Careers

Futures Design is the advanced concept design and incubation team within Amazon’s Device and Services Design Group (DDG). We are responsible for exploring and defining think (very) big opportunities globally and locally — so that we can better understand how new products and services might enrich the lives of our customers and so that product teams and leaders can align on where we're going and why we're going there. We focus on a 3–10+ year time frame, with the runway to invent and design category-defining products and transformational customer experiences. Working with Amazon business and technology partners, we use research, design, and prototyping to guide early product development, bring greater clarity to engineering goals, and develop a UX-grounded point of view. Our team is dedicated to unlocking new foundational capabilities in generative AI, guided by the thesis that embedding understanding through human factors, cognitive science, and socioeconomics is crucial to building AI systems that align with human needs. We place particular emphasis on the capabilities of simulacra through agentic systems and experiential/evolutionary learning, which we believe are vital to accelerating the development of AI as an aligned partner. Joining our team will give you the chance to drive key decisions that will impact the lives of millions of Amazon customers. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). A day in the life We're looking for a Senior Applied Scientist to join the growing DDG Futures Design team. You thrive in ambiguity and paradigm shifts – remaking assumptions of how customers engage, devices operate, and builders create. You apply deep expertise that spans design, technology, and product, grounding state-of-the-art emerging technologies through storytelling and a maker's mindset. You learn and adapt technology trends to enduring customer problems through customer empathy, code, and iterative experimentation. You will wear multiple hats to quickly assimilate customer problems, convert them to hypotheses, and test them using efficient technologies and design methods to build stakeholder buy-in. You’ll help your peers unlock challenging scenarios and mature the design studio’s ability to deliver design at scale across a breadth of devices and interaction modalities. You will work around limitations and push capabilities through your work. Your curiosity will inspire those around you and facilitate team growth, while your hands-on, collaborative nature will build trust with your peers and studio partners.

Do you want to use your expertise in translating innovative science into impactful products to develop a new business line in emerging stores. If you do, Emerging Stores Payments team would love to talk to you about how to make that a reality. As an applied scientist on our team, you will work with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables and define the execution roadmap. You will partner with scientists, and engineers on the design, development, testing, and deployment of scalable ML models. This is a unique, high visibility opportunity for someone who wants to have impact, dive deep into large-scale solutions, enable measurable actions on the employee experience, and work closely with scientists and economists. This role combines science leadership and technical strength. Key job responsibilities - As an Applied Scientist, ML Applications, you will: - Lead applied scientists to deliver machine-learning and AI solutions to production. - Design, develop, and evaluate innovative machine learning solutions to solve diverse challenges and opportunities for Amazon customers - Advance the team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner. - Partner with the engineering team to deploy your models in production. - Partner with scientists from across ML teams within India Consumer Payments to solve complex problems. - Work directly with Amazonians from across the company to understand their business problems and help define and implement scalable ML solutions to solve them. - Mentor and develop junior scientists and developers.

Are you a MS or PhD student interested in a 2025 Internship in the field of machine learning, deep learning, speech, robotics, computer vision, optimization, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Luxembourg, Netherlands, Poland, Romania, Spain, UAE, and UK). Please note these are not remote internships.

Amazon's EU International Technology (EU INTech) Selection Expansion (SelEx) charter mission is to accelerate the selection flywheel for Sellers. To achieve our mission, we drive bottoms-up innovations with the mental model of the EU first solution and scale WW. Our North Star is to delight Sellers with an automated selection expansion experience to help them grow their business, bringing their selection to all customers world-wide. Key job responsibilities We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including forecasting, ranking and reccomendations. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables. A day in the life You will work with Sr and Principal PM-T, TPM, BIE and other APSCI (internal and external to the team) to create solutions/models that will help seller to maximize the value of their investments while expanding in EU and WW. You will be supported by a team of more than 25 engineers to build the next chapter of selection expansion. About the team We are builders focused in one of the most critical sections of the flywheel: Selection. We built and own solutions such as Exports Central and EEA (European Expansion Accelerator), and continue to evolve and create ways to bring selection around the world.

The Community Feedback organization owns the experiences and systems that enable shoppers to provide and review trusted customer-generated content across the shopping journey. We bring together trusted, authentic inputs from the community and surface them with the help of AI so that customers can make effortless, high-confidence, purchase decisions. Features such as Customer Reviews, Content Moderation, and Customer Questions & Answers (Q&A), build a rewarding and engaging experience for creators to share their feedback, providing shoppers with trusted insights based on this feedback to inform their shopping decisions. We offer billions of star ratings and reviews with text, together with hundreds of millions of reviews and Q&A with media. Our vision is to make Amazon the internet’s most trustworthy, helpful, and delightful guide for customers on any shopping mission. Community Feedback materially impacts every retail marketplace, category and selling partner. Our features are a highly visible product, serving hundreds of millions of customers worldwide. Our team was the first to launch a customer-facing experience on Amazon that uses generative AI. Customer Reviews has received an overwhelming press coverage and S-Team visibility due to the launch of Review Highlights” feature - an AI-generated summary of text-based customer reviews. Since then, all customer-generated content has been used to power multiple high-profile experiences across the store such as Amazon’s Shopping AI Assistant (Rufus). The Principal Applied Scientist will be a thought leader and innovator to power this momentum and unlock further future value for customers. This role owns strategic projects in new and ambiguous areas leveraging advance machine learning techniques to create new scalable products. The customer problems to solve for can vary from how to rank and search content across the store, detect and mitigate abuse vectors such as fake reviews, to aggregate and summarize insights to help customers discover, compare, and purchase products at Amazon. This role requires experience and domain knowledge in NLP and ML, together with effective communication and collaboration skills to influence across multiple partnership teams including Search, Personalization, Rufus (Amazon’s Shopping AI Assistant) and Alexa. This position can be located in Barcelona, Madrid, or Berlin. Key job responsibilities As a Principal Applied Scientist, you are a trusted part of the technical leadership. 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. You solicit differing views across the organization and are willing to change your mind as you learn more. You are a hands-on scientific leader you are tackling intrinsically hard problems, whose solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team The Community Shopping team is part of the Shopping Discovery & Evaluation team, and our vision is to make Amazon the internet’s most trustworthy, helpful, and delightful guide for customers on any shopping mission. From the moment customers visit our store, we help them find what they are looking for and delight in our vast offering of products and services (Navigation Experience). We create immersive, visual, and personalized shopping experiences that inspire customers to kickstart their next shopping journey (Inspire, Amazon Native Player). We bring together trusted, authentic inputs from the community, and surface those inputs with the help of generative AI, to help customers confidently inform their next purchase (Community Feedback).

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 is seeking Applied Science Interns and Co-ops with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects within robotics. Examples of projects include allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, identifying objects and damage, and learning how to grasp all the products Amazon sells. As an Applied Science Intern/Co-op at Amazon Robotics, you will be working on one or more of our robotic technologies such as autonomous mobile robots, robot manipulators, and computer vision identification technologies. The intern/co-op project(s) and the internship/co-op location are determined by the team the student will be working on. Please note that by applying to this role you would be considered for Applied Scientist summer intern, spring co-op, and fall co-op roles on various Amazon Robotics teams. These teams work on robotics research within areas such as computer vision, machine learning, robotic manipulation, navigation, path planning, perception, optimization and more. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches

The Seller External Relations (SER) team ensures that Amazon is viewed globally by external audiences as a valuable, accessible, partner who respects and celebrates the success of its sellers. We develop strategic, data-supported, messaging and publish external reports that demonstrate and celebrate the positive experiences of sellers on Amazon to other sellers, the general public, and influentials (e.g., media and policymakers) with the goal of improving their perception of the experience and benefits of selling in our store. As Sr. Economist for SER, you will build the science models and the supporting structures needed to analyze, dive deep, and develop underlying data for our external messaging and reports. Your work will demonstrate how Amazon’s innovation enables seller success and supports their growth. You will have the opportunity to present findings to cross functional team partners to drive improvements. You will work closely with other Applied/Research/Data Scientists, Economists, Data Engineers, Software Development Engineers, Program Managers and Business Partners to solve challenging problems. You need be comfortable using intellect, curiosity and technical ability to develop innovative solutions to business problems. You will become an expert on aspects of the business to understand how to apply science and analytics to develop and substantiate our strategic messaging. You'll thrive if you enjoy tackling ambiguous challenges using the economics toolkit to identify and solve problems at scale. You will be expected to provide clear and concise explanation of results and approaches, provide opinion and guidance on problem solving, and present to senior leadership across multiple business units. The ideal candidate will have outstanding leadership skills, proven ability to develop, enhance, automate, and manage science models from end to end. The ideal candidate will have strong data mining and modeling skills and will be comfortable facilitating idea creation and working from concept through to execution. The ideal candidate must have demonstrated ability to manage medium-scale automation and modeling projects, identify requirements and build methodology and tools that are mathematically grounded but also explainable operationally, apply technical skills allowing the models to adapt to changing attributes. Key job responsibilities • Contribute to external messaging and report strategy based on science models and data analysis • Develop models to measure long term impact of the relationship between Amazon selling tools and seller behavior • Collaborate with product and engineering teams across the business to develop comprehensive models with diverse inputs • Use economical techniques to discover and develop underlying data for our strategic messaging and report work • Research, experiment and implement novel approaches. • Work closely with other scientists across teams. • Use the best practices in science: data integrity, design, test, and implementation and documentation. About the team SER is functionally diverse organization that includes a broad spectrum of skillsets and job families. We are a team of program and product managers, business analysts, creatives, storytellers, and small business evangelists - all important contributors to our work in ensuring that perception of Amazon’s support of small business matches reality. We have a supportive, fast-paced team culture, and we prioritize learning, growth, and helping each other to continuously raise the bar. Your direct team would be comprised of product and program managers, business analysts, and data engineers, with stakeholders and partners in similar functions accross the organization.

Are you excited about delighting millions of customers by driving the most relevant marketing initiatives? Do you thrive in a fast-moving, large-scale environment that values data-driven decision making and sound scientific practices? Amazon is seeking a Data Scientist . This team is focused on driving key priorities of a)core shopping that elevates the shopping CX for all shoppers in all lifecycle stages, b) developing ways to accelerate lifecycle progression and build foundational capabilities to address the shopper needs and c)Alternate shopping models We are looking for a Data Scientist to join our efforts to support the next generation of analytics systems for measuring consumer behavior using machine learning and econometrics at big data scale at Amazon. You will work machine learning and statistical algorithms across multiple platforms to harness enormous volumes of online data at scale to define customer facing products and measure customer responses to various marketing initiatives. The Data Scientist will be a technical player in a team working to build custom science solutions to drive new customers, engage existing customers and drive marketing efficiencies by leveraging approaches that optimize Amazon’s systems using cutting edge quantitative techniques. The right candidate needs to be fluid in: · Data warehousing and EMR (Hive, Pig, R, Python). · Feature extraction, feature engineering and feature selection. · Machine learning, causal inference, statistical algorithms and recommenders. · Model evaluation, validation and deployment. · Experimental design and testing.

Amazon's Search Science and AI team creates ML algorithms that connect customers around the world with products that delight them. We harness cutting-edge ML at Amazon's scale to make the customer experience easier and smoother. Our impact is large. For example, if your innovations save even 1 minute per customer per year, then for every 100 million customers, you save approximately 190 years of human effort. Key job responsibilities You will build search ranking systems that work for thousands of product types, billions of queries, and hundreds of millions of customers spread around the world. As an Applied Scientist you will find the next set of big improvements to ranking, leverage large datasets to understand the complexities of customer behavior, and get your hands dirty by building ML models that work at Amazon scale. In addition to typical topics in ranking, we are particularly interested in exploration techniques and reinforcement learning. A day in the life Our primary focus is improving search ranking systems. On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and guiding teams on best practices. You will also find yourself in meetings with business and tech leaders at Amazon communicating your next big initiative. About the team We are a team consisting of ML scientists and software engineers. Our interests and activities span machine learning for better ranking, statistics for better decision making, and infrastructure to make it all happen at scale and efficiently.