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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.
632 results found
  • US, WA, Seattle
    Job ID: 10580389
    (Updated 28 days ago)
    Are you passionate about using data and machine learning to improve how Amazon reaches customers? The Customer Targeting team is looking for an Applied Scientist to build the science behind the targeting of Amazon's marketing initiatives across channels and ad formats. You will turn business questions into modeling problems and take your solutions from prototype to production, working closely with senior scientists, engineers, and business partners. We are moving targeting toward outcome-based optimization and an AI-native, agentic way of working. In this role you will work on online optimization and reinforcement learning, incrementality modeling, and the next generation of our segment-based targeting model. You will also help build agentic workflows that make targeting decisions transparent and bring science recommendations to the people using them. The right candidate has strong quantitative and statistical skills, hands-on experience with modern ML methods, and is comfortable working through ambiguity in a fast-paced environment. You pay close attention to detail, learn quickly, and work well in a highly collaborative team. Key job responsibilities - Build online optimization (e.g., TSO, bandits) and reinforcement learning methods that optimize targeting decisions for business outcomes rather than proxy metrics. - Develop incrementality and uplift models that estimate the causal impact of targeting, and use them to improve who we target and how much we spend. - Improve the existing segment-based targeting model: engineer and evaluate new features, migrate it to new model architectures, and build automated feedback loops that retrain and improve the model from observed outcomes. - Contribute to the intelligence layer of our agentic system: build components that explain targeting decisions and propose science-driven solutions to business partners. - Design and analyze experiments (A/B tests, causal inference methods) to measure the incremental impact of targeting changes. - Write production-quality model code and partner with engineers to deploy, monitor, and maintain models. - Present methods and results clearly, backed by data, with actionable recommendations for science and business stakeholders. About the team Predictive Targeting builds the systems that decide who sees Amazon's marketing content, and how often, across Amazon's stores and channels. We are engineers and scientists working on one shared problem: making sure customers see the most relevant and engaging marketing, and making each campaign better than the last.
  • US, VA, Arlington
    Job ID: 10579474
    (Updated 3 days ago)
    PXT Central Science is seeking an exceptional Data Scientist to join our team. The ideal candidate will thrive in a dynamic, multifaceted role where you'll translate complex business challenges into rigorous quantitative frameworks, extract actionable insights from structured and unstructured datasets, and architect science-backed, scalable solutions that elevate the experience of our 1 million+ employees worldwide. If you're energized by the opportunity to apply data science to our mission of making Amazon Earth's Best Employer, we want to hear from you. Key job responsibilities • Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience. • Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliverable measurable impact. • Author and maintain detailed technical documentation related to the projects you drive. • Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations • Stay current with emerging methods and technologies, and implement them strategically to amplify the team’s impact. About the team The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science, engineering, and UX to develop and deliver solutions that measurably achieve this goal.
  • (Updated 29 days ago)
    The Amazon Web Services (AWS) Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Scientist on the Materials team, focused on materials integration and process development for superconducting quantum processors. You will join a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers working at the forefront of quantum computing. You should have expertise in thin-film deposition, semiconductor integration processes, and materials characterization, with a strong understanding of how device topography and process sequences constrain materials integration choices. Candidates with a track record in materials integration for superconducting or semiconductor devices at wafer scale will be preferred. We are looking for candidates with strong scientific and engineering principles, resourcefulness and a bias for action, superior problem solving, and excellent communication skills. As an Applied Scientist at CQC, you will be expected to drive materials integration R&D from process development through hardware demonstration and stay abreast of advances in superconducting materials and semiconductor manufacturing. Key job responsibilities You will develop and optimize materials for superconducting quantum hardware, with an emphasis on thin-film deposition processes and materials solutions that enable integration architectures for scaling qubit density. This includes establishing process-structure-property relationships for production-relevant films and interfaces, qualifying new tools and process modules, and designing integration schemes compatible with larger wafer formats. You will coordinate with cross-functional teams to translate materials advances into production, and publish results in scientific journals when appropriate.
  • (Updated 29 days ago)
    Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly. The Mission Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. What You'll Build You'll pioneer breakthrough solutions in Responsible AI at Amazon's scale. Imagine training models that set new safety standards, designing automated testing systems that hunt for vulnerabilities before they surface, and certifying the systems that power millions of daily conversations. You'll create intelligent evaluation systems that judge responses with human-level insight, build models that truly understand what makes interactions safe and delightful, and craft feedback mechanisms that help Alexa+ grasp the nuances of complex customer conversations. Here's where it gets even more exciting: you'll build AI agents that act as your team's safety net—automatically detecting and fixing production issues in real-time, often before anyone notices there was a problem. Your innovations won't just improve Alexa+; they'll fundamentally shape how it learns, evolves, and earns customer trust. As Alexa+ continues to delight customers, your work ensures it becomes more trustworthy, safer, and deeply aligned with customer needs and expectations. Your work directly protects customer trust at Amazon's scale. Every innovation you create—from novel safety mechanisms to sophisticated evaluation techniques—shapes how millions of people interact with AI confidently. You're not just building products; you're defining industry standards for responsible AI. This is frontier research with immediate real-world impact. You'll tackle problems that require innovative solutions: training models that remain truthful and grounded across diverse contexts, building reward models that capture the nuanced spectrum of human values across cultures and languages, and creating automated systems that continuously discover and address potential issues before customers encounter them. You'll collaborate with world-class scientists, product managers, and engineers to transform state-of-the-art ideas into production systems serving millions. What We're Looking For * Deep expertise in state-of-the-art NLP, Large Language Models * Track record of building scalable ML systems * Passion for impactful research—where frontier science meets real-world responsibility at scale * Excitement about solving problems that will shape the future of AI Ready to work on AI safety challenges that define the industry? Join us. Key job responsibilities The Responsible AI (RAI) team is at the forefront of building AI systems that are safe, ethical, and trustworthy. As a Senior Applied Scientist, you'll lead the scientific vision for end-to-end Responsible AI solutions—pioneering algorithms that eliminate false information, designing frameworks that hunt down vulnerabilities before bad actors find them, and developing models that understand human values across every culture we serve. Working alongside world-class engineers and scientists, you'll push the boundaries of model training, building agentic AI systems that coordinate multiple autonomous agents to solve complex safety challenges—transforming bold research into production systems that protect millions of customers daily while withstanding attacks and delivering exceptional experiences. But here's what makes this role truly special: you'll shape the future. You'll lead efforts to identify, define, and mitigate risks early—protecting customers before they're impacted—and mentor the next generation of AI safety experts. You'll design multi-agent architectures where distributed AI systems exhibit emergent collective intelligence while maintaining human oversight and control. Every innovation you drive—from consensus-driven reasoning frameworks to sophisticated orchestration patterns—will set new standards for trustworthy AI at the world's largest scale. A day in the life As a Responsible AI Scientist, you're at the frontier of AI safety—experimenting with breakthrough techniques that push the boundaries of what's possible. You partner with engineering to transform research into production-ready solutions, tackling complex optimization challenges. You brainstorm with Product teams, translating ambitious visions into concrete objectives that drive real impact. Your expertise shapes critical deployment decisions as you review impactful work and guide go/no-go calls. You mentor the next generation of AI safety leaders, watching ideas spark and capabilities grow. This is where science meets impact—building AI that's not just intelligent, but trustworthy and aligned with human values. About the team Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.
  • (Updated 29 days ago)
    Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly. The Mission Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. What You'll Build You'll pioneer breakthrough solutions in Responsible AI at Amazon's scale. Imagine training models that set new safety standards, designing automated testing systems that hunt for vulnerabilities before they surface, and certifying the systems that power millions of daily conversations. You'll create intelligent evaluation systems that judge responses with human-level insight, build models that truly understand what makes interactions safe and delightful, and craft feedback mechanisms that help Alexa+ grasp the nuances of complex customer conversations. Here's where it gets even more exciting: you'll build AI agents that act as your team's safety net—automatically detecting and fixing production issues in real-time, often before anyone notices there was a problem. Your innovations won't just improve Alexa+; they'll fundamentally shape how it learns, evolves, and earns customer trust. As Alexa+ continues to delight customers, your work ensures it becomes more trustworthy, safer, and deeply aligned with customer needs and expectations. Your work directly protects customer trust at Amazon's scale. Every innovation you create—from novel safety mechanisms to sophisticated evaluation techniques—shapes how millions of people interact with AI confidently. You're not just building products; you're defining industry standards for responsible AI. This is frontier research with immediate real-world impact. You'll tackle problems that require innovative solutions: training models that remain truthful and grounded across diverse contexts, building reward models that capture the nuanced spectrum of human values across cultures and languages, and creating automated systems that continuously discover and address potential issues before customers encounter them. You'll collaborate with world-class scientists, product managers, and engineers to transform state-of-the-art ideas into production systems serving millions. What We're Looking For * Deep expertise in state-of-the-art NLP, Large Language Models * Track record of building scalable ML systems * Passion for impactful research—where frontier science meets real-world responsibility at scale * Excitement about solving problems that will shape the future of AI Ready to work on AI safety challenges that define the industry? Join us. Key job responsibilities The Responsible AI (RAI) team is at the forefront of building AI systems that are safe, ethical, and trustworthy. As an Applied Scientist-II, you'll be a key contributor to end-to-end Responsible AI solutions—developing and refining algorithms that detect and eliminate false information, building models that identify vulnerabilities exploited by bad actors, and training systems that understand human values across diverse cultures. Working alongside world-class engineers and scientists, you'll apply state-of-the-art NLP and computer vision techniques to content classification and safety challenges—turning cutting-edge research into production systems that protect millions of customers daily. But here's what makes this role exciting: you'll grow into a future leader. You'll contribute to identifying, defining, and mitigating AI safety risks early—helping protect customers before they're impacted—while building deep expertise in responsible AI. You'll work within multi-agent architectures, implementing components where distributed AI systems maintain human oversight and control. Every model you build and every experiment you run—from consensus-driven reasoning modules to orchestration components—will directly strengthen trustworthy AI at the world's largest scale. But here's what makes this role truly special: you'll shape the future. You'll lead efforts to identify, define, and mitigate risks early—protecting customers before they're impacted—and mentor the next generation of AI safety experts. You'll design multi-agent architectures where distributed AI systems exhibit emergent collective intelligence while maintaining human oversight and control. Every innovation you drive—from consensus-driven reasoning frameworks to sophisticated orchestration patterns—will set new standards for trustworthy AI at the world's largest scale. A day in the life As a Responsible AI Scientist, you're at the frontier of AI safety—experimenting with breakthrough techniques that push the boundaries of what's possible. You partner with engineering to transform research into production-ready solutions, tackling complex optimization challenges. You brainstorm with Product teams, translating ambitious visions into concrete objectives that drive real impact. Your expertise shapes critical deployment decisions as you review impactful work and guide go/no-go calls. You mentor the next generation of AI safety leaders, watching ideas spark and capabilities grow. This is where science meets impact—building AI that's not just intelligent, but trustworthy and aligned with human values. About the team Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.
  • US, CA, Sunnyvale
    Job ID: 10577453
    (Updated 22 days ago)
    MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Data Scientist II Job Location: Sunnyvale, California Job Number: AMZ10564077 Position Responsibilities: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. 40 hours / week, 8:00am-5:00pm, Salary Range: $175,040/year to $212,800/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
  • US, NY, New York
    Job ID: 10581936
    (Updated 15 days ago)
    Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Demand Tech Experience (DTx), as an org, owns the Amazon Ads Console — the advertiser-facing workspace for creating and managing campaigns, reviewing performance, and acting on recommendations used by millions of advertisers. Our team, DTx Science, is the centralized science team within DTx, dedicated to improving and protecting the advertiser experience across ad consoles through applied science methodologies. The team drives impact through four core functions: Ad Console Personalization, Recommendation Development, Ad Console Experimentation, and DVA Agent Evaluation and Impact Measurement. We leverage a breadth of state-of-the-art techniques such as deep learning, reinforcement learning, LLMs, long term causal modeling as well as sophisticated A/B testing to develop personalized experiences with directly quantifiable business and advertiser success outcomes. We are looking for an accomplished machine learning expert to lead the Applied Science strategy for our recommendation creation and personalization program. In this role, you will work closely with business leaders, stakeholders and cross-functional teams to drive program success through ML-driven solutions. You will shape the applied science roadmap, promote a culture of data-driven decision-making, and deliver significant business impact for millions of advertisers worldwide and the company using advanced data techniques and applied science methodologies. Key job responsibilities As an Applied Scientist on this team, you will - Serve as the technical leader in Machine Learning, driving collaboration between scientists and engineers, guiding efforts within the team and collaborating with other teams. - Conduct hands-on analysis and modeling of large-scale data to generate insights that boost ads revenue while maintaining a positive advertiser and shopper experience. - Lead end-to-end Machine Learning projects that involve high levels of ambiguity, scale, and complexity. - Build, experiment, optimize, and deploy machine learning models, collaborating with software engineers to bring your models into production. - Run A/B experiments, gather data, and perform statistical analysis to validate your models. - Develop scalable and automated processes for large-scale data analysis, model development, validation, and serving. - Explore and research innovative machine learning approaches to push the boundaries of what’s possible. About the team The DTx Science team is the centralized science team within Demand Tech Experience (DTx), dedicated to improving and protecting the advertiser experience across ad consoles through applied science methodologies. The team drives impact through four core functions: Ad Console Personalization, Recommendation Development, Ad Console Experimentation, and DVA Agent Evaluation and Impact Measurement. Improve advertiser experience: Ad Console Personalization and Recommendation Development aim to improve the advertiser ad console experience by providing customized and personalized console experiences for each user and increasing their ad performance with relevant, science-backed onboarding and oppertunty recommendations. Protect advertiser experience: Ad Console Experimentation and DVA Agent Evaluation and Impact Measurement protect the advertiser experience by supporting the organization in making data-driven decisions to launch UX and agentic features that benefit advertisers.
  • US, WA, Bellevue
    Job ID: 10591731
    (Updated 14 days ago)
    Do you enjoy solving complex, ambiguous problems with data and turning insights into business impact? Amazon is looking for a Data Scientist III to join a team where your analytical expertise will directly shape strategy and drive measurable outcomes. In this role, you will lead the design and delivery of data science solutions across large-scale projects, working with cross-functional partners to unlock new opportunities. You will bring broad expertise in machine learning, statistics, and scientific research to recommend the right approaches, build actionable models, and influence how your team tackles its most important challenges. If you are a collaborative, curious problem-solver who thrives on turning data into decisions, we want to hear from you. Key job responsibilities - Lead the design, implementation, and delivery of data science solutions for complex or ambiguous business problems, selecting appropriate machine learning and statistical methods to maximize impact. - Build, train, and evaluate machine learning models (e.g., classification, regression, clustering) using tools such as Python, R, and SQL, and apply advanced techniques including generative AI where appropriate. - Partner with cross-functional teams to translate business questions into rigorous analytical frameworks, and communicate findings that influence team and organizational strategy. - Drive data science best practices and set standards for your team, including reviewing analyses, data modeling processes, and results produced by peers, and providing constructive feedback. - Mentor and develop other data scientists in your organization, share knowledge of emerging methods and techniques, and contribute to internal enablement through presentations and documentation. A day in the life You might start your morning reviewing experiment results or refining a model you have been iterating on, then join a working session with engineers and product partners to align on how your analysis will inform an upcoming launch. After lunch, you could be exploring a new dataset, prototyping a novel approach, or writing up findings for a broader audience. Throughout the day, you will balance hands-on technical work with mentoring teammates and collaborating across groups to ensure your solutions address real business needs. About the team Our team is passionate about using data science to solve meaningful problems at Amazon scale. We value collaboration, intellectual curiosity, and a commitment to building solutions that are rigorous, reproducible, and actionable. Whether you are developing new models, mentoring colleagues, or partnering with stakeholders to shape strategy, you will be part of a group that invests in your growth and celebrates creative problem-solving. We are focused on building an inclusive environment where every voice contributes to our shared mission.
  • (Updated 28 days ago)
    We are seeking an Applied Scientist III to own the technical vision and development of an AI-based governance intelligence platform that will redefine how account and organizational governance is defined, validated, and enforced at scale. This mission-critical platform will leverage AI-driven autonomous agents to conduct proactive, intelligent governance operations across the account lifecycle. The platform will integrate deeply with organizational management, identity, and cloud-native control systems to provide self-serve, automated governance insights, policy verification, and enforcement mechanisms. The Governance Foundations team is building a unified governance foundation that consolidates account management controls — including automated enrollment, managed policies, and account lifecycle guardrails — into a single, intelligent, scalable system. As a senior science leader on the team, you will operate with a high degree of autonomy on ambiguous, open-ended problems that span multiple organizations. You will set the multi-year scientific direction, make the architectural and modeling decisions that others build on, and drive alignment across applied science, engineering, product, and partner teams — up to and including senior leadership. This is an opportunity to shape the future of AI-driven governance assurance at enterprise scale: defining standards, influencing company-wide account governance posture, and leading technical innovation at the highest level. Key job responsibilities - Own and define the next-generation governance intelligence and policy-matching platform, setting the multi-year technical strategy for AI-driven governance automation across applied science and engineering teams and resolving the hardest, most ambiguous problems in the space. - Build on and advance a multi-agent LLM framework for autonomous governance operations, and influence partner organizations to adopt the most promising approaches — including human-in-the-loop enforcement boundaries that cannot be bypassed by autonomous agents. - Develop a highly scalable intelligent governance agent framework — combining traditional ML and LLM-based techniques — that enables internal teams to automate validation, classification, and enforcement across structured and unstructured policy and account data. - Provide technical leadership and scientific mentorship across the broader organization — raising the bar on science quality, growing other scientists and engineers, and representing the team's technical direction to senior leadership — while still diving deep hands-on to diagnose complex system performance and correctness problems in distributed governance control planes. - Define the scientific metrics, evaluation methodology, and quality bar by which the platform's governance decisions are measured and trusted. About the team The Accounts Management and Governance team builds the unified governance foundation for account and organizational management at scale. The team consolidates account lifecycle controls, policy propagation, and enforcement guardrails into a single intelligent system, ensuring the experiences Amazon delivers to its customers uphold our highest standards of security, correctness, and operational integrity. The science team harnesses AI to strengthen Amazon's governance posture more efficiently and effectively
  • (Updated 24 days ago)
    The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, all working to innovate in quantum computing for the benefit of our customers. We are looking to hire an Applied Scientist to design and model novel superconducting quantum devices (including qubits), readout and control schemes, and advanced quantum processors. The ideal candidate will have a track record of original scientific contributions, strong engineering principles, and/or software development experience. Resourcefulness, as well as strong organizational and communication skills, is essential. About the team The Amazon 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. Inclusive Team Culture Here at Amazon, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 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 US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility. 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.

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.