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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.
655 results found
  • US, CA, San Francisco
    Job ID: 10593916
    (Updated 10 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. The Data, Insights, Science and Optimization, Consumer Product and Tech (DISCO CPT) team is looking for a Data Scientist to join a team of Data Scientists, Analytics Leads, Business Intelligence Engineers and Data Engineers who analyze big data, provide analytics and insights as well as build models and algorithms that power product for personalized experiences. The team focuses on accelerating Amazon Music customer growth by empowering Product teams to make sound, customer-centric decisions through data and insights. We build data pipelines, science models, self-service analytics, insights and dashboards, deliver engagement and retention at scale. In this role, you will pioneer and execute advanced analytics and experimentation efforts for the Amazon Music product team. You will work with stakeholders and partners to deliver experimentation insights, author scientific artifacts, build scalable models to advance our analytics and science products. The ideal candidate must be willing to effectively lead science solutions, prioritize across multiple stakeholders and projects and be ready to jump into a fast-paced, dynamic and fun environment. Key job responsibilities 1. Data Scientist I on this role will be a thought partner to Product and Engineering organizations through their expertise in experimentation, statistical modeling and advanced analytics 2. Conceptualize and drive strategic growth areas: app performance, stablity and latency experimentation, Gen AI initiatives, and product excellence. 3. Bridge science, analytics, and engineering to deliver solutions informing strategic decisions on AM technology investments and long-term business performance 4. Drive experimentation, measurement efficiency tooling, and ROI tracking for AM leadership 5. Build and maintain causal models to understand customer sentiment and its impact on key engagement/retention metrics 6. Develop structural and predictive models using data science workflows to deliver measurable customer results A day in the life 1. Lead strategic initiatives across visual and voice experiences, experimentation and customer retention stakeholders 2. Conduct experimentation, build causal models to better understand key drivers for customer retention 3. Evaluate existing metrics and lead deep dives to ensure the right measurement framework is leveraged to measure and enhance user adoption through visual and voice interfaces 4. Partner with product managers to translate business questions into actionable science projects 5. Influence product roadmaps through data-driven insights on customer behavior patterns 6. Identify and resolve customer experience friction points with cross-functional teams Drive adoption of best practices and innovative solutions across the organization
  • US, WA, Seattle
    Job ID: 10593664
    (Updated 5 days ago)
    This is an Applied Scientist position in the AWS Automated Reasoning group. In this role you will work together with leading scientists in the field to develop and apply the latest automated-reasoning techniques, formal methods, and neurosymbolic approaches to ensure safety, security, and correctness of code and services. As Agentic AI becomes the primary method of software development, we are changing the way that computer systems are developed and operated, raising the bar on quality, verifiability, and durability. Automated Reasoning at Amazon is central to maintaining customer trust and improving the customer experience. Automated Reasoning techniques are being applied in diverse areas spanning generative-AI safety, agentic sandboxes, cloud infrastructure verification, software security and verification, cryptographic assurance, and policy validation. The techniques we are applying include automated theorem proving, model checking, constraint solving, and neurosymbolic proof search. This is a unique opportunity to get in early on a rapidly expanding part of AWS and help shape the technology, product, and business. You will have a chance to utilize your deep technical expertise within a fast-paced environment and make a large business and customer impact. Key job responsibilities • Design and implement algorithms and formal methods for automated reasoning, including constraint solving, model checking, static analysis, theorem proving, and program synthesis to verify the correctness, security, and reliability of computing systems. • Solve large or significantly complex problems that require deep knowledge and scientific innovation in your domain; own strategic problem solving and take the lead on design, implementation, and delivery of solutions with long-term quantifiable impact. • Develop new decision procedures, heuristics, and search strategies that improve the scalability and accuracy of verification tools; build and deploy production-grade automated reasoning systems at Amazon scale. • Explore and apply generative AI and machine learning techniques to enhance automated reasoning capabilities, including learning-based heuristics for search and optimization, neural approaches to symbolic reasoning, and methods for verifying the correctness of AI-generated code. • Develop automated reasoning techniques for generative AI and agentic coding systems, including methods for ensuring the safety and alignment of autonomous software agents and applying formal guarantees to large language model outputs. • Conduct original research and publish findings in peer-reviewed venues. • Work with customer teams to understand the nature of their software and the properties they need to establish; identify tools and methods capable of addressing verification needs, including novel analysis capabilities. • Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing deep knowledge and experience; collaborate with partner teams to translate verification capabilities into production systems. • Mentor scientists and engineers on formal methods, neurosymbolic techniques, and best practices for building reliable automated reasoning systems; assist in career development of others.
  • (Updated 4 days ago)
    Do you want to join an innovative team of scientists who use state of art AI & ML techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Selling Partner Trust & Store Integrity Science Team. We are looking for a talented scientist who is passionate to build advanced machine learning systems that help manage the safety of millions of transactions every day and scale up our operation with automation. Key job responsibilities - Innovate with the latest GenAI/LLM/VLM technology to build highly automated solutions for efficient risk evaluation and automated operations - Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to create impactful business value - Learn, explore and experiment with the latest machine learning advancements to create the best customer experience A day in the life you will be working within a dynamic, diverse, and supportive group of scientists who share your passion for innovation and excellence. You'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.
  • US, WA, Seattle
    Job ID: 10599924
    (Updated 0 days ago)
    Take hard sequential decision problems, like delayed rewards, shifting demand and strict business constraints, and turn them into pricing policies that run at Amazon scale. Few places let you test RL ideas on a problem this large. Key job responsibilities Every day, Amazon makes hundreds of millions of pricing decisions. Each one is a choice made with incomplete information: demand shifts, competitors move, inventory runs low, and every price we set changes the data we learn from next. The P2 Optimization Science (P2OS) team builds the science behind these decisions. Our work includes demand response models, the optimization systems that turn them into prices, and the experiments that prove those prices help customers and the business. We're hiring an Applied Scientist to build sequential decision-making methods for pricing. Most pricing systems estimate demand first and optimize second. We want systems that learn while they decide. That means deciding when to explore and when to exploit, how to trade short-term revenue against long-term customer trust, and how to set safe prices in categories where we have little history. You'll work on contextual bandits, reinforcement learning and online optimization problems that most research setups ignore: delayed and noisy rewards, hard business constraints, non-stationary demand, and a catalog too big for a separate model per product. This is an applied role. You'll take methods from offline simulation through online experiments and into production. Your success will be measured by what changes for customers and the business, not by benchmark scores. You'll partner closely with senior scientists, economists, software engineers and product managers. You'll also help shape the team's long-term direction on how Amazon prices adaptively. If you like hard optimization problems with real stakes, and you'd rather ship a method that works than publish one that doesn't, we'd like to talk to you. A day in the life As a Pricing Applied Scientist, you'll shape the prices customers see on a very large share of Amazon's catalog. In a typical week, you might: - Prototype a contextual bandit policy for a product segment with sparse sales history, then stress-test it in simulation against the current production approach. - Dig into why a policy is exploring more than expected and trace it to a reward signal that arrives days late. - Work through a reward design with an economist: how to credit a price change that lifts conversion today but may affect repeat purchases next month. - Review an online experiment readout with your product manager and decide whether the policy is ready to scale or needs another iteration. - Write a short science proposal on a new constraint, like limiting how often a price can change, and estimate its cost to the objective. - Pair with an engineer to make a policy fast enough to update prices in near real time. - Present your findings at the team's science review, or develop them into a paper for a venue like KDD, NeurIPS or EC. About the team The Pricing and Promotions Optimization Science (P2OS) team is the Optimization ‘Application Layer’ within Pricing Sciences. Our team is a small unit of specialized science resources equipped to solve some of the organization’s most ambiguous challenges. Our charter is to develop models to set optimal prices and promotions, shared common tooling across all merchants, rule and policy setting to drive error detection and price sharpness, and innovative price guardrails and incentives to support long-term marketplace health.
  • US, MA, North Reading
    Job ID: 10591833
    (Updated 12 days ago)
    Robotics Applied Scientist II Intern/Co-op (2027) 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? We’re looking for current PhD students with a passion for robotic research and applications to join us in 2027 as Robotics Applied Scientist II Interns/Co-ops to shape the future of robotics and transform automation at Amazon’s scale. By applying to this role, you will be considered for Robotics Applied Scientist II Intern/Co-op (2027) opportunities across various Robotics teams at Amazon with different robotics research focus. Internship positions are available for multiple locations, durations (3 to 6+ months), and year-round start dates (winter, spring, summer, fall). Join us at the forefront of Applied Science, where your contributions will shape the future of Robotics! Key job responsibilities As a Robotics Applied Scientist II Intern/Co-op, you will work alongside global experts to advance the state of the art in robotics and artificial intelligence, tackling innovative problems that bridge the gap between research and real-world robotics implementation to innovate and build solutions on behalf of our customers. We are particularly interested in students with specialization and expertise in one or more of the following research areas: - Robotics - Artificial Intelligence - Robotics Manipulation (e.g., robot arm, grasping, dexterous manipulation, end of arm tools/end effector) - Autonomous Mobile Robots - Mobile Manipulation - Multi-Robot Coordination - Autonomous Navigation - Locomotion - Motion/Path Planning - Controls - Perception - Sensing - Robot Learning - Machine Learning - Computer Vision - Large Language Models (LLM), Vision-Language-Action Models (VLA), Vision-Language-Models (VLM) - World Models - Human-Robot Interaction - Robotics Simulation - Optimization - And related! Key responsibilities may include: - Develop novel, scalable algorithms and/or modeling techniques that advance the state-of-the-art in science areas such as robotics, artificial intelligence, or related - Tackle challenging, innovative research problems within robotics, artificial intelligence, or related that bridge the gap between theoretical advancement and practical robotics implementation - Collaborate with cross-functional teams to solve complex problems, and to communicate research findings clearly, leveraging your expertise in robotics, artificial intelligence, or related - Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment - Leverage AI-powered tools where applicable to accelerate research, experimentation, and prototyping. - Critically review and validate outputs from AI tools and automated systems. About the team Explore Robotics Teams at Amazon At Amazon, robotics is where innovative research meets real-world deployment. There are many different specialized robotics teams, including the few highlighted below. Learn more about Robotics at Amazon here: https://www.amazon.science/research-areas/robotics Fulfillment Technologies and Robotics We build dynamic partnerships between people and intelligent machines. This intricate collaboration helps Amazon fulfill orders with unmatched accuracy. Working in symphony with our robotic technology, you’ll have the opportunity to extend your technical capabilities by working alongside some of the industry’s most advanced technologies. This includes our fleet of autonomous mobile robots, sophisticated control software, and technologies like language perception, machine learning, object recognition, and semantic understanding of commands. These technologies help us deliver an ever-improving customer and employee experience, as well as improve the safety of our facilities. Amazon Robotics Amazon Robotics is at the epicenter of robotics innovation. We design, test, and build mobile robots and mechatronic systems. Our offices, labs, test floors, and factories are close together, which means we can design the hardware, write the code, test, build, and watch it all come to life. Our areas of focus include advancements in autonomous mobility, AI, robotic management software, and much more. Fauna Fauna is focused on building capable, safe, and genuinely delightful robots for everyday life. Fauna’s goal is simple: make robots people actually want to live and interact with everyday. Fauna develops tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Fauna’s work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but overall experience. Amazon Fulfillment Technologies Amazon Fulfillment Technologies develops tech solutions that create network optimizations for all Amazon sites worldwide. We own network infrastructure and devices in all buildings and labor planning and scheduling technology for fulfillment centers in North America and Europe.
  • (Updated 12 days ago)
    The FAIM (Full Funnel Agentic Intelligence and Models) builds the agentic AI systems behind next-generation advertising. The team develops multimodal foundation models and LLM-driven agents that power shopper understanding, audience-aware creative generation, and agentic advertising workflows. As a Principal Applied Scientist for the FAIM team, you will invent the models that help advertisers achieve desired outcomes. Today's state of the art models can setup ad campaigns to a specification, but do not understand advertising strategy well enough to help with abstract goals that real advertisers ask about like "how can I make more money." This is a rare charter to build foundational optimization science where little exists today, spanning campaign recommendation, cross-product budget allocation, incrementality measurement, and long-term-sales modeling. You will set technical direction for a growing team, partner with engineering and product to take models from research to production at Amazon scale, and directly move advertiser ROAS and new-to-brand growth. In this role you will - Own the science vision for developing evaluations of the Ads Agent - Partner with scientists from across Ads to develop best practices for evaluating agent performance both online and offline - Raise the science bar for all agent evaluations developed in Ads. - Own establishing a data driven foundation for making decisions about when new features are ready to launch in Ads Agent. Key job responsibilities - Define the long-term scientific vision for agent evaluations in Ads - Translate ambiguous advertiser needs and competing objectives into a concrete science roadmap. - Invent, prototype, and productionize machine learning and optimization solutions for joint budget allocation across sponsored ad products, spanning the shopper journey from awareness to purchase. - Develop rigorous approaches to incrementality measurement and long-term-sales modeling that ground optimization in true advertiser value. - Design and lead large-scale experiments and analyses to validate hypotheses and guide product direction. - Partner closely with engineering and product to define technical contracts, data schemas, and serving systems that carry models into production. - Raise the technical bar across science and engineering through mentorship, design reviews, and hands-on collaboration. - Grow scientific talent and publish impactful research internally and at top-tier venues.
  • US, NY, New York
    Job ID: 10593798
    (Updated 10 days ago)
    The Supply Chain Optimization Technologies (SCOT) organization owns Amazon’s global inventory management systems: we decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We do this for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. Our systems are built entirely in-house, and are automated large-scale business operations, inventory and supply chain planning and optimization systems. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the efficiency of Amazon's inventory investment and placement decisions. The Inbound Systems team within SCOT seeks a Research Scientist to innovate in SCOT inbound placement decision and capacity management systems. As a research scientist, you will use your experience to initiate the design, development, execution and implementation of scientific research projects. Working closely with fellow scientists, BI engineers and product managers, you will use your experience in modeling, statistics, and simulation to design models of new policies, simulate their performance, and evaluate their benefits and impacts to cost, reliability, and speed of our fulfillment network. Our teams are looking for experience in network and combinatorial optimization, statistical inference, and machine learning. This position requires superior analytical thinking, and ability to apply their technical and statistical knowledge to identify opportunities for real world applications.
  • (Updated 17 days ago)
    We're building systems that turn research into real world impact. We're advancing the intelligence behind how customers converse, connect and interact with Alexa across the globe and we're tackling complex conversational AI challenges with state of the art GenAI systems. We're looking for PhD students across multiple research domains to invent, design, and implement state of the art solutions for never before solved problems. Your work here won't just stay in a notebook, it ships to production and reaches customers worldwide. Check out the details below including the job responsibilities, team details, and basic qualifications before submitting your application. You can find more information about the Amazon Science community as well as interview preparation tips 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 should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end. Projects may include developing and implementing real-time AI services, conducting comprehensive analysis of GenAI algorithms and methodologies or contributing to the creation of reliable, efficient code for production systems that serve millions of users — depending on the team you're matched with. Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship, subject to performance evaluation and headcount availability. Further benefits of an Amazon Science internship include; - All of our internships offer a competitive salary - Interns are paired with an experienced manager and mentor(s) - Interns get invited to different intern program or office events - Interns can build their professional and personal network with other Amazon Scientists - Interns can potentially publish work at top tier conferences About the team You'll submit a single application and we'll match you with science teams best aligned with your research interests. Applications are reviewed on a rolling basis, and your application stays active until we find a team match or confirm there are no matches available. Start dates are available throughout the year for durations of between 3–6 months. Please note, each team has different start date and duration preferences — your recruiter will confirm the preferences of the team you're matched with prior to interviewing. We offer science internships in multiple locations across the EMEA region and you can indicate your interest in all these locations by applying here (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note we do not offer remote internships.
  • (Updated 5 days ago)
    Are you passionate about using AI to protect and elevate the shopping experience for hundreds of millions of customers? We're looking for a Sr. Applied Science Manager to lead the Sponsored Products and Brands, Search Relevance team, ensuring that every product recommendation shoppers see on our search results page is relevant, trustworthy, and genuinely useful. In this role, you'll be at the forefront of defining what a great search experience looks like by inventing entirely new ways to help customers understand why a product matches their needs. Safeguard the Customer Experience - Lead the development of predictive models that identify and mitigate irrelevant, misleading, or low-quality product recommendations across search placements - Design and scale AI-powered systems whose outputs are used to continually improve the search results - Expand the definition of search quality beyond query-ASIN relevance to encompass shopper preferences, page-level context, and overall experience coherence Define and Measure Search Quality at Scale - Own the development and ongoing measurement of customer experience metrics as reported to senior leadership - Partner with leaders across Search, Retail, and Advertising organizations to align on metric definitions and establish independent measurement standards where needed - Build scalable measurement frameworks that anticipate evolving search presentation formats and proactively adapt to them Invest in State-of-the-Art AI Infrastructure - Drive investment in AI infrastructure and systems that reduce the cost of measuring and monitoring CX metrics across all placements and marketplaces - Build increasingly precise AI models that minimize human effort for auditing, training data generation, and placement-specific customization - Make strategic build-vs-reuse decisions by staying closely connected to peer teams across the organization Invent New Product Experiences - Create novel product presentation experiences that help shoppers understand the differential value of each result — through intelligent selection of images and titles, contextual explanations, and visual indicators such as badges and tags - Partner with peer teams to share learnings and advocate for the adoption of successful innovations beyond your immediate scope Lead and Influence Across the Organization - Manage and grow a team of applied scientists, engineers, and product managers - Partner with senior leaders (Director-level and above) across multiple organizations to drive alignment on shared goals and cross-functional initiatives - Represent search quality and customer experience in executive-level reviews and reporting cadences
  • US, WA, Seattle
    Job ID: 10589082
    (Updated 14 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 that support 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!

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.