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About Amazon Science

Science at Amazon enables new customer experiences, addresses existing customer pain points, complements engineering and product disciplines, and is a critical functional skill for all Amazon businesses. It is this focus on the customer, and the company’s ability to have impact at global scale that attracts some of the brightest minds in artificial intelligence, machine learning, and related fields.

  • Amazon scientists are conducting cutting edge research in areas ranging from machine learning to operations, conversational AI, robotics, quantum computing, and more.
  • Take deep dives into the latest research from Amazon scientists. including in depth looks at research that has been accepted at leading scientific conferences around the world.
  • The latest news about scientific innovation at Amazon, including in-depth behind the science features, awards, and recognitions.
  • Amazon is a great place to practice science and have real business impact, but that’s only one part of the story. Our scientists continue to publish, teach, and engage with the worldwide research community.
  • Amazon researchers regularly contribute to the broader scientific community through the public release of code and datasets.
  • Our scientists are active in conferences worldwide, where they look forward to contributing to — and learning from — the latest research, as well as engaging with the global science community.
  • Whether you’re a faculty member, student, developer, thought leader or a policy maker, Amazon offers a number of ways to engage with the company’s science community.
  • Amazon Go Store in the Amazon Seattle Campus
    JORDAN STEAD/(JORDAN STEAD / Amazon)
    The company recruits talent from around the world for applied scientists, data scientists, economists, research scientists, scholars, academics, PhDs, and interns.
Yoelle Maarek, vice president of research and science for Alexa Shopping
We coined 'customer-obsessed science' a few years ago to highlight how Amazon does science differently. Not only do we always start from a customer need, but even our scientific methodology starts from the customer backwards. This approach is an awesome source of inspiration and professional fulfillment for our scientists because it increases the chances that our work won’t gather dust on a shelf, but instead will delight millions of customers across the globe.
Yoelle Maarek, vice president, Research and Science, Alexa Shopping & Tech
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Christopher Stratchey wrote, "The separation of practical and theoretical work is artificial and injurious. Much of the practical work done in computing, both in software and in hardware design, is unsound and clumsy because the people who do it have not any clear understanding of the fundamental design principles of their work. Most of the abstract mathematical and theoretical work is sterile because it has no point of contact with real computing." Our customer-obsessed science strategy reliably nudges me back towards the intersection of the practical and theoretical. That's where the really game-changing work is at.
Byron Cook, vice president, distinguished scientist, Automated Reasoning Group
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It means first developing a conviction that the problem we are working on is or will be truly important to customers. It's like asking the five whys — all starting with, ‘Who cares about the problem, and why should they care?’ — before getting down to a mathematical model. Once we are convinced about the value, it's about developing the right science to address the problem — and the problems that have the most customer impact in the long-term often require exciting new science and systems. This helps us focus on science that will really move the needle for our customers and stand the test of time.
Salal Humair, vice president and distinguished scientist, SCOT Inventory, Planning & Control
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Customer-obsessed science means to always put yourself in the customer's shoes to improve the experience. It also means listening to customer pain points, and inventing on their behalf. They will tell you what they don't like, but it is up to us to provide solutions to delight them. Just Walk Out is a prime example of innovative solution addressing the "nobody likes to wait in line" customer pain point.
Gerard Medioni, vice president, distinguished scientist, Physical Stores Tech
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Customer-obsessed science aims to solve customer problems and improve customer experiences. It is aligned with business priorities and brings value to our business. It is science that works backwards from customer needs and pain points, as opposed to forward from technology. It's important not to confuse customer-obsessed science with science that has a short time-horizon — customer-obsessed science be focused on the long-term.
Rajeev Rastogi, vice president, India Machine Learning
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Customer-obsessed science means that you focus on understanding the customer's problem and bringing the best scientific tools to solve the problem. It means that you are not dogmatic about methods, but seek to apply the best method or combination of methods to solve the customer's problem. You invent and simplify, seeking expertise by partnering with others if the best method(s) is not your specialty.
Justine Hastings, vice president, PXT Science
Spyros Matsoukas, Senior Principal Applied Scientist, Alexa AI
Research and development that is grounded on real-world challenges and customer-facing problems. Only by working backwards from the customer, including defining metrics that characterize customer experience, we can ensure that our scientific innovations have measurable impact on customers’ lives.
Spyros Matsoukas, vice president and distinguished scientist, Alexa
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Working backwards from customers means advancing state of art that solves specific customer pain points or builds new delights. The key difference is that we do not start with a solution and then look for problems where that solution can be applied. We start with the desired experience, identify key problems to solve, and then invent novel approaches to solve those problems.
Manoj Sindhwani, vice president, Alexa Speech
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Customer obsession in science means applying the scientific method in service of our customers. Working backwards from the customer; their needs, wants, and pain points, is focusing our work on scientific innovation that is truly impactful. But science is a creative endeavor -- we often find surprises and new insights along the way. As we do, we continuously evaluate new ways to delight our customers.
Nikko Ström, vice president and distinguished scientist, Alexa AI
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Customer-obsessed science is about anticipating customers' needs by devising innovative solutions to challenging problems that customers do not yet realize they have or will have. This allows us to respond quickly with enhanced services when these needs do arise.
Douglas Terry, vice president, distinguished scientist, Database & AI Leadership
Garrett van Ryzin
I was always attracted to practical science — calculating where a projectile will land, how current flows in a circuit, what determines supply and demand. I love understanding how the world works and using this knowledge to make things better. And this is exactly what Amazon's customer-obsessed science is all about, working backwards from what customers value and using science to innovate and make their lives better. It's what great science is all about.
Garrett van Ryzin, distinguished scientist, SCOT
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Inventing devices and services that improve the health and wellness of everyone on the planet.
David Heckerman, vice president and distinguished scientist, Advanced Technologies
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Customer-obsessed science means inventing and applying scientific approaches to understand and solve customer problems. It’s not just about coming up with the best algorithm or model you can think of, but proving it with sound methodology and ensuring it’s applicable to real-world challenges. This is core to everything that we do at Amazon, and it’s what makes us different. We start with our customers and work backwards from their needs, testing and improving our products and services based on their behavior and feedback.
Rohit Prasad, senior vice president and head scientist, Alexa

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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India
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US, WA, Bellevue
The North America Customer Delivery Excellence (CDE) team within Amazon Global Delivery Services is seeking a Data Engineer to join our team in Seattle. You will be building world class big data applications to support Amazon transportation and business operations. As a Data Scientist on the CDE team, you will be responsible for: Procuring large datasets sufficient to train Machine Learning models and neural networks to ensure statistical significance in business insights. Interface with other technology teams to extract, transform, and load data from a wide variety of data sources. Drive both business and technology solutions to improve Amazon Inbound visibility. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers. Translate data into actionable insights for the stakeholders.
US, NY, New York
Amazon is investing heavily in building a world class advertising business. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The Sponsored Products Marketplace Intelligence team is responsible for ranking, allocation and pricing of ads on Amazon search pages. A Senior Manager for pricing will be responsible for defining our business and technical strategy for one of our most impactful marketplace controls, creating lasting value for Amazon and advertisers. Job Responsibilities: Lead business, science and engineering strategy and roadmap for Sponsored Products pricing controls. Oversee development, testing, launch and improvement of models designed to price ads. Develop state of the art experimental approaches and ML models. Impact and Career Growth: Opportunity to grow and broaden your technical skills as you work in an environment that thrives on creativity, experimentation, and product innovation. Drive real-time algorithms to price billions of ads per day in advertising auctions. Have the ability to experiment autonomously with meaningful projects. This is a high-visibility role managing a cross-functional team of scientists, engineers and product managers. You'll be responsible for developing roadmaps, staffing plans and growing your team. Why you love this opportunity: Sponsored Products (SP) is Amazon's largest and fastest growing business. Over the last few years we grown to a multi-billion dollar business. SP ads are shown prominently throughout search and detail pages, allowing shoppers to seamlessly discover products sold on Amazon. Pricing is one of the highest impact decisions we make. This role has unparalleled opportunity to grow our marketplace and deliver value for advertisers.
DE, Tuebingen
Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon. We are a smart team of doers that work passionately to apply cutting edge advances in technology and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We are a newly established innovative Development Center in Tübingen, Germany which focuses on computer vision, machine learning, robotics and causality in diverse application fields at Amazon. If you get excited by the prospect of dealing with ambiguity, solving hard, large scale problems, working in a startup like environment and if you want to come to one of the most exciting places of the world for researching Intelligent Systems, then we have the perfect role for you.
US, CA, Santa Clara
Amazon is looking for a passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading technology in language, generative AI and foundational models. Key job responsibilities As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use of speech, vision and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, image and structured data sources, and large-scale computing resources to accelerate advances in machine learning.
ES, B, Barcelona
Are you excited to help customers discover the hottest and best reviewed products? Through the enablement of intelligent campaigns that leverage machine-learning models, you will help to deliver the best possible shopping experience for Amazon’s customers all over the globe. We are looking for experienced scientist who will work with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables. Your domain spans the design, development, testing, and deployment of data driven and highly scalable solutions using data processing and machine learning in product recommendation. You will partner with scientists, product managers, and engineers to help invent and implement scalable Data processing and ML models while inventing tools on our customers behalf. Key job responsibilities As a Principal Applied Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. A day in the life This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, and work closely with scientists and engineers. We are particularly interested in candidates with experience building large scale machine learning solutions and working with distributed systems to 1) help us build robust ensemble of ML systems that drive classification and recommendation of products with a high precision and recall utilizing various signals and scale to new marketplaces and languages and 2) design optimal supervised and unsupervised machine learning models and solutions for moderately complex projects in business, science and engineering. About the team The Discovery Tech team helps customers discover and engage with new, popular and relevant products across Amazon worldwide. We do this by combining technology, science, and innovation to build new customer-facing features and experiences alongside cutting edge tools for marketers. You will be responsible for creating and building critical services that automatically generate, target, and optimize Amazon’s cross-category marketing and merchandising.
Spain, M, Madrid
Do you want to build cutting-edge AI/ML technologies that reinvent the user experience for Amazon devices! Do you want to shape the vision and direction for the next generation of intelligent customer experiences leveraging state-of-the-art deep learning and generative models? The Amazon Devices Core AI team seeks to hire an Applied Science Manager who has a solid background in foundational AI/ML research, extensive experience in building scalable AI/ML solutions, strong ability to lead scientific initiatives, and has a proven track record of executing complex projects and delivering high business impact. The long-term vision of the Core AI team is to make Amazon devices effortlessly engaging for all our customers. We are creating an experience that understands why and when customers engage with different types of contents or take different actions, and build our products to foresee and satisfy those needs. We are building the capabilities to give Amazon devices the ability to help customers discover and find all types of relevant information and contents through conversational interactions, suggestions, and personalized recommendations. We build state-of-the-art foundational technologies that enable an intelligent customer experience leveraging advanced deep learning and large language models, generative AI, and privacy-preserving machine learning on device. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. You must have a demonstrated ability for optimizing, developing, launching, and maintaining large-scale customer-facing production systems. You should be willing to dive deep when needed, move rapidly with a bias for action, and get things done. You should have an entrepreneurial spirit, love autonomy, know how to build and deliver pioneering solutions to challenging problems. This role will demand resourcefulness and a fearless willingness to learn on both the technical and business side. As an Applied Science Manager you will: Directly manage and lead a team of Applied Scientists and ML Engineers to deliver AI/ML solutions at scale that empower our devices to provide the best experience for our customers. Define a long-term science vision, driven from our customers' needs, translating that direction into science and engineering roadmaps, and foster cross-team collaboration to execute complex projects. Act as a technical supervisor, able to assess scientific direction, technical design documents, and steer development efforts to maximize project delivery. Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization. Develop and manage a research agenda that balances short term deliverables with measurable business impact as well as long term investments. Drive continued scientific innovation and advance the team's engineering craftsmanship as a practitioner and thought leader.
US, CA, San Francisco
The AWS AI Labs team has a world-leading team of researchers and academics, and we are looking for world-class colleagues to join us and make the AI revolution happen. Our team of scientists have developed the algorithms and models that power AWS computer vision services such as Amazon Rekognition and Amazon Textract. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. AWS is the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems which will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. Our research themes include, but are not limited to: few-shot learning, transfer learning, unsupervised and semi-supervised methods, active learning and semi-automated data annotation, large scale image and video detection and recognition, face detection and recognition, OCR and scene text recognition, document understanding, 3D scene and layout understanding, and geometric computer vision. For this role, we are looking for scientist who have experience working in the intersection of vision and language. We are located in Seattle, Pasadena, Palo Alto (USA) and in Haifa and Tel Aviv (Israel).
CA, ON, Toronto
Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The Detail page Ad relevance team in Sponsored Products organization is responsible for measuring the ads relevance and suppressing the irrelevant ads for optimal shoppers’ experience. We build advanced deep-learning models, large-scale machine-learning (ML) pipelines, and real-time serving infra to determine the relevance of ads with immediate detail page context, widgets the ads are served and shoppers’ intent on all devices in all marketplaces. Through precise estimation of ad relevance and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for energetic, entrepreneurial, and self-driven science leaders to join the team. Key job responsibilities As a Principal Applied Scientist in the team, you will: - Be single threaded owner of Ad relevance in Detail page: develop relevance models, own relevance Andon Cord deep dive, report & audit DP relevance metrics: dive deep into relevance regression and develop their solutions to improve. - Seek to understand in depth the Sponsored Products offering at Amazon and identify areas of opportunities to grow our business via principled ML solutions. - Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in ML. - Design and lead organization wide ML roadmaps to help our Amazon shoppers have a delightful shopping experience while creating long term value for our sellers. - Work with our engineering partners and draw upon your experience to meet latency and other system constraints. - Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver. - Be responsible for communicating our ML innovations to the broader internal & external scientific community. We are open to hiring candidates to work out of one of the following locations: Toronto, ON, CAN
US, WA, Seattle
Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Amazon Robotics, a wholly owned subsidiary of Amazon.com, empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas. AR is seeking uniquely talented and motivated data scientists to join our Global Services and Support (GSS) Data Solutions and Insights (DSI) Team. DSI focuses on improving the supportability of the Amazon Robotics solutions through automation, with the explicit goal of simplifying issue resolution for AR and our global network of Fulfillment Centers. The candidate will work closely with data scientists, software engineers, Fulfillment Center operation teams, system engineers, and product managers in the development, qualification, documentation, and deployment of new - as well as enhancements to existing - models, metrics, and data driven dashboards. As such, this individual must possess the technical aptitude to interface with different data access layers for metric computation, data mining, and data modeling. This role is a 6 month co-op to join AR full time (40 hours/week) from September – December 2023. The Co-op will be responsible for: Developing and building models in AWS environment Diving deep into operational data and metrics to identify and communicate trends used to drive development of new tools for supportability Translating operational metrics into functional requirements for BI-tools, models, and reporting Collaborating with cross functional teams to automate AR problem detection and diagnostics
JP, 13, Tokyo
日本の大学で機械学習や関連領域の研究に従事している学生の皆様に向けたフェローシッププログラムのご案内です。Amazon JapanのRetail Scienceチームでは、何百万人もの顧客にインパクトを与える価値あるテクノロジーに繋がるような、新しいプロトタイプやコンセプトを開発するプロジェクトに従事していただく学生を���集しています。プログラムは1ヶ月から3ヶ月の短期間のプロジェクトになります。 プロジェクトの対象となるテーマには、自然言語処理、表現学習、レコメンデーションシステム、因果推論といった領域が含まれますが、これらに限定されるわけではありません。プロジェクトは、チームのシニアサイエンティスト1名または複数名のガイダンスのもとで定義、遂行され、プロジェクト中は他のサイエンティストもメンターとしてフォローします。 学生の皆様が新しいモデルを考案したり、新しいテクノロジーを活用し実験する時間を最大化できるようにすることが目標です。そのため、プロジェクトではエンジニアリングやスケーリングよりも、プロトタイピングを行い具体的に概念実証を行うことに集中します。 また、Amazonでは論文出版も推奨しています。従事した研究開発活動の成果物として出版される論文には著者として参加することになります。 フェローシッププログラムは目黒の東京オフィスで、他のチームと一緒に行われます。Amazonは、プログラム期間中に必要なIT機器(ラップトップなど)、給与、宿泊費と通勤費を支給します。 Are you a current PhD student enrolled in a Japanese university researching Machine Learning or a related discipline? The Japan Retail Science team is looking for Fellows for short term (1-3 months) projects to develop new prototypes and concepts that can then be translated into meaningful technologies impacting millions of customers. In this position, you will be assigned a project to carry out from areas including but not limited to natural language processing, representation learning, recommender systems, or causal inference. The project will be defined and carried out under the supervision of one or more of our senior scientists, and you will be assigned another scientist as a mentor to follow you during the project. Our goal is to maximize the time you spend on inventing new models and experimenting with new techniques, so the work will concentrate on prototyping and creating a tangible proof of concept, rather than engineering and scaling. Amazon encourages publications, and you will be included as an author of any published manuscript. The fellowship will be carried out from our Tokyo office in Meguro together with the rest of the team. Amazon will provide the necessary IT equipment (laptop, etc.) for the duration of the fellowship, a salary, and a stipend to cover accommodation and commuting expenses. A day in the life チームの多くのメンバーは、午前9時くらいから10時半くらいまでの間に仕事を始め、夕方6時から7時には仕事を終えています。出席が必要なミーティングに参加していれば、勤務時間は自由に決められます。 パートタイムを希望する場合、勤務時間数は採用担当者とともに決定します。フルタイムの場合、労働時間は通常の契約通り週40時間となります。 オフィスは目黒にあり、週3回の出社が必要です。残りの2日間はリモートワーク、オフィスへの出勤いずれも可能です。 The majority of the team starts working between 9 and 10.30am until 18-19. You will have complete flexibility to determine your working hours as long as you are present for the meetings where your attendance is required. Number of working hours will be determined together with the hiring manager in case you want to pursue the Fellowship part-time. In case of full-time, working hours will be 40/week as per a standard contract. Our office is located in Meguro, and presence in the office is required 3 times/week. You are free to work remotely for the remaining two days or come to the office if you prefer. About the team 私たちのチームは、日本および世界のすべてのAmazonのベンダー企業に提供されるソリューションを支える製品を発明し、開発しています。私たちは、プロダクトマネージャーやビジネス関係者と協力し、科学的なモデルを開発し、インパクトのあるアプリケーションに繋げることで、Amazonのベンダー企業がより速く成長し、顧客により良いサービスを提供できるようにします。 私たちは、科学者同士のコラボレーションが重要であり、孤立した状態で仕事をしても、幸せなチームにはならないと考えています。私たちは、科学者が専門性を高め、最先端の技術についていけるよう、社内の仕組みを通じて継続的に学ぶことに重きを置いています。私たちの目標は、世界中のAmazonのベンダーソリューションの主要なサイエンスチームとなることです。 Our team invents and develops products powering the solutions offered to all Amazon vendors, in Japan and worldwide. We interact with Product Managers and Business stakeholders to develop rigorous science models that are linked to impactful applications helping Amazon vendors grow faster and better serving their customers. We believe that collaboration between scientists is paramount, and working in isolation does not lead to a happy team. We place strong emphasis on continuous learning through internal mechanisms for our scientists to keep on growing their expertise and keep up with the state of the art. Our goal is to be primary science team for vendor solutions in Amazon, worldwide.