Careers

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Within Sponsored Products, the Bidding team is responsible for defining and delivering a collection of advertising products around bid controls (dynamic bidding, bid recommendations, etc.) that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Key job responsibilities As a Senior Applied Scientist on this team, you will: • Lead a new initiative across Sponsored Products Bidding focused on AI/ML based features. • Be the technical leader in AI, Machine Learning; lead efforts within this team and across other teams. • Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. • Drive end-to-end AI/Machine Learning projects that have a high degree of ambiguity, scale, complexity. • Build models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your AI/ML models. • Run A/B experiments, gather data, and perform statistical analysis. • Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. • Research new and innovative AI/ machine learning approaches. • Recruit Applied Scientists to the team and provide mentorship. A day in the life Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon's Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. 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. The SPB Bidding team within Sponsored Products and Brands is focused on guiding and supporting Millions of advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in bidding systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our vision is to build a highly personalized, context-aware bidding system that leverages auction simulations, ML models, and optimization algorithms. This framework, will operate across SPB bidding system and proactively delivering value based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities—from high-level product guidance down to granular recommendations—and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art bidding agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning and preference optimization), ensuring our systems are both scalable and adaptive.

We are looking for an AI/ML Engineer to build efficient, stable foundation models for long-horizon agentic workloads. The role combines model development with systems and hardware optimization. Qualifications Strong background in machine learning, deep learning, transformers, and foundation models. Experience with PyTorch, JAX, or similar frameworks. Experience training, fine-tuning, or serving large-scale models. Knowledge of GPU architecture, CUDA, Triton, custom kernels, or hardware-aware optimization. Familiarity with distributed training and model parallelism. Experience with AWS Trainium, Inferentia, Neuron SDK, TPUs, or other custom accelerators is preferred. PhD in machine learning, computer science, electrical engineering, or a related field is preferred. Key job responsibilities Responsibilities Design, train, fine-tune, and evaluate custom foundation models. Improve model efficiency, stability, latency, throughput, and memory usage. Build models that support planning, tool use, memory, self-correction, and multi-step task execution. Optimize training and inference using CUDA, Triton, custom GPU kernels, and tensor operations. Profile and resolve compute, memory, communication, and distributed-training bottlenecks. Work with GPUs and specialized AI accelerators, including AWS Trainium and other custom tensor hardware. Develop evaluations for model reliability and long-horizon agent performance. 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) 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.

Your Next Big Challenge Starts Here You've spent years mastering machine learning. Now imagine applying that expertise where it actually reaches billions of people — every single day. At Amazon Ads, we're not just running ads. We're re-inventing the entire advertising experience using generative AI, large language models, and next-generation ML. From the moment a brand crafts a campaign to the instant a customer discovers something they love — your science powers it all. Billions of impressions. Millions of clicks. Petabytes of data. And you — at the center of it. Why This Role Will Excite You Unmatched scale and resources. You'll have access to computational power and datasets most scientists only dream about. Build solutions that don't just work in a notebook — they work at planet scale. Breadth that keeps you sharp. One quarter you might be optimizing real-time bidding systems. The next, you're building creative AI that generates ad content. Ranking, personalization, NLP, computer vision, LLMs — it's all on the table. Your ideas ship. This isn't a research lab where papers collect dust. You'll take models from concept to production, run A/B experiments, and see your work move metrics that matter — for advertisers, customers, and the business. People who push you forward. You'll collaborate with world-class engineers, scientists, and product leaders who are just as passionate about solving hard problems as you are. What You'll Actually Do Research and build next-generation ML solutions — including generative AI and LLM applications — that transform how advertising works Own end-to-end projects: from messy, ambiguous problems to deployed, production-grade models Design experiments that validate your hypotheses and measure real business impact Build models that balance what's best for customers and advertisers — because great advertising should feel helpful, not intrusive Work cross-functionally with engineers, PMs, and fellow scientists to ship fast and iterate faster Develop scalable ML pipelines that optimize monetization without sacrificing customer experience Where This Takes Your Career Whether you want to go deep as a technical IC or grow into people leadership — both paths are real here. You'll have opportunities to: Lead high-visibility technical initiatives Mentor and grow other scientists Shape strategy alongside senior leadership Build a reputation in a community that genuinely values scientific excellence Your work won't just be seen internally — it'll impact millions of customers and advertisers worldwide. Watch Scientists at Amazon Ads Talk About Their Work https://www.youtube.com/watch?v=vvHsURsIPEA Learn More About Amazon Ads https://advertising.amazon.com/ Basic Qualifications 5+ years building ML models for real business applications PhD, or Master's degree + 6 years of applied research experience Strong programming skills in Python, Java, C++, or similar Hands-on experience with deep learning and neural network methods Preferred Qualifications Experience with tools like scikit-learn, TensorFlow, PyTorch, Spark MLLib, MxNet, numpy, scipy Experience with large-scale distributed systems (Hadoop, Spark, etc.)

We are seeking a talented and motivated Data Scientist to join our 1P Lending team. In this role, you will design, build, and deploy machine learning models and analytical frameworks that drive credit risk assessment, income estimation, fraud detection, and portfolio optimization. You will work with credit bureau data, transactional data, and alternative behavioral signals to create models that directly impact lending decisions and customer outcomes. Key job responsibilities • Understand lending business, products, data consumed to make decisions, regulatory context, and practice of Data Science related to this field. • Closely Interact with risk, product and collection team to understand the business challenges. • Define, Design and Implement complex ML solutions for various credit lifecycle stages like credit risk scoring, income prediction, collection optimisation, sales optimisation, fraud detection etc. • Create robust model validation, monitoring, and governance solutions in compliance with regulatory requirements. • Help the Decision-Engine team to deploy the ML solutions in production with sub-second latency. • Develop new modeling techniques and analytical frameworks for innovative lending products within the regulatory landscape. • Drive end-to-end delivery of scalable data pipelines from ideation to production deployment. • Optimize performance and accuracy of existing ML solutions. • Derive actionable insights from massive and diverse datasets. • Lead analytical design and implementation for new global market geographies. • Mentor junior team members in data science best practices. • Present findings and recommendations to senior leadership with clear, data-backed conclusions. About the team As Decision Sciences team supporting 1p lending, we use Data Science, Machine Learning, and advanced analytics on massive datasets to power credit decisioning, risk management, and customer experience optimization. We operate at the intersection of ML, Fintech and E-commerce, working on cloud scale ML infrastructure. If explainable GenAI, Probabilistic Graph Models, DNNs and Monte Carlo Simulations excite you, then we are the right team for you.

The Amazon Search team creates customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide. Amazon has grown rapidly and will continue to do so in foreseeable future. Providing a high quality search experience is a unique challenge as Amazon expands to new customers, countries, categories, and product lines. We are seeking a strong applied scientists to join the newly formed Relevance India team. This team’s charter is to increase the pace at which Amazon expands and improve the search experience at launch. In practice, we aim to invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models. Key job responsibilities Build machine learning models for Product Search. Develop new ranking features and techniques building upon the latest results from the academic research community. Propose and validate hypothesis to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system. Focus on identifying and solving customer problems with simple and elegant solutions. Design, develop, and implement production level code that serves billions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment. Collaborate with other engineers and related teams within A9.com and Amazon.com to find technical solutions to complex design problems. Take ownership. Understand the needs of various search teams, distil those into coherent projects, and implement them with an eye on long-term impact. Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects. Be ambitious. Find and eagerly tackle hard problems. Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to the technologies and vast technical tools and resources of Amazon and will need to learn how to use them effectively. Be customer focused. Work backwards from customer problems, figure out elegant solutions, and implement them for speed and scalability.

We are seeking an Applied Scientist to focus on Robotics Spatial Intelligence and Semantic Understanding. In this role, you'll research and build advanced semantic and world understanding algorithms that enable robots to observe, understand, and reason about complex and dynamic home environments. You'll work across a broad spectrum of 3D perception, contextual understanding, and world modeling approaches to build robust solutions that support autonomous decision making, task planning, navigation, and manipulation. Key job responsibilities - Develop and implement robust World Understanding and Modeling algorithms for a domestic robot. - Build simulation-based and on-robot evaluation frameworks with comprehensive benchmarks and metrics for systematic evaluation of Our Spatial Intelligence stack. - Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world performance. - Collaborate with navigation, manipulation, and other teams to ensure seamless integration of World Understanding capabilities. - Stay current with the latest advances in World Modeling, Spatial Reasoning, and related fields and apply relevant findings to improve system performance About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers, and is becoming the conversational AI interface for Amazon services with the launch of Alexa for Shopping on Amazon.com and Amazon mobile app. At Alexa Ads, we are creating industry's first and most advanced Agentic Advertising products to drive Agentic Commerce. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa Agentic/Conversational Ads and Personalization. In this role, you will build machine learning models that seamlessly and naturally integrate relevant advertising into the Alexa experience while deeply personalizing user interactions. You will work closely with other scientists, engineers, and product managers to take models from conception to production. Key job responsibilities - Design, develop, and evaluate innovative machine learning and deep learning models for natural language processing (NLP), recommendation systems, and personalization. - Conduct hands-on data analysis and build scalable ML pipelines. - Design and run A/B experiments to measure the impact of new models on customer experience and ad performance. - Collaborate with software development engineers to deploy models into high-scale, real-time production environments. About the team We are building a new science team in Bangalore to solve some of the most impactful problems in computational advertising. This isn't about tweaking existing models as we are rethinking how ads are ranked, priced, and personalized across voice-first and screen-first surfaces. These are problems that don't have textbook solutions. Key points to note about the team: 🧪 Greenfield team - you are not joining a mature org with rigid processes. You will shape the science roadmap, pick the problems, and define the culture from day one. 📈 Direct business impact — your models directly drive revenue. No yearly cycles to see if your work matters. 🌏 Global scope, local autonomy — collaborate with scientists and engineers across Seattle, Sunnyvale, and Bangalore, but own your problem space end-to-end. 🎓 Ship AND Publish: We encourage top-tier publications (NeurIPS, ACL, EMNLP, KDD, ICML, WWW) while ensuring your research hits production.

Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.

Come join the Device connectivity team in building the next generation of innovative wireless solution that create a magical experience on our products and services. We actively engage in strategic initiatives, foster partnerships with industry and academia, leverage foundational artificial intelligence and large language models to stay at the forefront of the technological advancements. We are seeking an experienced Applied Science Manager to lead and grow a team of applied scientists who are pushing the boundaries of AI/ML in wireless connectivity and sensing. In this role, you will combine deep technical expertise with strong people leadership to drive scientific innovation that directly impacts millions of customers worldwide. Key job responsibilities As a Applied Science Manager in the team, you will: Build, mentor, and develop a high-performing team of applied scientists, setting the technical bar through code reviews, design reviews, and hands-on contributions while fostering a culture of scientific excellence, innovation, and operational rigor. Define and drive the AI/ML science roadmap for wireless solutions by developing a deep understanding of Amazon's Devices and Services offerings, translating complex business problems into well-defined scientific challenges, identifying high-risk and high-impact technical directions, and guiding your team to deliver them from conception through production. Collaborate cross-functionally with engineering, product, and business partners to drive ML development from research through optimization and onto production devices, aligning science investments with product goals while meeting on-device performance, latency, and resource constraints. Balance exploratory research with production delivery timelines, ensuring the team maintains scientific rigor while meeting business commitments. Represent the team's AI innovations to both internal leadership and the external scientific community through leadership reviews, publications, patents, and conference presentations, providing clear articulation of science strategy, progress, and impact. About the team About the team Device Connectivity team is empowering possibilities through wireless innovation on our devices and through services, our vision is to design and develop transformative products and services that consistently exceed our customers' expectations.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.