Careers

Are you passionate about data science? Do you want to solve real customer problems through innovative technology? Do you enjoy working on scalable research and projects in a collaborative team environment? Do you want to see your science solutions directly impact millions of customers worldwide? At Amazon, we hire the best minds in technology to innovate and build on behalf of our customers. Customer obsession is part of our company DNA, which has made us one of the world's most beloved brands. We're looking for current Master's and PhD students with a passion for robotic research and applications to join us as Robotics Data Scientist Intern/Co-ops in 2026 to shape the future of robotics and automation at an unprecedented scale across. For these positions, our Robotics teams at Amazon are looking for students with a specialization in one or more of the research areas such as robotics, data science, computer vision, large language models, visual language models, statistics, machine learning, causal inference, deep learning, artificial intelligence, applied generative AI, operations research, data analysis, predictive modeling, and more! We're looking for curious minds who think big and want to define tomorrow's technology. At Amazon, you'll grow into the high-impact engineer you know you can be, supported by a culture of learning and mentorship. Every day brings exciting new challenges and opportunities for personal growth. By applying to this role, you will be considered for Robotics Data Science Intern/Co-op (2026) opportunities across various Robotics teams at Amazon with different robotics research focus, with internship positions available for multiple locations, durations (3 to 6+ months), and year-round start dates (winter, spring, summer, fall). Amazon intern and co-op roles follow the same internship structure. "Intern/Internship" wording refers to both interns and co-ops. Amazon internships across all seasons are full-time positions, and interns should expect to work in office, Monday-Friday, up to 40 hours per week typically between 8am-5pm. Specific team norms around working hours will be communicated by your manager. Interns should not have conflicts such as classes or other employment during the Amazon work-day. Applicants should have a minimum of one quarter/semester/trimester remaining in their studies after their internship concludes. The robotics internship join dates, length, location, and prospective team will be finalized at the time of any applicable job offers. In your application, you will be able to provide your preference of research interests, start dates, internship duration, and location. While your preference will be taken into consideration, we cannot guarantee that we can meet your selection based on several factors including but not limited to the internship availability and business needs of this role. Key job responsibilities • Design and implement state-of-the-art solutions for never-before-solved problems. • Collaborate closely with other research and robotics experts to design and run experiments, research new algorithms, and find new ways to improve Amazon Robotics analytics to optimize the Customer experience. • Partner with technology and product leaders to solve business problems using scientific approaches. • Build new tools and invent business insights that surprise and delight our customers. • Work to quantify system performance at scale, and to expand the breadth and depth of our analysis to increase the ability of software components and warehouse processes. • Work to evolve our library of key performance indicators and construct experiments that efficiently root cause emergent behaviors. • Engage with software development teams and warehouse design engineers to drive the evolution of the Amazon Robotics system, as well as the simulation engine that supports our work. About the team Learn more about Robotics at Amazon: https://www.aboutamazon.com/news/operations/amazon-robotics-robots-fulfillment-center https://www.aboutamazon.com/news/operations/amazon-million-robots-ai-foundation-model

The newest business group in AWS, Applied AI Solutions are built by AWS and AWS Partners to deliver applied AI solutions that leverage Amazon’s operational expertise and that businesses love and trust for their day-to-day success. Our ambition is to become a partner which companies can rely on to run their business every day, putting AI to work delivering better customer experience, operational excellence and speed. Our customers are evolving from builders to both builders and buyers. As the AWS customer base expands, we increasingly need to serve customers who prefer to “buy” Solutions in addition to those who prefer to “build.” Given the depth and breadth of offerings (200+ AWS services and features, and thousands of APN offerings), and various ways they can be put together, increasingly customers need prescriptive guidance and automation to reduce the number of decisions they need to make and minimize last-mile development to adopt AWS. Are you excited about developing state-of-the-art AI solutions and designs using large data sets to solve real world problems? Do you have proven analytical capabilities and can multi-task and thrive in a fast-paced environment? Do you enjoy the prospect of solving real-world problems that have not been solved at scale anywhere before? Along the way, you’ll get opportunities to be a disruptor, innovator, and a problem solver—someone who truly enables machine learning to create significant impacts. You will collaborate closely with cross-functional business and engineering teams to identify and deliver high-impact use cases for Generative AI. You will design, develop, and evaluate Generative AI models and agents. You will partner with engineering teams to ensure seamless model deployment and integration into production systems. The ideal candidate thrives in ambiguity, builds collaborative relationships, moves fast, and is passionate about the customer experience. They lead by example, can communicate effectively with a wide variety of audiences and are comfortable pitching new ideas. If you love finding innovative solutions to complex and ambiguous problems, this may be the opportunity for you.

Do you want to join a team of innovative scientists to research and develop generative AI technology that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment? Amazon Connect is a highly disruptive cloud-based contact center from AWS that enables businesses to deliver intelligent, engaging, dynamic, and personalized customer service experiences. The Agentic Customer Experience organization is responsible for weaving native-AI across the Connect application experiences delivered to end-customers, agents, and managers/supervisors. The Interactive AI Science team, serves as the cornerstone for AI innovation across Amazon Connect, functioning as the sole science team support high impact product including Amazon Q in Connect, Contact Lens and other key initiatives. As an Sr. Applied Scientist on our team, you will work closely with senior technical and business leaders from within the team and across AWS. You distill insight from huge data sets, conduct cutting edge research, foster ML models from conception to deployment. You have deep expertise in machine learning and deep learning broadly, and extensive domain knowledge in natural language processing, LLMs and Agentic AI, etc. You are comfortable with quickly prototyping and iterating your ideas to build robust ML models using technology such as PyTorch, Tensorflow and AWS Sagemaker. The ideal candidate has the ability to understand, implement, innovate on the state-of-the-art Agentic AI based systems. We have a rapidly growing customer base and an exciting charter in front of us that includes solving highly complex engineering and scientific problems. We are looking for passionate, talented, and experienced people to join us to innovate on modern contact centers in the cloud. The position represents a rare opportunity to be a part of a fast-growing business soon after launch, and help shape the technology and product as we grow. You will be playing a crucial role in developing the next generation contact center, and get the opportunity to design and deliver scalable, resilient systems while maintaining a constant customer focus. Learn more about Amazon Connect here: https://aws.amazon.com/connect/ About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the 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.

Interested in driving thought leadership by building machine learning solutions that will derive actionable insights about the complex economy of Amazon’s retail business? Whether you’re passionate about building highly scalable and reliable systems or a scientist who likes to solve novel business problems, the Automated Profitability AI team is the place for you. We use machine learning, generative AI, causal inference, and econometric/economic modeling to analyze Amazon’s relationships with vendors, and recommend actions that generate mutual growth. We are an interdisciplinary team of applied scientists, engineers, and economists building solutions to solve some of the toughest business problems at Amazon. As an Applied Scientist, you bring structure to ambiguous business problems and use science, logic, and practical experience to decompose them into scalable solutions. You use your broad experience with a diversity of machine learning methods to determine the right approach to solve complex business problems that can have humans-in-the-loop and may be data sparse. You provide feedback to other scientists on the team, help them define problems and solutions, and mentor junior scientists. You’re committed to on-going learning and can quickly acquire the knowledge you need to address novel problems. You work effectively with science, engineering, economics and business teams. Key job responsibilities - Apply machine learning and modeling techniques including deep learning, generative AI, reinforcement learning and causal inference methods to automate negotiation processes and drive business growth for Amazon and its vendors - Work with business subject-matter-experts (SMEs) to develop models that support human decision making during complex business negotiations - Design experiments and metrics that can quantify the impact of models on business outcomes - Collaborate with engineering teams to design and implement software solutions for science problems - Contribute to Amazon and broader research communities by producing publications About the team The Automated Profitability Team transforms how Amazon manages and optimizes procurement. We leverage AI to empower Worldwide Stores and Vendors to make "best-in-class" economic decisions with contextually relevant insights, and recommendations that align with broader business objectives.

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. This specific economist role is part of the Automated Profitability Management (APM) team whose vision is to offer the world’s most advanced suite of products to optimize and manage the contractual agreements between a retailer and its suppliers. Our teams build software and machine learning models to optimize contract negotiations, and exchange of goods between Amazon Retail and tens of thousands of brands ("vendors") offering millions of products available to hundreds of millions of Amazon customers worldwide. We handle product costs (How much should Amazon pay for this product?) but also cover supply chain (Who pays the initial shipping costs?), reverse-logistics (Who pays for damaged products? What about unsold inventory?) and more. Our mission is to provide to our customers the world’s largest product assortment at competitive prices, through long term partnership with our vendors. You will build econometrics and machine learning (ML) models that combine internal cost and pricing data, with external inflation signals (e.g. commodity prices, labor rates, transportation costs) to determine where contract changes are warranted. Where possible, you will design and conduct experiments to estimate the long term impact of the new contracts on customers, vendors, and Amazon. To do so, you will work closely with other economists, ML scientists, product managers, and software developers to implement and scale your solutions. Key job responsibilities - Develop econometric and causal models to improve the outcome of contract negotiations for all products offered by Amazon Retail worldwide. - Determine the causal impacts of systems, strategy, or inputs changes on business growth and profitability through experiments or observational methods. - Collaborate with product managers, applied scientists, economists, and software developers to incorporate economic models into negotiation tooling.

Are you ready to be at the forefront of Agentic AI innovation and redefine the future of communication? Join our dynamic Alexa Connections team as a Sr. Applied Scientist, and lead futuristic initiatives that will shape the next generation of intelligent, conversational experiences. In this role, you'll work at the intersection of disruptive AI technologies and real-world impact, making a difference for millions of customers. You'll collaborate with a team of passionate professionals who are as excited about innovation as you are, and together, you'll push the boundaries of what's possible with Alexa+. As a Sr. Applied Scientist, you'll drive the development of novel algorithms and modeling techniques to advance the state of the art with LLMs and real-time Agentic AI solutions that power our next-generation communication features. You'll work closely with cross-functional teams, including product management, engineering, design, and data, to design and deliver innovative solutions that leverage these AI technologies to enable seamless, intelligent communication experiences. You'll also lead the integration of these advanced AI systems into Alexa's core capabilities, ensuring a seamless and intuitive user experience. Key job responsibilities - Develop new inference and training techniques to improve the performance of Large Language Models for Smart Home control and Automation - Develop robust techniques for synthetic data generation for training large models and maintaining model generalization - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environment, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues - Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done About the team Alexa Connections aspires to make Alexa+ the world’s most trusted connection assistant for getting things done and creating moments of joy. Our vision emphasizes a) Trust as our foundation for becoming a daily habit, knowing our customers have plentiful choices, b) Completion of end-to-end customer journeys, beyond shipping features, and c) Joy through personalized, proactive experiences, that create a memory.

The WW DSP Analytics team is a centralized analytics organization within Amazon's Last Mile Delivery Service Partner (DSP) program. We build best-in-class solutions that enable data-driven decision making across our global DSP ecosystem. Our team partners with internal stakeholders, DSP owners, and cross-functional teams to deliver insights that drive operational excellence, business growth, and the success of small business owners in Last Mile delivery. Our work directly impacts customer experience, driver and station associate experience, DSP success, and Amazon's sustainable growth. We are seeking a passionate Data Scientist with strong machine learning and analytical skills to join our team. You will work on challenging problems in the delivery planning space, applying data science rigor to generate actionable insights that support DSP performance measurement and continuous improvement. Key job responsibilities Develop Science Solutions for DSP Performance: Design and implement data science solutions to optimize Delivery Service Partner (DSP) operations, capacity planning, and performance measurement across the global DSP network Apply Advanced Machine Learning Techniques: Leverage solid research experience in Machine Learning and statistical modeling to identify opportunities for improving DSP analytics, forecasting models, and performance measurement systems Optimize DSP Program Policies and Sentiment Risks: Analyze sentiment risks and enhance existing algorithms that support DSP program management, including scorecard metrics, capacity reliability models, and performance evaluation frameworks Analyze Business Requirements with Return on Investment (ROI) calculation: Demonstrate superior logical thinking by quickly approaching large, ambiguous problems, translating high-level DSP program requirements into mathematical models, and applying models to predict the return on investment. Build Production-Scale Analytics: Contribute to the development and deployment of scalable data models, dashboards, and automated reporting systems that enable self-service analytics for DSP stakeholders Accelerate GenAI footprint: Partner with Data Engineers to expand our GenAI tools and improve developer productivity along with raising the bar on data quality. Conduct Independent Data Analysis: Mine and analyze complex datasets across multiple domains (performance metrics, financial data, operational data) using programming and statistical analysis tools to generate actionable insights Thrive in a Collaborative Environment: Excel in a fast-paced analytics organization that encourages collaborative and creative problem-solving, measure and communicate analytical risks, constructively critique peer work, and align research focuses with DSP program strategic needs Partner Cross-Functionally: Work closely with Business Intelligence Engineers, program teams, and DSP stakeholders to define KPIs, validate analytical approaches, and ensure insights drive meaningful business outcomes

The Amazon Smart Vehicles (ASV) science team is seeking a passionate and skilled Applied Scientist with extensive expertise in advanced LLM technologies. This role involves innovating in rapidly evolving areas of AI research, focusing on creating personalized services to enhance drivers' and passengers' experiences. Your work will aim to simplify their lives, keep them informed, entertained, productive, and safe on the road, with direct application to prominent Amazon products. If you have extensive expertise in LLMs, natural language processing, and machine learning, along with experience in high-performing research teams, this could be the perfect opportunity for you. Our dynamic and fast-paced environment demands a high level of independence in decision-making and the ability to drive ambitious research initiatives through to production. You will collaborate closely with other science and engineering teams, as well as business stakeholders, to ensure your contributions are both impactful and delivered with maximum efficiency. Key job responsibilities - Leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI) - Work with talented peers to lead the development of novel algorithms and modeling techniques to advance the state of the art with LLMs - Collaborate with other science and engineering teams as well as business stakeholders to maximize the velocity and impact of your contributions About the team This is an exciting moment to lead in AI research and application. As part of the Amazon Smart Vehicles science team, you have the opportunity to shape the future by enhancing information-driven experiences for Amazon customers around the globe. Your work will directly influence customers through innovative products and services powered by language and multimodal technology!

Are you seeking an environment where you can drive innovation? Do you want to be at the forefront of solving the toughest real-world supply chain problems? Do you want to play a key role in the future of Amazon's Stores business? Come and join us! Supply Chain Optimization Technologies (SCOT) owns Amazon's global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon's business goals and to make our customers happy. We decide how to place and move inventory within Amazon's fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars worldwide. Check our website if you are curious to learn more about the breadth of problems we tackle: https://www.amazon.science/tag/supply-chain-optimization-technologies We are seeking a Sr. Manager of Applied Science with expertise in Statistical Machine Learning and/or Reinforcement Learning to drive research, development, and deployment of AI technology that empowers SCOT to build, run, and continuously improve the world's most efficient supply chain. To achieve this goal, we accelerate ML / RL software adoption through our partnerships and infrastructure. In this role, you will manage a team of scientists tasked researching the next generation of solutions to power buying, placement, and fulfillment decisions, while translating customer needs into reusable software infrastructure that accelerates adoption and deployment. Key job responsibilities - Lead technical innovation in reinforcement learning applications for complex supply chain environments, solving unique challenges and ensuring practical implementation in real-world deployments. - Build and develop a high-performing team by fostering collaboration, mentoring top talent, and creating a balanced culture of technical excellence. - Bridge technical possibilities with business requirements by providing strategic judgment, evaluating technology feasibility, and managing implementation risk. - Drive cross-functional collaboration by interfacing with product teams, leadership, and partner organizations to translate business needs into technical solutions.