Careers

The Sponsored Products and Brands (SPB) team at Amazon Ads is transforming advertising through generative AI technologies. We help millions of customers discover products and engage with brands across Amazon.com and beyond. Our team combines human creativity with artificial intelligence to reinvent the entire advertising lifecycle—from ad creation and optimization to performance analysis and customer insights. We develop responsible AI technologies that balance advertiser needs, enhance shopping experiences, and strengthen the marketplace. Our team values innovation and tackles complex challenges that push the boundaries of what's possible with AI. Join us in shaping the future of advertising. Key job responsibilities This role will redesign how ads create personalized, relevant shopping experiences with customer value at the forefront. Key responsibilities include: - Design and develop solutions using GenAI, deep learning, multi-objective optimization and/or reinforcement learning to transform ad retrieval, auctions, whole-page relevance, and shopping experiences. - Partner with scientists, engineers, and product managers to build scalable, production-ready science solutions. - Apply industry advances in GenAI, Large Language Models (LLMs), and related fields to create innovative prototypes and concepts. - Improve the team's scientific and technical capabilities by implementing algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor junior scientists and engineers to build a high-performing, collaborative team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value.

At Amazon Robotics, we design advanced robotic systems capable of intelligent perception, learning, and action alongside humans, all on a large scale. Our goal is to develop robots that increase productivity and efficiency at the Amazon fulfillment centers while ensuring the safety of workers. We are seeking an Applied Scientist to develop innovative, scalable solutions in feedback control and state estimation for robotic systems, with a focus on contact-rich manipulation tasks. In this role, you will formulate physics-based models of robotic systems, perform analytical and numerical studies, and design control and estimation algorithms that integrate fundamental principles with data-driven techniques. You will collaborate with a world-class team of experts in perception, machine learning, motion planning, and feedback controls to innovate and develop solutions for complex real-world problems. As part of your work, you will investigate applicable academic and industry research to develop, implement, and test solutions that support product features. You will also design and validate production designs. To succeed in this role, you should demonstrate a strong working knowledge of physical systems, a desire to learn from new challenges, and the problem-solving and communication skills to work within a highly interactive and experienced team. Candidates must show a hands-on passion for their work and the ability to communicate their ideas and concepts both verbally and visually. Key job responsibilities - Research, design, implement, and evaluate feedback control, estimation, and motion-planning algorithms, ensuring effective integration with perception, manipulation, and system-level components. - Develop experiments, simulations, and hardware prototypes to validate control algorithms, and optimization techniques in contact-rich manipulation and other challenging scenarios. - Collaborate with software engineering teams to enable scalable, real-time, and maintainable implementations of algorithms in production systems. - Partner with cross-functional teams across hardware, systems engineering, science, and operations to transition algorithms from early prototyping to robust, production-ready solutions. - Engage with stakeholders at all levels to iterate on system design, define requirements, and drive integration of control and estimation capabilities into Amazon Robotics platforms. A day in the life 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 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!

Come build the future of entertainment with us. Are you interested in helping shape the future of movies and television? Do you want to help define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at any time and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on We are seeking an exceptional Applied Scientist to join our Prime Video Sports personalization team in Israel. Our team is dedicated to developing state-of-the-art science to personalize the customer experience and help customers seamlessly find any live event in our selection. You will have the opportunity to work on innovative, large-scale projects that push the boundaries of what's possible in sports content delivery and engagement. Your expertise will be crucial in tackling complex challenges such as information retrieval, sequential modeling, realtime model optimizations, utilizing Large Language Models (LLMs), and building state-of-the-art complex recommender systems. Key job responsibilities We are looking for an Applied Scientist with domain expertise in Personalization, Information Retrieval, and Recommender Systems, or general ML to develop new algorithms and end-to-end solutions. As part of our team of applied scientists and software development engineers, you will be responsible for researching, designing, developing, and deploying algorithms into production pipelines. Your role will involve working with cutting-edge technologies in recommender systems and search. You'll also tackle unique challenges like temporal information retrieval to improve real-time sports content recommendations. As a technologist, you will drive the publication of original work in top-tier conferences in Machine Learning and Recommender Systems. We expect you to thrive in ambiguous situations, demonstrating outstanding analytical abilities and comfort in collaborating with cross-functional teams and systems. The ideal candidate is a self-starter with the ability to learn and adapt quickly in our fast-paced environment. About the team We are the Prime Video Sports team. In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues like NFL Thursday Night Football, Tennis majors like Roland-Garros and English Premier League to list a few and are broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.

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.

The AWS Neuron Science Team is looking for talented scientists to enhance our software stack, accelerating customer adoption of Trainium and Inferentia accelerators. In this role, you will work directly with external and internal customers to identify key adoption barriers and optimization opportunities. You'll collaborate closely with our engineering teams to implement innovative solutions and engage with academic and research communities to advance state-of-the-art ML systems. As part of a strategic growth area for AWS, you'll work alongside distinguished engineers and scientists in an exciting and impactful environment. We actively work on these areas: - AI for Systems: Developing and applying ML/RL approaches for kernel/code generation and optimization - Machine Learning Compiler: Creating advanced compiler techniques for ML workloads - System Robustness: Building tools for accuracy and reliability validation - Efficient Kernel Development: Designing high-performance kernels optimized for our ML accelerator architectures A day in the life AWS Utility Computing (UC) provides 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, Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Additionally, this role may involve exposure to and experience with Amazon's growing suite of generative AI services and other cloud computing offerings across the AWS portfolio. About the team AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it’s all being enabled by AWS Neuron. Neuron is a Software that include ML compiler and native integration into popular ML frameworks. Our products are being used at scale with external customers like Anthropic and Databricks as well as internal customers like Alexa, Amazon Bedrocks, Amazon Robotics, Amazon Ads, Amazon Rekognition and many more. About the team 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.

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

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and and complex reasoning; with a focus across text, image, and video modalities. As an Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports

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 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