Careers

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: multimodal models, few-shot 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. For this role, we are looking for a science manager who has experience working in the intersection of vision, language and audio. We are located in Seattle, Pasadena, Palo Alto (USA) and in Haifa and Tel Aviv (Israel). About the team 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 in the cloud. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

The Worldwide Capacity Planning team is looking for a Research Scientist for their Forecasting Science team. Here you'll develop cutting-edge algorithms that transform complex analytical insights into powerful business solutions. You'll design and implement innovative and automated end-to-end forecasting solutions to support planning, and address critical demand challenges and service quality metrics. The ideal candidate will be an innovative problem-solver with exceptional communication skills, and passionate about turning data into meaningful organizational transformation, leveraging techniques like machine learning, econometric modeling, time series forecasting, statistical inference, and optimization to directly impact our bottom line and elevate our global customer service capabilities. Key job responsibilities - Drive model development and improvement with a combination of econometrics, statistics, machine learning and analytical techniques to create scalable solutions for business problems. - Collaborate with product, software engineering, research science, data engineering, and business leaders to build algorithms and models. - Design, develop and evaluate of highly innovative models for forecasting problems. - Identify business problems, and formulate scientific solutions. - Use the best practices in science: data integrity, design, test, and implementation and documentation. - Contribute to Amazon's Intellectual Property through patents and internal and external publications. A day in the life We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment. If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Benefits summary: Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team Worldwide Capacity Planning optimizes capacity across operations sites that help minimize customer wait time and route customers to the associate who can best resolve their issue, on the first contact. We build forecasting models and optimization tools that help predict the hourly capacity requirement, including when there are new device or game launches, or when there is a special event, such as Prime Day.

At Amazon, we strive every day to be Earth’s most customer centric company. Selling Partner Support Engagement (SPSE) Science delivers on this by building AI-enhanced experiences and automation that help to provide world class support to our global network of selling partners. We building at the cutting edge of Gen AI applications, working to tackle the many challenges that we confront caused by the volume, diversity, and complexity of our selling partner's needs… and we are always striving to do better. Do you want to join an innovative team who creatively applies techniques ranging from statistics and traditional machine learning to deep learning, natural language processing, and generative models? A team that drives our flywheel of improvement by hunting down opportunities to do better that are buried in tens of millions of solved cases? Are you interested in helping us redefine what world class support can be in an age of automation and AI, while prizing human empathy and ingenuity? The SPSE Science Team is looking for an Applied Scientist to build statistical and machine learning solutions that help us understand and solve our most challenging problems. We need to better understand our Sellers and the problems they face, to augment our human workforce with smarter tools, to anticipate problems so that we are prepared to deal with them, to automatically diagnose and resolve issues, and to identify opportunities to grow and improve. In this role, you will have ownership of the end-to-end development of solutions to complex problems and you will play an integral role in strategic decision-making. You will also work closely with engineers, operations teams, product owners to build ML pipelines, platforms and solutions that solve problems of defect detection, automation, and workforce optimization.

The Amazon Economics Team is hiring Economist Interns. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets to solve real-world business problems. Some knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with future job market placement. Roughly 85% of interns from previous cohorts have converted to full-time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.

The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a 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.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities - Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch. For example, starting from deep scientific thinking about new ways to support customers’ journeys through discovery, you analyze how customers discover, review and purchase Private Brands to innovate marketing and merchandising strategies. - Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results. - Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions. - Present results, reports, and data insights to both technical and business leadership. - Constructively critique peer research and mentor junior scientists and engineers. - Innovate and contribute to Amazon’s science community and external research communities.

Amazon Business (AB) is dedicated to serving the needs of business customers by building the most innovative B2B marketplace in the world. As part of Amazon Business Europe (ABEU), we’re scaling our business by integrating cutting-edge technology, advanced data science, and robust engineering solutions to create exceptional experiences for business customers across the EU. We are seeking a Sr. Manager of Data Science to lead a multi-disciplinary team driving innovation and operational excellence. This role is pivotal to our mission, combining strategic vision, hands-on leadership, and scientific expertise. You will manage a diverse team of data scientists, business intelligence and data engineers, working collaboratively to deliver high-impact scientific solutions and scalable systems to improve customer experience and drive business growth. The role focuses on identifying and solving ambiguous, high-value problems using state-of-the-art methodologies in machine learning (ML) as well as developing self-service data platforms for internal analytics. Key job responsibilities • Strategic Leadership: Define and execute the scientific vision for ABEU, aligning with broader Amazon Business goals. Drive cross-organizational initiatives, identifying opportunities to leverage data science and advanced analytics to solve critical business challenges. Partner with senior leaders to prioritize programs and align resources with strategic objectives. • Team Development: Hire, develop, and mentor a diverse team of scientists and engineers, fostering a culture of innovation, learning and excellence. • Science and Innovation: Design and implement cutting-edge ML models, analytics systems, and scalable architectures to support B2B e-commerce. Explore novel scientific approaches and contribute to advancements in areas such as sales automation, product recommendation, pricing optimization, and customer segmentation. Stay abreast of industry developments to inspire and implement state-of-the-art solutions, particularly in GenAI. • Stakeholder Engagement: Represent scientific and technical initiatives to senior leadership, articulating trade-offs and driving consensus. Collaborate across geographies and functions to integrate AB data into tools and systems, improving customer experience and operational scalability. • Operational Excellence: Develop the data foundation and metrics to enhance operational transparency and decision-making. Manage day-to-day technical operations, ensuring quality and efficiency across data pipelines, tools, and models.

We are seeking an exceptional Managing Economist to lead our Japan Stores Economics team at Amazon. We work in a wide range of areas that are critical to our customers and businesses, including speed, selection, pricing, and customer growth. This role offers a unique opportunity to shape Amazon Japan's key business decisions and growth strategies through economic principles and econometric science. Key job responsibilities • Lead, mentor, and promote a team of economists, fostering a culture of customer obsession, innovation, and analytical rigor. • Proactively drive science-based strategic decision makings across Japan businesses. • Bar raise science and make critical prioritization and resource allocation decisions to ensure the team delivers the highest impact. • Collaborate with product, engineering, and science teams in Japan and around the global to drive innovation together. • Represent the economist team in global forums and executive-level meetings. About the team Japan Stores Economics team is the central team for Amazon Japan's economic science. We are a compact team of highly skilled Ph.D. economists who work on some of the most impactful problems in Japan, including selection, delivery speed, pricing, and customer growth. We are not merely an internal consulting team -- we proactively work with the business teams to identify opportunities and shape how our business operates. We are a force-multiplier -- we bring together product, engineering, and finance teams to drive complex projects and deliver innovations to our customers.

mmPROS Surface Research Science seeks an exceptional Applied Scientist with expertise in forecasting and risk modeling to optimize Amazon's middle mile transportation network, the backbone of its logistics operations. Amazon's middle mile transportation network utilizes a fleet of semi-trucks, trains, and air planes to transport millions of packages per day as well as other freight between warehouses, vendor facilities, and customers, on time and at low cost. The mmPROS Surface Research Science team delivers innovation, models, algorithms, and other scientific solutions to efficiently plan and operate the middle mile surface (truck and rail) transportation network. The team focuses on large-scale problems in vehicle route planning, capacity procurement, network design, forecasting, and equipment re-balancing. Your role will be to build innovative forecasting, risk quantification, and other machine learning models to decide the optimal long-term and short-term strategy for truck capacity procurement and other planning problems. Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers. You will operate as part of a team of innovative, experienced scientists working on machine learning and optimization problems, and you will work in close collaboration with partners across product, engineering, business intelligence, and operations. Key job responsibilities - Design, develop, and implement forecasting models, risk models, and other machine learning models to inform our hardest planning decisions. - Implement machine learning and risk models in Amazon's production software. - Lead and partner with product, engineering, and operations teams to drive modeling and technical design for complex business problems. - Lead complex modeling and data analyses to aid management in making key business decisions and set new policies. - Write documentation for scientific and business audiences. About the team This role is part of mmPROS Surface Research Science. Our mission is to build the most efficient and optimal transportation network on the planet, using our science and technology as our biggest advantage. We aim to leverage cutting edge technologies in optimization, operations research, and machine learning to grow our businesses and solve Amazon's unique logistical challenges. Scientists in the team work in close collaboration with each other and with partners across product, software engineering, business intelligence, and operations. They regularly interact with software engineering teams and business leadership.

Have you ever ordered a product on Amazon and when that box-with-the-smile arrives, you wonder how it got to you so fast? Ever wondered where it came from and how much it cost Amazon? Wondered how Amazon designs its transportation network to scale and reliably deliver hundreds of millions of package to customer’s doorsteps? If so, EU Fulfillment Optimization team is for you. We use mathematical models, business analytics, algorithm design and statistics to improve decision-making capabilities across Operations and Amazon Logistics. Our objective is to create a reference for what the ideal transportation network looks like and build scalable audit mechanisms to assess and reduce the gap to the current network. We do so by treating system defects as gifts and solve anomalies in systems and their behavior to achieve business goals. We are based out of the EU headquarters in Luxembourg and looking for a talented and motivated Senior Applied Scientists to innovate and enhance our outbound network optimization and management products. In this role, you will solve highly visible problems that are important for senior leaders across organizations. Key job responsibilities We want you solve capacity optimization problems and re-define the way we approach resource allocation. You are someone: >> With business acumen with strategic, analytical, and critical thinking, who can understand the business challenge and develop technical and algorithmic solutions to those problems. >> Who understands technical software development life cycle and have experience to drive research teams towards business solutions >> Who drives strategic product communications across organizations providing clarity in decisions >> Has experience to develop scalable applied science solutions

Take Earth's most customer-centric company. Mix in hundreds of millions of shoppers spending tens of billions of pounds annually, an exciting opportunity to build next-generation shopping experiences, Amazon’s tremendous computational resources, and our extensive e-Commerce experience. What do you get? The most exciting Recommendations/Personalization position in the industry. Are you passionate about working on disruptive ideas? Are you obsessed with finding and building the most innovative and customer-friendly user experiences? Have you built and launched new experiences that impact shoppers all around the world? This is a unique opportunity that combines the ability to build exciting, new user experiences for Amazon's customers, with the opportunity to work with Big Data, Machine Learning, and other advanced techniques to provide the best personalized experience for hundreds of millions of Amazon's customers. More about the role: Our organization is growing our focus on the shopping experience for health & personal care, groceries, and other nascent product categories. We are responsible for one of the largest and fastest-growing businesses in the company, and are seeking an applied science manager to build a team of world-class software engineers and scientists that will deliver on an Amazon-critical charter. This team will need to deliver experiences that delight customers and create long-term value for the company. This role requires good technical skills, a deep understanding of machine learning approaches, and a passion for melding ML with great user experience/design. You must have a demonstrated ability for optimizing, developing, launching, and maintaining large-scale production systems. As a key member of the team, you will oversee all aspects of the software lifecycle: design, experimentation, implementation, and testing. 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 deliver, and long for the opportunity to build pioneering solutions to challenging problems. This role will demand resourcefulness and willingness to learn on both the technical and business side. The challenges we take on can involve a mix of large-scale distributed systems, big data technologies, machine learning science, and require a keen sense of customer obsession and long-term strategic thinking. About you: You're a former engineer or scientist who can see the bigger picture. While your career is full of individual wins, it is now more fulfilling when your team is able to build, deliver, and impress. You enjoy leading and mentoring others, and want to work on projects that require innovative and creative thinking alongside deep technical problem solving. You challenge yourself and others to constantly come up with better solutions, and can deliver on a technical roadmap that serves our customers and the business optimally. You communicate clearly, and hold yourself and your team to a high bar. As an Applied Science Manager, you will be responsible for ensuring your team successfully delivers on design, development, testing, experimentation, and the operations of algorithms, datasets, and systems your team owns. You should have an established track record of launching customer-facing experiences, deep technical ability, and excellent project management and communication skills. This role requires working closely with product management to define strategy and requirements, and leading a development team from design through delivery and subsequent operation. This position will also require regular communication with senior management on status, risks, and strategy. About our organization: Amazon’s Personalization organization is a small, high-performing group that leverages Amazon’s expertise in machine learning, big data, and distributed systems to deliver the best shopping experiences for our customers. We work end-to-end, from foundational backend systems to future-forward user interfaces. Our team’s culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making. We run hundreds of experiments each year and our work has revolutionized e-commerce with features such as “Customers Who Bought Also Bought” and “Recommended for You”. We care deeply about our customers, as well as the well-being and growth of our team members. Amazon’s internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow. This is a track record we are proud of and will continue to uphold. We are looking for creative and innovative leaders with a similar penchant for deeply-technical problem solving and the ability to lead, mentor, and deliver while upholding Amazon’s leadership principles.