matter experts in AI with a focus on 3D perception, computer vision, deep learning, and generative modeling. We target high-impact algorithmic unlocks in areas such as 3D scene understanding and completion, semantic occupancy prediction, multi-view 3D reconstruction, depth estimation, shape completion, and real-time inference - all of which have high-value impact for our current and future fulfillment networks. We are seeking an passionate, hands-on, seasoned Senior Applied Scientist who will be deep in code and algorithms; who is technically strong in building scalable 3D perception systems across semantic scene completion, encoder-decoder and transformer architectures (e.g., VoxFormer, MonoScene), voxelized occupancy prediction, panoptic and instance segmentation, depth estimation, point cloud processing, and multi-view fusion. As a Senior Applied Scientist, you will contribute to the research and development of advanced 3D perception pipelines that enable robots to reason about occluded and partially observed environments; your work along with other top-notch scientists and engineers will deliver the world's most scalable and robust robotic perception systems. You will drive ideas to products using paradigms such as 3D generative models, query-based transformers, masked autoencoder-style completion, and scalable pseudo-ground-truth data generation. As a Senior Applied Scientist, you will also help lead and mentor our team of applied scientists and engineers. You will take on challenging perception problems - such as completing 3D bin scenes from partial observations, integrating multi-camera inputs, and optimizing inference latency for edge deployment - distill requirements, and then deliver solutions that either leverage existing academic and industrial research or utilize your own out-of-the-box but pragmatic thinking. In addition to coming up with novel solutions and prototypes, you will directly contribute to implementation while you lead. A successful candidate has excellent technical depth in 3D computer vision, scientific vision, project management skills, great communication skills, and a drive to achieve results in a collaborative team environment. You should enjoy the process of solving real-world problems that, quite frankly, haven't been solved at scale anywhere before. Along the way, we guarantee you'll get opportunities to be a disruptor, prolific innovator, and a reputed problem solver—someone who truly enables AI and robotics to significantly impact the lives of millions of consumers. Key job responsibilities - Architect, design, and implement 3D perception models - including encoder-decoder networks, query-based transformers, and generative architectures- for semantic occupancy prediction and scene completion on robotic platforms. - Own the end-to-end model lifecycle: develop scalable training pipelines, optimize inference latency for ARM-based edge processors, and deploy production models that meet real-time performance targets. - Design and scale pseudo-ground-truth data generation pipelines - both heuristic-based and learning-based (e.g., SAM3D, shape completion) to produce curated training samples using SageMaker infrastructure. - Drive multi-view perception integration by fusing multiple view camera inputs for robust 3D reconstruction in partially observed and occluded bin environments. - Influence the team's technical strategy and contribute to the long-term vision and roadmap for 3D perception in fulfillment robotics. - Partner with cross-functional stakeholders across engineering, science, and operations teams to define requirements, iterate on system design, and deliver end-to-end solutions from research prototype to production deployment. - Maintain high standards by participating in design and code reviews, designing for fault tolerance and operational excellence, and creating mechanisms for continuous improvement. - Prototype and validate concepts through simulation, synthetic data evaluation, and live robotic workcell testing using 3D metrics (mIoU, IoU) and affordance-based evaluation frameworks. - Mentor applied scientists and engineers, raise the technical bar, and foster a culture of scientific rigor and rapid experimentation. 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! About the team https://www.youtube.com/watch?v=2X4CU3jmw-g The Vulcan Stow Perception team builds the visual intelligence that enables Amazon's next-generation robotic stow systems to understand and interact with densely packed fulfillment environments. We own the full perception stack—from raw sensor input to actionable 3D scene representations—powering robots that autonomously stow millions of items daily across Amazon's global network. Our team tackles some of the hardest unsolved problems in 3D robotic perception: completing occluded scenes from partial observations, generating real-time semantic occupancy predictions, fusing multi-camera inputs (pedestal and end-of-arm tool), and producing sub-250ms mesh reconstructions that drive downstream manipulation decisions. We operate at the intersection of research and production-scale deployment, building systems that must be both scientifically rigorous and operationally bulletproof. We are a tight-knit group of applied scientists and engineers who ship models that run on real robots in real fulfillment centers—not just papers or prototypes. Our culture values technical depth, rapid experimentation, and end-to-end ownership. If you want to push the boundaries of 3D computer vision, work with transformer and generative architectures at the frontier, and see your work directly impact how millions of packages reach customers - this is the team.
  • (Updated 35 days ago)
    As an Applied Scientist II in the Alexa Conversational Modelling Intelligence team within Alexa AI, you will drive model post-training for Large Language Models that power Alexa+. You'll adopt and adapt state-of-the-art techniques — including supervised fine-tuning, reinforcement learning, preference optimization, and knowledge distillation — running rigorous experiments and translating findings into production-ready solutions that directly improve the customer experience for millions of users worldwide. You will own the full model development cycle from data curation through training, evaluation, and deployment. Your day-to-day will involve developing evaluation methods and metrics, diagnosing model defects, optimizing model training pipelines, and iterating on recipes to move concrete quality and efficiency benchmarks. You'll write clean, reproducible code, contribute to shared tooling, and collaborate closely with scientists and engineers to bring models from experimentation to scale. You are technically curious, experiment-driven, and motivated by real customer impact. You are an expert in LLM post-training. You will also advance the state of the art by publishing at top-tier NLP/ML conferences (ACL, EMNLP, NeurIPS, ICML, ICLR) — contributing to the broader research community while grounding your work in measurable outcomes. Key job responsibilities * Own the full model development cycle — from data curation through training, evaluation, and deployment. * Develop and apply post-training techniques: supervised fine-tuning, reinforcement learning, preference optimization, and knowledge distillation. * Build evaluation methods and metrics, and diagnose model defects to target the highest-impact improvements. * Optimize model training pipelines and iterate on recipes to move concrete quality and efficiency benchmarks. * Write high-quality documentation on methods and experiment outcomes, and communicate findings clearly to stakeholders. A day in the life Post-training is one of the most active frontiers in LLMs right now. The field has moved from scaling pretraining to getting more out of models afterward through RL, reasoning recipes, and preference optimization. You'll work on these techniques directly, on a product used by millions of customers every day. A typical day: review overnight training runs and dashboards, dig into model defects to form hypotheses, then curate data and iterate on a recipe, improving shared tooling along the way. You'll sync with scientists and engineers to unblock the path to production, and write up your findings for stakeholders. It's fast-moving — a good idea can reach millions of customers within weeks. About the team The Alexa Conversational Modelling Intelligence team builds industry-leading LLM-based conversational technologies that customers love. Our mission is to push the envelope in LLMs for Alexa to deliver the best-possible customer experience. As an Applied Scientist, you'll contribute directly to that mission through model development and experimentation.
  • US, CA, Sunnyvale
    Job ID: 10460378
    (Updated 37 days ago)
    MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Manager III, Economist Job Location: Sunnyvale, California Job Number: AMZ9803624 Position Responsibilities: Independently manage a team of economists and/or scientists in developing strategic economic analyses and demand estimation models. Translate business questions into econometric methodologies and causal inference analyses. Communicate economic insights to non-technical audiences to guide strategic-level, high-impact business decisions. Scale economic models through cross-functional collaboration with engineering teams. Establish scientific quality standards and research priorities. Drive operational efficiency and research excellence across the team. 40 hours / week, 8:00am-5:00pm, Salary Range: $201,300/year to $272,400/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
  • (Updated 0 days ago)
    Success in any organization begins with its people and having a comprehensive understanding of our workforce and how we best utilize their unique skills and experience is paramount to our future success. WISE (Workforce Intelligence powered by Scientific Engineering) delivers the scientific and engineering foundation that powers Amazon's enterprise-wide workforce planning ecosystem. Addressing the critical need for precise workforce planning, WISE enables a closed-loop mechanism essential for ensuring Amazon has the right workforce composition, organizational structure, and geographical footprint to support long-term business needs with a sustainable cost structure. We are looking for a Applied Scientist to join our ML/AI team to work on Advanced Optimization and LLM solutions. You will partner with Software Engineers, Data Engineers and other Scientists, TPMs, Product Managers and Senior Management to help create world-class solutions. We're looking for people who are passionate about innovating on behalf of customers, demonstrate a high degree of product ownership, and want to have fun while they make history. You will leverage your knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages to analyze and translate the data into meaningful insights. You will have end-to-end ownership of operational and technical aspects of the insights you are building for the business, and will play an integral role in strategic decision-making. Further, you will build solutions leveraging advanced analytics that enable stakeholders to manage the business and make effective decisions, partner with internal teams to identify process and system improvement opportunities. As a tech expert, you will be an advocate for compelling user experiences and will demonstrate the value of automation and data-driven planning tools in the People Experience and Technology space. Key job responsibilities - Engineering execution - drive crisp and timely execution of milestones, consider and advise on key design and technology trade-offs with engineering teams - Priority management - manage diverse requests and dependencies from teams - Process improvements – define, implement and continuously improve delivery and operational efficiency - Stakeholder management – interface with and influence your stakeholders, balancing business needs vs. technical constraints and driving clarity in ambiguous situations - Operational Excellence – monitor metrics and program health, anticipate and clear blockers, manage escalations To be successful on this journey, you love having high standards for yourself and everyone you work with, and always look for opportunities to make our services better. Internal job description

Science at Amazon around the world

Amazon scientists are working on large-scale technical challenges in a variety of research areas across the globe. Use the pins below to learn more about the customer-obsessed science being conducted at some of our research locations.
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Academia

Amazon collaborates with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly across all sectors of society.