Careers

The Economic Value & Optimization (EV&O) team builds causal econometric models that quantify the long-term economic value of Amazon's retail selection. Our models inform portfolio-level assortment decisions worth billions in projected OPS impact. We are looking for an Econ intern to work on improving our dynamic causal modeling framework and strengthening the empirical grounding of model outputs through experimental calibration. The intern will work with senior economists and scientists to develop methodological improvements that directly influence how Amazon decides what assortment to carry. Key job responsibilities - Develop and test extensions to our dynamic econometric framework including incorporating Gen AI methodology. - Design and implement models to reconcile counterfactual estimates with experimental treatment effects from selection de-assortment experiments. - Conduct econometric analyses on large-scale customer behavior panel data. - Quantify model performance using validation metrics and identify sources of bias. - Communicate findings to science leadership and business stakeholders through written documents and presentations.

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa 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 deep learning and GenAI 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.

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa 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 deep learning and GenAI 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.

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa 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 deep learning and GenAI 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.

Do you want to work on Reinforcement Learning (RL) post-training of frontier Large Language Models (LLMs) to revolutionize customer service? Come join the world class researchers and academics in the AWS AI endeavor, and develop the science that powers countless new businesses in cloud computing! AWS, the world-leading provider of cloud services. 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 journals. The scientific topics you are going to work on include, but are not limited to: LLM post-training to improve capabilities particularly for instruction following, reasoning over long context, and tool use, etc. About the team 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. 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. Mentorship and 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. Diverse Experiences Amazon 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.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! The Prime Video Ads - Growth, Engagement and monetization (GEM) team is responsible for deciding for every stream, every break, every impression what the right ad experience is for the customer and the right price for the advertiser. We own the centralized decisioning layer, the situation-aware ad load system, the ML prediction platform, the long-term measurement framework, and the experimentation platform that gates every change to production. We are hiring a customer-focused, solutions-oriented Data Scientist to build and guide data-driven frameworks that determine which personalization, yield, and supply innovations are working for customers, advertisers, and the business. You will be embedded on projects that are fast-paced, challenging, and directly influence what hundreds of millions of customers see when they watch Prime Video. Key job responsibilities - Use advanced statistical and machine learning techniques to extract insights from large-scale streaming, ad delivery, and auction data sets. - Design and implement end-to-end data science workflows from data acquisition and cleaning through model development, offline evaluation, A/B testing, and production deployment in partnership with product and engineering teams - Build, validate, and maintain the statistical models that support the roadmap including Supply tier classification and Supply Quality Index, ad tolerance and fatigue scoring, and propensity and disengagement prediction - Partner with product and economist teams to design hold out experiments to measure impact of Ad load on revenue and customer engagement; define north star metrics, power calculations, holdout structures, and promotion gates for every major lever. - Support scalable, self-service analytics by building curated datasets for PVa product, ops, sales, and science covering supply, yield, CX, and advertiser diversification outcomes. - Partner with product stakeholders and science peers to identify strategic, data-driven opportunities to improve the customer experience and advertiser results. - Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders - Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization

We're seeking talented Robotics Software Engineers to expand our software team. This highly technical role involves designing, implementing, and optimizing software solutions across diverse AI robotics hardware that support both autonomous, teleoperation, and ML training/evaluation. You'll work closely and collaboratively with multidisciplinary teams; including software, hardware, research, and operations - to drive advancements in our robotic systems. Key job responsibilities • Work with mechanical, control, EE, and ML engineering teams to bring up and integrate sensors and actuators • Design and build software framework to accelerate development of full robotics applications • Work with AI researchers to build inferencing, training, and evaluation software for robotics controls. • Create testing environment for HW/SW/Policy testing and QA About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Our team focuses on optimizing the house promotional experience within Prime Video for customers and marketing teams to surface personalized recommendations to streamers and optimize the advertising experience. The job will give candidates an opportunity to sit at the forefront of improving the Amazon Prime Video experience for customers and improving the handling of advertising for internal and external marketers within Prime Video. Advertising within Prime Video is at a exciting crossroads to make meaningful impact for customers while driving business innovation. Key job responsibilities Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis.

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa 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.