Careers

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 (CX) org 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 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, generative AI and LLM Agents evaluation and optimization, 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. 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.

Amazon is looking for talented Postdoctoral Scientists to join our Robotics team for a one-year, full-time research position. Postdoctoral Scientists will innovate in key areas of computer vision and manipulation challenges in Amazon warehouses. The Amazon Robotics team seeks to automate the picking activities in Amazon AR Sortable FCs by retrofitting into existing stations. The team develops robotic manipulators, both the related hardware and software (including machine learning approaches). The team was formed in 2022 and is based in Berlin. Our team focuses on solving computer vision and manipulation challenges in Amazon warehouses. For example, how can robots interact with the fabric pods used to store items. The technical challenges include 3D scene understand for items in clutter, identification of target items in the scene, and placement and/or removal of target items. As the solution space is open ended, the team is looking for postdoc candidates who are excited to apply and advance the state-of-the-art algorithms to this domain. Key job responsibilities Key job responsibilities In this role you will: • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.

Amazon Economics is seeking Structural Economist (STRUC) Interns who are passionate about applying structural econometric methods to solve real-world business challenges. STRUC economists specialize in the econometric analysis of models that involve the estimation of fundamental preferences and strategic effects. In this full-time internship (40 hours per week, with hourly compensation), you'll work with large-scale datasets to model strategic decision-making and inform business optimization, gaining hands-on experience that's directly applicable to dissertation writing and future career placement. Key job responsibilities As a STRUC Economist Intern, you'll specialize in structural econometric analysis to estimate fundamental preferences and strategic effects in complex business environments. Your responsibilities include: - Analyze large-scale datasets using structural econometric techniques to solve complex business challenges - Applying discrete choice models and methods, including logistic regression family models (such as BLP, nested logit) and models with alternative distributional assumptions - Utilizing advanced structural methods including dynamic models of customer or firm decisions over time, applied game theory (entry and exit of firms), auction models, and labor market models - Building datasets and performing data analysis at scale - Collaborating with economists, scientists, and business leaders to develop data-driven insights and strategic recommendations - Tackling diverse challenges including pricing analysis, competition modeling, strategic behavior estimation, contract design, and marketing strategy optimization - Helping business partners formalize and estimate business objectives to drive optimal decision-making and customer value - Build and refine comprehensive datasets for in-depth structural economic analysis - Present complex analytical findings to business leaders and stakeholders

Amazon Economics is seeking Reduced Form Causal Analysis (RFCA) Economist Interns who are passionate about applying econometric methods to solve real-world business challenges. RFCA represents the largest group of economists at Amazon, and these core econometric methods are fundamental to economic analysis across the company. In this full-time internship (40 hours per week, with hourly compensation), you'll work with large-scale datasets to analyze causal relationships and inform strategic business decisions, gaining hands-on experience that's directly applicable to dissertation writing and future career placement. Key job responsibilities As an RFCA Economist Intern, you'll specialize in econometric analysis to determine causal relationships in complex business environments. Your responsibilities include: - Analyze large-scale datasets using advanced econometric techniques to solve complex business challenges - Applying econometric techniques such as regression analysis, binary variable models, cross-section and panel data analysis, instrumental variables, and treatment effects estimation - Utilizing advanced methods including differences-in-differences, propensity score matching, synthetic controls, and experimental design - Building datasets and performing data analysis at scale - Collaborating with economists, scientists, and business leaders to develop data-driven insights and strategic recommendations - Tackling diverse challenges including program evaluation, elasticity estimation, customer behavior analysis, and predictive modeling that accounts for seasonality and time trends - Build and refine comprehensive datasets for in-depth economic analysis - Present complex analytical findings to business leaders and stakeholders

Amazon Economics is seeking Forecasting, Macroeconomics and Finance (FMF) Economist Interns who are passionate about applying time-series econometric methods to solve real-world business challenges. FMF economists interpret and forecast Amazon business dynamics by combining advanced time-series statistical methods with strong economic analysis and intuition. In this full-time internship (40 hours per week, with hourly compensation), you'll work with large-scale datasets to forecast business trends and inform strategic decisions, gaining hands-on experience that's directly applicable to dissertation writing and future career placement. Key job responsibilities As an FMF Economist Intern, you'll specialize in time-series econometric analysis to understand, predict, and optimize Amazon's business dynamics. Your responsibilities include: - Analyze large-scale datasets using advanced time-series econometric techniques to solve complex business challenges - Applying frontier methods in time series econometrics, including forecasting models, dynamic systems analysis, and econometric models that combine macro and micro data - Developing formal models to understand past and present business dynamics, predict future trends, and identify relevant risks and opportunities - Building datasets and performing data analysis at scale using world-class data tools - Collaborating with economists, scientists, and business leaders to develop data-driven insights and strategic recommendations - Tackling diverse challenges including analyzing drivers of growth and profitability, forecasting business metrics, understanding how customer experience interacts with external conditions, and evaluating short, medium, and long-term business dynamics - Build and refine comprehensive datasets for in-depth time-series economic analysis - Present complex analytical findings to business leaders and stakeholders

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

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.

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.

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.

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.