Careers

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.

This role will develop Economic and Econometric models and thought leadership on projects that span our business, with a particular focus on supply chain and inventory selection. Through the lens of economics, you will develop a deeper understanding of how customers value our selection and interact with Amazon's store to make shopping easier. You will be a key scientist, advising Amazon leaders how to evaluate selection and understand customers. You will work on developing frameworks and scaleable, repeatable models supporting optimal pricing and policies for Amazon's business. You will partner with science and technology teams across Amazon including Supply Chain, Operations, Retail, FBA, Consumer Pricing, and Finance. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. Ability to incorporate AI tools and methods into your work is highly valued. They will work closely with Economists, Data/Applied Scientists, Software Engineers and Product Managers to integrate economic insights into policy and systems production. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.

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.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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 Amazon Sponsored Products and Brands is looking for a talented Sr. Applied Scientist to join the Global Optimization science team at the forefront of advertising technology innovation. We are working backwards from emerging markets to reimagine Amazon's advertising stack from the ground up, leveraging multilingual and multi-modal GenAI technologies — including semantic hash designs, LLMs, and more — to deliver solutions that scale to non-US marketplaces from day one. This is your opportunity to be part of a small, high-impact team that prototypes, invents, and ships state-of-the-art solutions that will define the future of digital advertising. The ideal candidate combines entrepreneurial drive with deep technical expertise, thriving in ambiguous, fast-moving environments where you define the path forward with minimal structure. Our team regularly goes from ideas on the whiteboard to production-grade experiments. Your Customer Obsession fuels your passion for translating science into real-world value for millions of advertisers and customers worldwide. You are consistently Right, A Lot when navigating complex technical decisions, demonstrating the rare ability to identify solutions that drive maximum impact with minimal resources. Whether you're architecting scalable GenAI systems or optimizing multi-task recommendation engines, you cut through complexity to find the solutions that deliver the most results. Your GenAI experience goes beyond theoretical knowledge—you have successfully delivered value with state-of-the-art technologies at Amazon scale, understanding both the promise and practical challenges of deploying machine learning in production environments (evaluations, etc.). You're not just a scientist or just an engineer—you're a builder who sees the bigger picture and knows how to make it reality. Key job responsibilities * Architect next-generation systems that replace legacy monolithic infrastructure with scalable, intelligent solutions that scale worldwide on day one. * Pioneer breakthrough applied science in multi-modal GenAI applications for advertising, combining text, image, and multi-lingual support. * Drive end-to-end innovation from research ideation through production deployment at Amazon scale. * Lead cross-functional collaboration with product, engineering, and business teams to translate science into customer impact. About the team You will join a newly-founded team with a broad mandate to experiment and innovate, with a focus on driving growth of sponsored products ad experiences across non-US marketplaces. This broad charter gives us the flexibility to explore and apply scientific techniques to novel product problems. You will have the satisfaction of seeing your work improve the experience of millions of Amazon shoppers worldwide while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills, and be a science leader in an environment that thrives on creativity, experimentation, and product innovation.

The R2L team is responsible for building the next generation supply chain for Amazon's world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes! The R2L Science & AI team is the centralized data science and AI function serving all R2L business verticals. We drive data informed decision making and build AI-powered products that optimize every stage of R2L's operational pipeline from supply chain planning through last-mile delivery. We are looking for a customer-focused, solutions-oriented Senior Manager, Data Science to lead and scale the data science function within the R2L organization. In this role, you will build and manage a high-performing team of Data Scientists and BI Engineers while owning the AI technical roadmap for R2L. You will be responsible for delivering data science and AI solutions that drive measurable operational improvements across R2L's end-to-end network including Supply Chain, Operations, Delivery, Operational Excellence, and Finance. This is a people leadership role with deep technical expectations. You will set the technical vision, hire and develop talent, and partner with senior leaders across R2L and external stakeholders to ensure data science and AI investments are aligned with business priorities and deliver outsized impact. Key job responsibilities - Build and manage a team of Data Scientists and BI Engineers - Define and drive the multi-year vision for Science and AI roadmap for R2L, aligning investments with business priorities to deliver measurable efficiency and customer experience improvements - Define and execute the Gen AI strategy for R2L, identifying high-impact use cases for LLMs, agentic AI, and automation across operational workflows - Influence VP and Director-level leaders through data-driven narratives, technical deep dives, and business impact framing - Educate senior leaders about and advocate for high-quality measurement as an input to data-driven decisions - Raise the technical bar across the organization through mentorship, artifact reviews, and establishing best practices for experimentation, model development, and deployment - Stay up-to-date on the latest data science, measurability, AI tools, techniques, and best practices and help evangelize them across the organization 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: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 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!

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.