Careers

Application deadline: Applications will be accepted on an ongoing basis Amazon Ads is re-imagining advertising through cutting-edge generative artificial intelligence (AI) technologies. We combine human creativity with AI to transform every aspect of the advertising life cycle—from ad creation and optimization to performance analysis and customer insights. Our solutions help advertisers grow their brands while enabling millions of customers to discover and purchase products through delightful experiences. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground in product and technical innovations. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Why you’ll love this role: This role offers unprecedented breadth in ML applications and access to extensive computational resources and rich datasets that will enable you to build truly innovative solutions. You'll work on projects that span the full advertising life cycle, from sophisticated ranking algorithms and real-time bidding systems to creative optimization and measurement solutions. You'll work alongside talented engineers, scientists, and product leaders in a culture that encourages innovation, experimentation, and bias for action, and you’ll directly influence business strategy through your scientific expertise. What makes this role unique is the combination of scientific rigor with real-world impact. You’ll re-imagine advertising through the lens of advanced ML while solving problems that balance the needs of advertisers, customers, and Amazon's business objectives. Your impact and career growth: Amazon Ads is investing heavily in AI and ML capabilities, creating opportunities for scientists to innovate and make their marks. Your work will directly impact millions. Whether you see yourself growing as an individual contributor or moving into people management, there are clear paths for career progression. This role combines scientific leadership, organizational ability, technical strength, and business understanding. You'll have opportunities to lead technical initiatives, mentor other scientists, and collaborate with senior leadership to shape the future of advertising technology. Most importantly, you'll be part of a community that values scientific excellence and encourages you to push the boundaries of what's possible with AI. Watch two Applied Scientists at Amazon Ads talk about their work: https://www.youtube.com/watch?v=vvHsURsIPEA Learn more about Amazon Ads: https://advertising.amazon.com/ Key job responsibilities As a Senior Applied Scientist in Amazon Ads, you will: - Research and implement cutting-edge ML approaches, including applications of generative AI and large language models - Develop and deploy innovative ML solutions spanning multiple disciplines – from ranking and personalization to natural language processing, computer vision, recommender systems, and large language models - Drive end-to-end projects that tackle ambiguous problems at massive scale, often working with petabytes of data - Build and optimize models that balance multiple stakeholder needs - helping customers discover relevant products while enabling advertisers to achieve their goals efficiently - Build ML models, perform proof-of-concept, experiment, optimize, and deploy your models into production, working closely with cross-functional teams including engineers, product managers, and other scientists - Design and run A/B experiments to validate hypotheses, gather insights from large-scale data analysis, and measure business impact - Develop scalable, efficient processes for model development, validation, and deployment that optimize traffic monetization while maintaining customer experience

We're on a journey to build something new a green field project! Come join our team and build new discovery and shopping products that connect customers with their vehicle of choice. We're looking for a talented Applied Scientist to join our team of product managers, designers, and engineers to design, and build innovative automotive-shopping experiences for our customers. This is a great opportunity for an experienced engineer to design and implement the technology for a new Amazon business. We are looking for a Applied Scientist to design, implement and deliver end-to-end solutions. We are seeking passionate, hands-on, experienced and seasoned Applied Scientist who will be deep in code and algorithms; who are technically strong in building scalable computer vision machine learning systems across item understanding, pose estimation, class imbalanced classifiers, identification and segmentation.. You will drive ideas to products using paradigms such as deep learning, semi supervised learning and dynamic learning. As a Applied Scientist, you will also help lead and mentor our team of applied scientists and engineers. You will take on complex customer problems, distill customer requirements, and then deliver solutions that either leverage existing academic and industrial research or utilize your own out-of-the-box but pragmatic thinking. In addition to coming up with novel solutions and prototypes, you will directly contribute to implementation while you lead. A successful candidate has excellent technical depth, scientific vision, project management skills, great communication skills, and a drive to achieve results in a unified team environment. You should enjoy the process of solving real-world problems that, quite frankly, haven’t been solved at scale anywhere before. Along the way, we guarantee you’ll get opportunities to be a bold disruptor, prolific innovator, and a reputed problem solver—someone who truly enables AI and robotics to significantly impact the lives of millions of consumers. Key job responsibilities Architect, design, and implement Machine Learning models for vision systems on robotic platforms Optimize, deploy, and support at scale ML models on the edge. Influence the team's strategy and contribute to long-term vision and roadmap. Work with stakeholders across , science, and operations teams to iterate on design and implementation. Maintain high standards by participating in reviews, designing for fault tolerance and operational excellence, and creating mechanisms for continuous improvement. Prototype and test concepts or features, both through simulation and emulators and with live robotic equipment Work directly with customers and partners to test prototypes and incorporate feedback Mentor other engineer team members. A day in the life - 4+ years of building machine learning models for retail application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning - Demonstrated expertise in computer vision and machine learning techniques.

Do you ever struggle to explain your work? How's this: "Do you shop at Amazon? Do you know that box that says 'Add to Cart' and shows a price? Our team owns the model which picks that offer and the customer experience around the display of the offer price and the elements surrounding the 'Add to Cart' button which inform a purchase decision. We pick and display offers several billion times a day across all surfaces (mobile app, mobile web, desktop, Alexa shopping) worldwide. Our mission is to be the world’s first and most trusted choice for every customer on earth to discover and evaluate any product or service. Our team blends machine learning models to rank and select the best offer from the most trusted merchant for all products sold on Amazon along with a world-class front-end user experience for offer comparison to our global customers. We are responsible for the experiences and services that enable developers, including our own, to create tailored shopping experiences for every customer, product, business and marketplace offered by Amazon. We build scalable and extensible frameworks which allow for many teams at Amazon to innovate within the Offers Experience in a federated manner. If you are passionate about influencing and delivering the next-generation Amazon customer buying experience, we want to meet you. We are looking for a Senior Economist to join one of the most impactful and visible teams in Amazon. In this role you will work with business stakeholders throughout Amazon and provide technical direction and business expertise to strategize and help launch new businesses and features for our customers. You will use data to justify customer friendly decisions and present customer and financial impact of the changes we make to our stakeholders. You will work closely with other economists, engineers, product managers, applied scientists, TPMs, managers, and senior leadership team to understand and drive business impact. Successful candidates will have experience working on multiple projects with different stakeholders, make data driven decisions, have strong communication skills to interact with executives, non-technical and technical individuals and have a high technical bar along with a passion for people and project management. This is an opportunity to work with a team that drives one of the most coveted real estate in the E-commerce, the Amazon ‘Buy Box’ on Amazon Product Detail Page, Amazon Search Page , multiple buying widgets etc. on the Amazon desktop, mobile and tablet environments.

We are seeking an exceptional Sr. Manager, Applied Science - Global Selling Partner Risk Intelligence and Prevention, to lead the development and implementation of advanced AI solutions that will transform how we prevent bad actors from operating in our store and enable Selling Partners to start and grow their business without fear of disruption, so that customers and Selling Partners across the globe trust us and have confidence in the integrity of Amazon’s store. This role will focus on leveraging large language models and other generative AI technologies to enhance decision-making processes, automate complex risk assessment tasks, and improve operational efficiency in selling partner risk management. Key job responsibilities • Set up the vision, mission and a 3-year science plan for the selling partner risk management • Lead and manage a team of scientists, business intelligence engineers, business analysts, TPMs, to build foundational and domain-specific solutions that prevent bad actors from operating in our store • Identify and prioritize high-impact opportunities for AI-driven transformation to make Amazon the most trusted store for our customers and selling partners • Mentor and guide team members to achieve their career goals and objectives About the team Trust and Store Integrity Science is a new org established in 2024. We are missioned to leverage the fast evolving AI advancements to transform how we prevent bad actors in our stores, across science, engineering, product and program management, and operations.

Amazon LEO is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Amazon LEO will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity. We are seeking a Scientist to own analytics, scientistic research, validation, and development of our phased array systems across customer terminals and satellite-deployed terminals. In this role, you will transform raw test and telemetry data into actionable insights and automated checks that ensure every deployed system performs to expectations. You will build data and ML pipelines that detect calibration issues, quantify array performance, validate new algorithms, and increase the effectiveness, reproducibility, and automation of our antenna, calibration and deployment workflows. This role sits at the intersection of array processing, data science, and systems engineering, working closely with calibration/validation, phased array systems, RF communications, and test engineering teams. Key job responsibilities - Own metrics and data models that describe end-to-end calibration and system performance for customer terminals and satellite-deployed terminals, from factory test through field deployment. - Design and implement ML and statistical methods (e.g., anomaly detection, drift detection, predictive failure models, classification/regression) to identify mis-calibration, degraded performance, and emerging issues in large fleets of terminals and arrays. - Develop visualization and analytics tools (dashboards, reports, interactive notebooks) to help engineers quickly understand array performance, calibration residuals, and system margins across time, geography, and configurations. - Work with antenna, RF systems, and calibration engineers to define quantitative acceptance criteria for calibration and system validation, and encode those criteria into automated checks and workflows. - Design and run experiments and simulations that compare predicted vs. measured performance, closing the loop between link/array models and deployed hardware. - Build and maintain data pipelines that ingest lab data, chamber results, manufacturing test data, and in-field telemetry into secure, high-quality datasets suitable for analysis and ML training. - Prototype, test, and deploy machine learning and analytics applications in the cloud, partnering with software and systems teams to ensure solutions are scalable, maintainable, and integrated into existing tools and monitoring systems. - Provide clear, data-driven recommendations to improve calibration algorithms, test strategies, and system design; communicate findings to technical and non-technical stakeholders. - Mentor engineers and analysts in data best practices, experiment design, and interpretation of calibration and performance metrics. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. A day in the life You will work with engineers to process large amounts of data and work through full designs to fully understand the Amazon Leo satellites and customer terminals from lab test benches to fully integrated customer terminals. Your tools and systems will prove out the performance of one of the most advanced communication systems ever built. You’ll collaborate with RF and systems engineers, see your models run using real hardware data, and make daily decisions that directly affect the readiness of Leo’s payload and customer terminal products. The data you analyze and scalable systems you build will enable critical data collection, system analysis, and calibration pipelines that ensure Leo hardware performs flawlessly on Earth and in orbit. About the team Our team owns the full performance lifecycle of Leo’s antenna systems from early concept testing and calibration to final product release. We operate at the intersection of RF hardware, software automation, and large-scale system integration. You’ll work closely with antenna, DSP, and system development engineers, contributing to test frameworks, manufacturing support, and performance validation. We leverage AWS tools and scalable software architectures to accelerate development, automate validation, and deliver reliable test systems used across the entire Leo organization. If you want to work on real hardware, influence product performance, and see your work scale to millions of users worldwide this is the place to do it

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 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 who work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. 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 empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas. Amazon internships across all seasons are full-time positions, and intern/co-ops 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. Please note that by applying to this role you would be considered for Data Science Intern and Co-op in 2026 (winter, spring, summer, fall) roles on various Robotics teams. You will be able to provide your preference of location and start date during the application process but, we cannot guarantee that we can meet your selection based on several factors including but not limited to the availability and business needs of this role. Finalization on the location and start dates available will be provided to you at the time of job offer. 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 Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics https://www.aboutamazon.com/news/operations/amazon-robotics-robots-fulfillment-center https://www.aboutamazon.com/news/operations/amazon-million-robots-ai-foundation-model