Careers

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

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.

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

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.

Join us at Amazon as we reinvent shopping again! We're not just talking about improving the existing Amazon shopping experiences, we're building a brand-new world where shopping is effortless and intuitive through the power of generative AI. Leveraging state-of-the-art Large Language Models and generative AI, we're creating a live, two-way natural language conversational experience that is fast, helpful and trustworthy. As people turn to Amazon for deeper insights and understanding about products earlier and earlier in their shopping journeys, we're stepping up to the challenge by synthesizing complex information and multiple perspectives so customers can explore Amazon’s vast catalog to find exactly the products that solve their particular needs. Imagine having a back and forth conversation with an AI assistant helping you to articulate a problem you’re trying solve, effortlessly answering your product questions and giving you trustworthy advice and recommendations for what to buy. Also imagine a world where this same AI assistant reduces your mental load by proactively predicting and then fulfilling your shopping needs without you needing to interfere, thus saving you time and money along the way. We are building such an AI assistant to become the digital manifestation of the helpful salesperson that asks customers what they need, helps them navigate the store, waits unobtrusively while they look over the shelves, and helps them find complementary goods. What does economics have to teach this salesperson? Can we embed lessons from the behavioral literature to help customers? This is an opportunity to embed economic expertise into large scale generative models. This is just the beginning, and the future is yours to shape. We're searching for pioneers who are passionate about using technology and innovation to fundamentally change how customers shop, and who are ready to make a lasting impact on the industry and even disrupting how Amazon serves customers. You'll be a senior technical leader working with talented scientists, economists, engineers, and product leaders to innovate on behalf of our customers and help turn generative AI shopping into Amazon’s next business pillar. Key job responsibilities As the Principal Economist in the Shopping Economics team, you are a senior member of the technical leadership team, working with executives, principal engineers and scietists, and senior product leaders. Your economic thought leadership helps us to build new-to-world customer experiences that solve important problems for customers while creating new business models, ensuring Amazon is optimizing its innovation portfolio to maximally help customers solve their shopping problems. Solving problems like improving the match quality between customers’ heterogeneous needs and Amazon’s nearly infinite selection, articulating the economics of advertising in a conversation, using insights from economics to better align the LLM, and using deep learning techniques to measure substitution patterns and the economic value of engagement. You work with economists, scientists, and engineers Amazon-wide to rethink systems across the company to better optimize for helping customers through their entire shopping journey. You also develop and evangelize new mental models and new ways to measure the economic value of bleeding edge generative AI. As the senior economist in the team, you also guide the work and careers of other economists on the team.

AMZL Global Fleet and Products (GFP) organization is responsible for fleet programs and capacity for Last Mile deliveries. The Fleet Planning team is looking for a Data Scientist to drive the most efficient use of fleet. Last Mile fleet planning is a complex resource allocation problem. The goal of fleet allocation planning is to optimize the size and mix of fleet allocated to DSPs through various programs to improve branded fleet utilization. Changes in routes, last mile network, exiting DSPs and new DSP onboarding create continuous need for re-allocation of fleet to maintain an efficient network capacity. This requires allocation to adhere to various operational limits (repair network, EV range, Station Charging capability) and also match route’s cube need to vehicles capacity. As a Data Scientist on the Fleet Planning team (GFP), you will be responsible for building new science models (linear programs, statistical and ML models) and enhancing existing models for changing business needs. You would work with program managers in planning, procurement, redeployment, deployment, remarketing, variable fleet and infrastructure programs to build models that would support the requirements of all programs in a coherent plan. Key job responsibilities • Build models and automation for planners for generating vehicle allocation plans • Partner with program teams to test and measure success of implemented model • Lead reviews with senior leadership, deep dive model outputs and explain implications of model recommendations.

AWS Resilience owns service to prevent and response to availability and security issues for all AWS Services. In other words, we’re the people who keep the cloud running. We work on the most challenging problems, with constant new services and possible failure modes to prevent — and we’re looking for talented people who want to help. You’ll join a diverse team of software, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security and availability. You’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. AWS Incident Response is at the heart of the high availability of Amazon Web Services. We make customer impacting events shorter and less frequent by driving large scale event and incident response. Our automated tooling quickly identifies the cause of an issue and helps mitigate its impact, and much of our engineer time is spent on projects to improve the tooling and automation. We also provide manual incident management for AWS and other Amazon groups, directing the resolution of an issue with service teams, and diving deep into those events to drive improvements to the tooling. It's an exciting time to join our team as we are growing and expanding our offerings. Key job responsibilities You will own the organisation strategy relative to the usage of ML, GenAI and propose the best technology to advance our ability to better detect, faster root cause ,and correlate to prior incidents to shorten customer facing AWS incidents. Your work will enable us to identify gaps in our current strategy, learnings from past incidents. You will contribute to shortening incident response through deep analysis and introduction of new technology. About the team AWS Infrastructure Services (AIS) AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. About AWS Diverse Experiences AWS 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. 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 (gender diversity) 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.