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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.
605 results found
  • IN, TN, Chennai
    Job ID: 10401676
    (Updated 12 days ago)
    Alexa Connections is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Connections products and services. Key job responsibilities As an Applied Scientist with the Alexa Connections team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Set up experimentation frameworks for agile model analysis and A/B testing. * Collaborate with partner teams on LLM evaluation frameworks and post-training methodologies. * Contribute to end-to-end delivery of solutions from research to production, including reusable science components. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.
  • US, WA, Seattle
    Job ID: 10382992
    (Updated 32 days ago)
    Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the next level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Research Scientist, you will work with a unique and gifted team developing exciting products for consumers and collaborate with cross-functional teams. Our team rewards intellectual curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the intersection of both academic and applied research in this product area, you have the opportunity to work together with some of the most talented scientists, engineers, and product managers. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
  • US, WA, Seattle
    Job ID: 10398366
    (Updated 4 days ago)
    Have you ever wanted to solve a mystery or be part of solving a case? Are you fascinated by detective stories or crime shows on TV? Do you love to manage huge volumes of data, have a science background and enjoy solving complex problems? WWOS Tech is transforming into an AI-first security technology organization, and we're seeking an exceptional Applied Science Manager to anchor this transformation. As the Science & BI Lead, you'll own the enterprise AI/ML roadmap, lead an organization of scientists and BIEs, and deliver production AI and ML models that will generate 1M+ efficiency hours annually. Key job responsibilities Lead AI/ML Strategy & Delivery - Own the enterprise AI/ML roadmap across UNITE (theft detection, investigation automation), PRISM (operational disruption, risk management) and other WWOS Tech products - Deliver net-new production AI models by EOY 2026 aligned to WWOS SPS goals: reduce theft/fraud loss from 0.30% to 0.19% of GMS and transform incident preparedness from reactive to proactive. - Establish AI/ML delivery standards: model quality gates, bias detection, responsible AI compliance (Amazon Trust principles, EU AI Act), and production readiness criteria - Build centralized model registry, shared experimentation platform (SageMaker), and MLOps infrastructure in partnership with Data Engineering Build & Scale High-Performing Teams - Lead Science & BI pillar within WWOS Tech: grow Science team over next 18 months, manage 3 BIE managers overseeing BIEs across EESN, Ops Disruption, and Business Reporting teams - Recruit, onboard, and retain top AI/ML talent in a highly competitive market; develop career paths for Scientists, ML Solutions Architects, and BIEs transitioning to AI-enabled strategic advisors - Drive AI literacy across all of WWOS organization: 100% AI-trained by EOY 2026 across Technical, Leadership, and Cross-Skill tracks - Establish operating rhythm: weekly Science pillar sync, bi-weekly cross-pillar integration reviews, monthly AI portfolio health inspections Partner with Business & Technical Leaders - Translate ambiguous business problems into AI/ML solutions through direct partnership with field leaders, program vertical leaders, and WWOS senior leadership. - Represent WWOS Tech in Amazon-wide AI/ML forums: AWS AI partnerships, responsible AI governance, GOS AI forums Drive Responsible AI & Governance - Ensure all AI models touching sensitive security data meet Amazon's responsible AI bar and evolving regulatory requirements (GDPR, EU AI Act) - Implement bias detection, model explainability and human-in-the-loop mechanisms for high-risk applications - Conduct quarterly AI risk assessments with Legal, InfoSec, and Privacy teams; maintain AI model inventory and compliance dashboard - Partner with AI Ethics & Governance Specialist to establish enterprise-wide responsible AI frameworks About the team We are a team that cares about your work-life balance, while challenging you to solve problems at high scale. You will be part of a strong team in a fast-paced, start-up environment where agile development is embraced and innovation is encouraged. You will get support and resources from some of the smartest people in the industry to continue your personal and professional growth. You'll be joining a fun team that prides itself on a great work environment with an inclusive group of people that loves working together towards a common goal and make history in launching a new strategic service in the industry.
  • (Updated 5 days ago)
    The Mission Build AI safety systems that protect millions of Alexa customers every day across modalities( text, audio, image, and so on). 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 evaluation systems that hunt for vulnerabilities before they surface, and certifying the systems that power millions of daily conversations. You'll create intelligent Generative AI 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 advanced computer vision and GenAI models and algorithms for comprehensive visual understanding in RAI domain * Track record of building scalable ML systems across modalities ( text, images and so on) * Provide technical leadership on AI products/features, and develop and mentor junior scientists on the team. * Collaborate with scientists, engineers, product/program managers and other cross-functional teams * Passion for impactful research—where frontier science meets real-world responsibility at scale Ready to work on AI safety challenges that define the industry? Join us. Key job responsibilities This is where you'll make your mark. You'll architect breakthrough Responsible AI solutions that become industry benchmarks, 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 with world-class engineers and scientists, you'll push the boundaries of model training—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 advance optimization techniques, build evaluation systems that reason like humans, resolve Responsible AI vulnerabilities in Generative AI systems, and mentor the next generation of AI safety experts. Every innovation you drive 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.
  • JP, 13, Tokyo
    Job ID: 10397291
    (Updated 11 days ago)
    Elevate Your Economic Research at the Forefront of Global Retail Innovation We're seeking a brilliant economics researcher to join our dynamic team in Tokyo, where your analytical skills will drive transformative insights across Amazon's global retail ecosystem. As an intern, you'll collaborate with world-class economists, data scientists, and business leaders to solve complex challenges that shape the future of e-commerce. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. A day in the life Your day will be filled with intellectual exploration and impactful problem-solving. You'll dive deep into large-scale datasets, develop sophisticated econometric models, and translate complex economic research into actionable business strategies. Expect to engage in collaborative discussions, leverage modern analytical tools, and contribute to projects that have real-world implications for our global customers.
  • US, CA, Santa Clara
    Job ID: 10380934
    (Updated 14 days ago)
    Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale. We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. As part of our diverse team—including data scientists, engineers, language engineers, linguists, and program managers—you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence. Key job responsibilities In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. Specific responsibilities include: * Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features * Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings * Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases * Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance * Develop and refine annotation guidelines and quality frameworks for evaluation tasks * Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies * Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements * Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts * Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.
  • JP, 13, Tokyo
    Job ID: 10397284
    (Updated 14 days ago)
    Elevate Your Economic Research at the Forefront of Global Retail Innovation We're seeking a brilliant economics researcher to join our dynamic team in Tokyo, where your analytical skills will drive transformative insights across Amazon's global retail ecosystem. As an intern, you'll collaborate with world-class economists, data scientists, and business leaders to solve complex challenges that shape the future of e-commerce. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. A day in the life Your day will be filled with intellectual exploration and impactful problem-solving. You'll dive deep into large-scale datasets, develop sophisticated econometric models, and translate complex economic research into actionable business strategies. Expect to engage in collaborative discussions, leverage modern analytical tools, and contribute to projects that have real-world implications for our global customers.
  • (Updated 18 days ago)
    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 and 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 This is where you'll make your mark. You'll architect breakthrough Responsible AI solutions that become industry benchmarks, 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 with world-class engineers and scientists, you'll push the boundaries of model training—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 certification processes, advance optimization techniques, build evaluation systems that reason like humans, and mentor the next generation of AI safety experts. Every innovation you drive 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, WA, Bellevue
    Job ID: 10391822
    (Updated 20 days ago)
    Amazon's Community Intelligence Science & Engineering (CISE) team operates at the intersection of computational social science, artificial intelligence, and operational planning. We build and validate models that quantify how Amazon's operational presence impacts local communities, and embed those signals into core planning models that drive Last Mile, Middle Mile, and site-level decisions across our network. You'll work at the forefront of applied AI and causal inference, building systems that influence decisions affecting thousands of communities daily. This role offers a unique opportunity to shape how the world's most customer-centric company measures, forecasts, and reduces operational risk to the communities we serve. A successful Senior Research Scientist on our team demonstrates exceptional scientific rigor combined with pragmatic execution. You will design the causal frameworks and predictive models that systematically embed these community signals into core operational planning processes where they do not yet exist. This means balancing breakthrough research with production deployment, collaborating across multiple science organizations, and translating complex analytical findings into actionable insights that influence senior leadership strategy. As a Senior Research Scientist, you will partner with product teams, operational scientists, and technical leaders across Last Mile Planning Science, Middle Mile Relay, Safety, and Worldwide Operations Security to identify opportunities where community intelligence creates multiplicative business impact. Key job responsibilities - Collaborate with operational science teams to integrate community risk signals into existing operational models and decision-making systems, with a focus on quantifying performance lift and defining integration architecture - Design and execute experiments to measure how community-impacting operational policies affect business outcomes - Build automated causal discovery systems leveraging knowledge graphs, LLMs, and document understanding to uncover relationships between operational policies and community outcomes - Design and deploy production ML forecasting systems with extended prediction horizons using multi-modal data sources, including survey-based indices, geospatial risk features, and operational metrics - Mentor junior scientists and contribute to building a research culture that balances high-risk, high-reward innovation with reliable product delivery About the team Amazon Community Operations (CommOps) works to anticipate our communities’ needs and build positive net impact anywhere we operate. From Operational Excellence to Community Outreach, Community Operations is defining what it means to be a positive presence in the community. This is a fast-paced, start-up environment where creative problem solving, operational excellence, and building relationships are the core of our day-to-day work.
  • (Updated 27 days ago)
    The Amazon Web Services Center for Quantum Computing (CQC) in Pasadena, CA, is looking to hire an Applied Scientist. You will join a multi-disciplinary team of experimental and theoretical physicists, materials scientists, and hardware and software engineers working at the forefront of quantum computing. You should have a solid foundation in experimental physics and deep and broad knowledge of experimental measurement techniques. 

Candidates should have a track record of original scientific contributions, and those with deep knowledge and experience in low temperature condensed matter physics (superconductivity, Josephson junctions, phononics, TLS physics etc.) will be preferred. We are looking for candidates with strong engineering principles, resourcefulness and a bias for action, superior problem solving, and excellent communication skills. Working effectively within a team environment is essential. You will be expected to work on new ideas and stay abreast of the field of experimental quantum computation. Key job responsibilities In this role, you will be part of the Physical Metrology and Exploration (PME) subgroup within the Device team. You will work with the basic building blocks of quantum processors, ranging from superconducting films and resonators to junctions and qubits. There are two core missions for the PME team. The first is to support the CQC’s central activities through the development of devices, both existing and novel, that fall within this complexity range. This involves understanding their physical principles, identifying performance limitations, and collaboratively enhancing their capabilities. In many cases though, existing tools and measurement protocols fall short in delivering the depth of insights required for this first mission. Hence the second core mission of the team centers on physical metrology development. This involves continuously refining existing methodologies and simultaneously devising entirely new ones by identifying specific physical phenomena and exploiting them for measurement applications. You will constantly learn, innovate, carry out agile and yet scientifically rigorous research, and disseminate findings to the rest of the organization. You will be responsible for building experiments that encompass the integrated stack: design, fabrication, cryogenics, signal chain, and control stack software. Based on your research, you will provide recommendations that improve our next-generation quantum processors.

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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Australia
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Canada
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Ontario
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China
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Beijing, CN
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Germany
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India
Hyderabad, IN
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Bengaluru, IN
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Israel
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United States
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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.