Careers

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.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Scientist on our team you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in multi-modal AGI models, with a focus on speech generation. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to build Machine Learning models for their application in speech generation. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. We are seeking a talented Applied Scientist to join our advanced robotics team, focusing on developing and applying cutting-edge simulation methodologies for advanced robotics systems. This role centers on research and development of physics-based simulation techniques, sim-to-real transfer methods, and machine learning approaches that enable rapid development, testing, and validation of robotic systems operating in complex, real-world environments. Key job responsibilities - Advance physics-based simulation fidelity for contact-rich manipulation and locomotion - Design and build high-performance simulation tools integrated into a production robotics stack - Translate research ideas into robust, scalable software pipelines - Develop methods to quantify and reduce simulation-to-reality gaps across design, safety, and control - Architect scalable simulation solutions for rigid and deformable body dynamics - Build simulation pipelines optimized for large-scale reinforcement and policy learning - Establish frameworks for continuous simulation improvement using real-world deployment data - Collaborate with engineering, science, and safety teams on simulation requirements and validation About the team Our team is building a comprehensive simulation platform for advanced robotics development, combining locomotion and manipulation capabilities. We operate at the cutting edge of physics simulation, reinforcement learning, and sim-to-real transfer, collaborating with world-class robotics engineers, applied scientists, and mechanical designers in a fast-paced, innovation-driven environment. This role uniquely combines fundamental research with real-world deployment. You will pursue core research questions in physics-based simulation while seeing your work translated into production systems, validated on real hardware, and informed by deployment data. Working alongside Simulation Software Engineers, you will help transform research ideas into scalable, production-grade simulation capabilities that directly impact how robots are designed, trained, and deployed.

Amazon Leo is Amazon’s low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity. 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. This position is part of the Satellite Attitude Determination and Control team. You will design and analyze the control system and algorithms, support development of our flight hardware and software, help integrate the satellite in our labs, participate in flight operations, and see a constellation of satellites flow through the production line into orbit. Key job responsibilities - Design and analyze algorithms for estimation, flight control, and precise pointing using linear methods and simulation. - Develop and apply models and simulations, with various levels of fidelity, of the satellite and our constellation. - Component level environmental testing, functional and performance checkout, subsystem integration, satellite integration, and in space operations. - Manage the spacecraft constellation as it grows and evolves. - Continuously improve our ability to serve customers by maximizing payload operations time. - Develop autonomy for Fault Detection and Isolation on board the spacecraft. A day in the life This is an opportunity to play a significant role in the design of an entirely new satellite system with challenging performance requirements. The large, integrated constellation brings opportunities for advanced capabilities that need investigation and development. The constellation size also puts emphasis on engineering excellence so our tools and methods, from conceptualization through manufacturing and all phases of test, will be state of the art as will the satellite and supporting infrastructure on the ground. You will find that Amazon Leo's mission is compelling, so our program is staffed with some of the top engineers in the industry. Our daily collaboration with other teams on the program brings constant opportunity for discovery, learning, and growth. About the team Our team has lots of experience with various satellite systems and many other flight vehicles. We have bench strength in both our mission and core GNC disciplines. We design, prototype, test, iterate and learn together. Because GNC is central to safe flight, we tend to drive Concepts of Operation and many system level analyses.

Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art recommendation system modeling and GenAI techniques? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science by publishing research! Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization. - Develop and test new signals for improving recommendation models - Use supervised and uplift learning algorithms to improve customer experience - Design A/B tests and conduct statistical analysis on their results - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area - Present and publish science research, contributing to Amazon's science community - Mentor junior engineers and scientists. About the team Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.

Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art recommendation system modeling and GenAI techniques? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science by publishing research! Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization. - Develop and test new signals for improving recommendation models - Use supervised and uplift learning algorithms to improve customer experience - Contribute to production code and science tooling - Design A/B tests and conduct statistical analysis on their results - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area - Present and publish science research internally and externally, contributing to Amazon's science community - Mentor junior engineers and scientists. About the team Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.

Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art recommendation system modeling and GenAI techniques? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science by publishing research! Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization. - Develop and test new signals for improving recommendation models - Use supervised and uplift learning algorithms to improve customer experience - Design A/B tests and conduct statistical analysis on their results - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area - Present and publish science research, contributing to Amazon's science community - Mentor junior engineers and scientists. About the team Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.

Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art recommendation system modeling and GenAI techniques? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science by publishing research! Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization. - Develop and test new signals for improving recommendation models - Integrate GenAI into Amazon customer shopping experience - Design A/B tests and conduct statistical analysis on their results - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area - Present and publish science research, contributing to Amazon's science community - Mentor junior engineers and scientists. About the team Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.

Alexa AI is looking for a Principal Applied Scientist to lead the science behind Alexa+, Amazon's LLM-powered conversational assistant. You will own the technical direction for key initiatives spanning large language model fine-tuning, alignment, agentic reasoning, and evaluation — directly shaping the experience for hundreds of millions of customers worldwide. As a Principal Scientist, you are a hands-on technical leader. You define research directions, design and run rigorous experiments, and ensure that research translates into production systems at scale. You decompose ambiguous, hard problems into clear solutions. Your code, models, and documents are exemplary and frequently referenced across the organization. You amplify your impact beyond your own work. You lead scientific reviews, scrutinize experimental design and modeling assumptions, and align teams toward coherent strategies. You mentor senior scientists, contribute significantly to hiring, and keep the broader scientific community current on state-of-the-art techniques. You bring business and industry context to technical decisions and can credibly present to executive leadership. Key job responsibilities Define and drive the science roadmap for conversational AI capabilities powered by large language models Design, implement, and evaluate novel approaches to LLM fine-tuning, alignment (RLHF, DPO), and distillation for production deployment Architect agentic systems — multi-step reasoning, tool use, planning, and orchestration — that work reliably at scale Develop evaluation frameworks and methodologies that go beyond standard benchmarks to capture real-world conversational quality Translate research advances into customer-facing products, working closely with engineering, product, and cross-functional science teams Publish results at top-tier venues and represent Amazon in the broader research community Mentor scientists at all levels and contribute to organizational planning, hiring, and technical culture About the team Alexa AI is building the science and technology behind Alexa+, Amazon's next-generation conversational assistant. Our team works at the intersection of large language models, reinforcement learning from human feedback and verifiable rewards, agentic architectures, and multilingual/multimodal understanding. We operate at massive scale — our models serve customers across dozens of languages and device types. If you want to push the frontier of conversational AI and see your work used by people every day, come join us.

The Amazon Alexa AI team in India is seeking a talented, self-driven Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms within the realm of Generative AI. Key responsibilities include: - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues