Careers

Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and ASR, TTS, & Speech to Speech models, requiring foundational deep learning and generative models knowledge. Applied scientists will contribute to cross-team scientific efforts, collaborate with partner teams, and deliver solutions that impact Alexa's international products and services. Key job responsibilities As an Applied Scientist with the Alexa International team, you will work with talented peers to develop and implement algorithms and modeling techniques to advance the state of the art with LLMs, particularly contributing to scientific research and applied AI for multi-lingual applications — a challenging area for the industry globally. Your work will directly impact our global customers in the form of products and services that support Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in text, speech, and vision domains. The ideal candidate possesses a foundational understanding of machine learning, speech and/or natural language processing, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in a fast-paced environment, like to tackle complex challenges, and are eager to deliver impactful solutions while iterating based on user feedback. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build and support online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Work on ASR, TTS, and Speech-to-Speech (S2S) model training and fine-tuning * Fine-tune/post-train LLMs using techniques like SFT, DPO, Reinforcement Learning (RLHF and RLAIF) for supporting model performance specific to a customer's location and language. * Experiment and help set up experimentation frameworks for agile model and data analysis or A/B testing. * Contribute to research efforts that drive innovation forward. * Collaborate with cross-team scientists and engineers on LLM evaluation frameworks, post-training methodologies, and best practices for international speech and language systems. * Contribute to end-to-end delivery of scientific solutions from research to production, including reusable science components and services. * Communicate solutions clearly to peers, partners, and stakeholders. * Actively participate in the broader internal and external scientific community through publications and community engagement.

We are seeking a Sr. Applied Scientist to focus on Robot Navigation. In this role, you'll research and develop advanced navigation systems that enable robots to move reliably and safely through complex, dynamic environments. You'll work across a broad spectrum of navigation approaches—from classical methods to learning-based techniques and foundation models—to build robust solutions for autonomous robot navigation. Key job responsibilities - Develop and implement robust navigation systems that enable reliable autonomous operation in complex, dynamic indoor environments with static and dynamic obstacles - Build simulation-based and on-device evaluation frameworks with comprehensive benchmarks and metrics for systematic comparison of navigation methods - Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world navigation performance - Collaborate with world model, manipulation, and other teams to ensure seamless integration of navigation capabilities into the full robot system - Stay current with the latest advances in robot navigation, spatial reasoning, and related fields, and apply relevant findings to improve system performance - Mentor fellow scientists and engineers while maintaining strong individual technical contributions 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.

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. We are seeking a highly skilled and analytical Data Scientist. You will play an integral part in the measurement and optimization of Amazon Music marketing activities. You will have the opportunity to work with a rich marketing dataset together with the marketing managers. This role will focus on developing and implementing models that aids in audience segmentation, AI-enablement in data/reporting, and assessing randomized controlled trials to rate marketing effectiveness. This role is suitable for candidates with strong background in cohort analysis, causal inference, statistical analysis, and data-driven problem-solving, with the ability to translate complex data into actionable insights. As a key member of our team, you will work closely with cross-functional partners to optimize marketing strategies and drive business growth. Key job responsibilities Develop Causal & Predictive Models Build and validate causal and predictive models that quantify how marketing and lifecycle programs affect customer retention, engagement, and subscriber growth for Amazon Music. Own the team's models end to end. Statistical Analysis at Scale Analyze large customer datasets using SQL and Python or R to interpret results and uncover meaningful patterns, grounding your work in trusted, well-governed data. Enable Data-Driven Decisions Partner with marketing and finance stakeholders to deliver recommendations that improve retention and return on investment. Prioritize the work with the greatest impact on customer growth, and present findings clearly to both technical and executive audiences. Bring AI into Self-Service Tools Partner with product managers and engineers to incorporate AI and machine learning into the team's self-service analytics tools, so stakeholders can answer their own questions faster and at greater scale. Cross-Functional Problem Solving Work across marketing, product, and engineering teams to frame key business questions and build credible analytical solutions. Innovate & Document Track emerging methods and apply them to improve measurement; maintain reproducible documentation and clear reporting for non-technical audiences.

We are seeking a Member of Technical Staff - Mechanical Engineer to design and develop robotic manipulation hardware within a frontier AI and robotics research lab. You will own the mechanical design of manipulation-focused hardware end-to-end: grippers, end-of-arm tooling (EOAT), multi-finger hands, UMI-style grippers, and data collection fixtures - all built to enable AI researchers to collect high-quality demonstration data and validate learned manipulation policies. This role sits at the intersection of mechanical design and AI research. You will be the person who builds the physical tools that make robot learning possible, rapidly prototyping and iterating on end-effectors and data collection hardware, working hand-in-hand with AI/ML researchers to understand what mechanical properties (compliance, sensing, geometry) actually matter for learned manipulation policies. The ideal candidate is hands-on, moves quickly, is motivated by learning across domains, and is as comfortable sketching a new gripper concept as they are debugging a real-world manipulation experiment. You thrive in fast-paced R&D environments where requirements evolve quickly, and you are genuinely curious about how your design decisions influence data quality and policy performance. If you want to directly shape the hardware that enables the next generation of robot learning, this role is for you. What You Bring: - A hands-on, build-first mindset: comfortable prototyping, testing, and iterating rapidly in a research environment. - Comfort designing in environments where requirements evolve quickly and hardware needs to be rethought from week to week - Genuine interest in how mechanical design choices such as compliance, geometry, sensing integration, etc. impact data quality for robot learning - Familiarity or curiosity about imitation learning, teleoperation, or data collection for manipulation - A collaborative and communicative working style, especially in multi-disciplinary research environments spanning AI, controls, and perception - A passion for robotics and advancing the state of the art in dexterous, capable manipulation systems Key job responsibilities - Design grippers, end-of-arm tools, and low DoF multi-finger hands for robotic manipulation research and data collection. - Develop UMI-style grippers and teleoperation hardware for collecting manipulation demonstration data. - Design fixtures, jigs, and mounting systems for cameras, sensors, and manipulation test setups. - Integrate tactile sensors, force/torque sensors, and cameras into compact gripper assemblies. - Rapidly prototype and iterate on manipulation hardware — from concept sketches to functional grippers in days/weeks. - Partner with AI researchers to understand what mechanical properties (compliance, sensing, geometry) matter for learned manipulation policies. - Design data collection devices, such as UMI grippers, that enable repeatable, high-quality demonstration capture. - Conduct mechanical testing of gripper performance (grasp force, compliance, durability, repeatability). - Apply DFM/DFA to scale successful gripper designs from one-offs to small batches (10s–100s of units). - Own cable routing, actuation, and sensing integration for compact end-effector designs. - Support hands-on builds, debug sessions, and real-world manipulation experiments. - Collaborate with controls, perception, and AI teams to ensure hardware meets research needs. About the team Frontier AI & Robotics (FAR) is the team at Amazon building the next generation of embodied intelligence. FAR drives the development and implementation of advanced AI models within Amazon’s operations that enable robots to see, reason, and act on the world around them, supporting a number of different warehouse automation tasks.

Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs), ASR, TTS, and Speech to Speech models, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Alexa's international products and services. Key job responsibilities As an Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with Large Language Models (LLMs), ASR, TTS, and Speech to Speech model. Your work will directly impact our international customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Drive research in ASR, TTS, and Speech-to-Speech (S2S) model training and fine-tuning * Advance multilingual speech recognition and synthesis using LLM-based architectures * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Collaborate with partner teams on evaluation frameworks and post-training methodologies. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.

Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs), ASR, TTS, and Speech to Speech models, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Alexa's international products and services. Key job responsibilities As an Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with Large Language Models (LLMs), ASR, TTS, and Speech to Speech model. Your work will directly impact our international customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Drive research in ASR, TTS, and Speech-to-Speech (S2S) model training and fine-tuning * Advance multilingual speech recognition and synthesis using LLM-based architectures * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Collaborate with partner teams on evaluation frameworks and post-training methodologies. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.

Are you interested in big data, Machine Learning, and building recommendation services using Generative AI? If so, Amazon's Personalization team might be the right place for you. Key job responsibilities - Use AI and machine learning to create scalable solutions for business problems. - Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes. - Design, develop and evaluate highly scalable models for predictive learning. - Work closely with software engineering teams to drive model implementations and new feature creations. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Research and implement novel machine learning and statistical approaches - Review peer work and provide feedback A day in the life You are an Applied Scientist who loves big data and passionate about improving customer shopping experience by inventing and applying state-of-art technologies (e.g., LLMs/SLMs, Machine Learning, Natural Language Processing, and Computer Vision) to build the next-generation product recommendation engine for Amazon. You have an entrepreneurial spirit, know how to deliver, are deeply technical and highly innovative. You work closely with software engineers to put algorithms into production. You also work in partnership with teams across Amazon to create enormous benefits for our customers. About the team We are part of Amazon’s Personalization organization, a high-performing group with a huge impact on hundreds of millions of customers, innovating at the intersection of customer experience, machine learning, and large-scale distributed systems. We run global experiments and our work has revolutionized e-commerce with features such as "Compare with similar items", "Keep Shopping For", “Customers who bought this item also bought”, and, “Frequently bought together” among others.

Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match! Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience. The NAS Shop and Keep (SHAKE) organization empowers customers to make confident, lasting purchase decisions by minimizing purchase anxiety and reducing returns. The NAS SHAKE science team advances this mission by innovating and developing scalable ML solutions tailored to these unique challenges. The team is hiring a Data Scientist who has a solid background in Statistical Analysis, Machine Learning, LLM, GenAI applications and Data Mining and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist. Key job responsibilities - You will work on our Science team and partner closely with applied scientists, data engineers as well as product managers, UX designers, and business partners to answer complex problems via data analysis. Outputs from your analysis will directly help improve the performance of the ML based recommendation systems thereby enhancing the customer experience as well as inform the roadmap for science and the product. - You can effectively analyze complex and disparate datasets collected from diverse sources to derive key insights, build segmentation models and improve customer experience by reducing retail returns. - You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders. - You are able to multi-task between different tasks such as gap analysis of algorithm results, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics or presenting to stakeholders. - You thrive in an agile and fast-paced environment on highly visible projects and initiatives.

Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match! Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience. The NAS Shop and Keep (SHAKE) organization empowers customers to make confident, lasting purchase decisions by minimizing purchase anxiety and reducing returns. The NAS SHAKE science team advances this mission by innovating and developing scalable ML solutions tailored to these unique challenges. The team is hiring a Data Scientist who has a solid background in Statistical Analysis, Machine Learning, LLM, GenAI applications and Data Mining and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist. Key job responsibilities - You will work on our Science team and partner closely with applied scientists, data engineers as well as product managers, UX designers, and business partners to answer complex problems via data analysis. Outputs from your analysis will directly help improve the performance of the ML based recommendation systems thereby enhancing the customer experience as well as inform the roadmap for science and the product. - You can effectively analyze complex and disparate datasets collected from diverse sources to derive key insights, build segmentation models and improve customer experience by reducing retail returns. - You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders. - You are able to multi-task between different tasks such as gap analysis of algorithm results, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics or presenting to stakeholders. - You thrive in an agile and fast-paced environment on highly visible projects and initiatives.

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. Key job responsibilities * Define and implement new automated reasoning features that employ scalable and efficient approaches to solve complex problems using neural learning and symbolic/formal reasoning * Apply software engineering best practices to ensure a high standard of quality for all team deliverables * Work in an agile, startup-like development environment * Deliver high-quality scientific artifacts * Work with the team to help drive business decisions About the team About the team Why AWS? 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.