Careers

We are seeking an Applied Scientist to lead the development of evaluation frameworks and data collection protocols for robotic capabilities. In this role, you will focus on designing how we measure, stress-test, and improve robot behavior across a wide range of real-world tasks. Your work will play a critical role in shaping how policies are validated and how high-quality datasets are generated to accelerate system performance. You will operate at the intersection of robotics, machine learning, and human-in-the-loop systems, building the infrastructure and methodologies that connect teleoperation, evaluation, and learning. This includes developing evaluation policies, defining task structures, and contributing to operator-facing interfaces that enable scalable and reliable data collection. The ideal candidate is highly experimental, systems-oriented, and comfortable working across software, robotics, and data pipelines, with a strong focus on turning ambiguous capability goals into measurable and actionable evaluation systems. Key job responsibilities - Design and implement evaluation frameworks to measure robot capabilities across structured tasks, edge cases, and real-world scenarios - Develop task definitions, success criteria, and benchmarking methodologies that enable consistent and reproducible evaluation of policies - Create and refine data collection protocols that generate high-quality, task-relevant datasets aligned with model development needs - Build and iterate on teleoperation workflows and operator interfaces to support efficient, reliable, and scalable data collection - Analyze evaluation results and collected data to identify performance gaps, failure modes, and opportunities for targeted data collection - Collaborate with engineering teams to integrate evaluation tooling, logging systems, and data pipelines into the broader robotics stack - Stay current with advances in robotics, evaluation methodologies, and human-in-the-loop learning to continuously improve internal approaches - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers

Are you passionate about using data science to transform how businesses understand and optimize customer interactions at scale? Do you want to build the models and analytics that power the next generation of AI-driven customer experiences while working directly with customers to accelerate production deployments? As a Senior Applied Scientist within the Applied AI Solutions team, you will collaborate across AI Velocity Teams (AIVT), enabling multiple customer engagements simultaneously. You will lead data science initiatives that span the full lifecycle — from identifying high-value business problems and formulating hypotheses, through rigorous experimentation and modeling, to deploying production-grade solutions that serve thousands of customers. You will bring deep expertise in statistical inference, machine learning, and experimental design to drive measurable impact across Amazon Connect's analytics products and broader Connect AI initiatives. A critical dimension of this role is working directly with customers during production pilots to accelerate time-to-value. You will partner with Applied AI Solutions Architects and Customer Success Specialists to design, build, and deploy AI solutions in customer environments during fixed deployment cycles. You will enable field teams with data-driven insights, reusable analytical assets, ROI tools, and scalable tooling that accelerate customer engagements and solution delivery. Your work will directly influence customer decisions to adopt Connect Customer AI by quantifying business outcomes and demonstrating measurable value. You will operate with significant autonomy, owning the scientific direction of your projects while collaborating with applied scientists, software engineers, product managers, technical, and business stakeholders. You will be expected to identify the right methodology for each problem — whether that's a classical statistical approach, a modern deep learning technique, or a novel combination — and communicate your findings clearly to both technical and non-technical audiences. This role spans Connect AI initiatives including conversational analytics and agentic AI capabilities, offering the opportunity to pioneer data science approaches that scale intelligent analytics worldwide. Key job responsibilities - Design, develop, and deploy statistical models and machine learning pipelines to drive product improvements and business decisions - Work directly with customers during production pilots to design, build, and deploy AI solutions that demonstrate measurable business value - Design and execute A/B experiments and causal inference analyses to measure the impact of new features and model changes on customer outcomes - Build ROI models and business case tools that quantify the value of Connect Customer AI for existing customers transitioning from Connect Customer Basic - Develop and maintain forecasting systems for demand prediction, capacity planning, and workforce optimization - Develop and apply NLP and generative AI techniques to extract insights from structured and unstructured data at scale - Partner with applied scientists and software engineers to productionize models, ensuring reliability, monitoring, and operational excellence - Enable AI Velocity teams with reusable analytical assets, diagnostic notebooks, and scalable tooling that accelerate customer engagements - Build benchmarking studies and optimization frameworks that demonstrate value across customer cohorts - Own success metrics and create mechanisms to measure model performance, adoption, and business impact - Communicate findings and technical trade-offs to senior leadership and customer executives through written documents (6-pagers, science reviews) and presentations - Operate as a shared resource across 2-3 AIVT teams simultaneously, providing data science expertise across multiple customer engagements A day in the life - Start the morning on a call with the AI Velocity Teams preparing for a strategic customer engagement — reviewing the analytical assets and dashboards you've built, walking through how to interpret model outputs, and tailoring recommendations to the customer's contact center environment - Join a customer working session where you're deploying a production pilot — analyzing their historical contact data, building demand forecasting models, and demonstrating how AI optimizations will reduce their cost per serviced contact while improving customer experience metrics - Dive into a deep analysis triggered by AIVT field feedback — a large enterprise customer is seeing unexpected patterns in their contact data, and you're pulling together multi-source data to isolate root cause and build a reusable diagnostic notebook the AIVT team can leverage for similar cases - Participate in a Conversational Analtyics science review, presenting your A/B test results on a new sentiment classification approach and discussing trade-offs between model accuracy and inference latency with the engineering team - Spend the afternoon building a reusable ROI calculator that field teams can use across customer engagements — packaging your economic models with configurable parameters so teams can quickly quantify the value of Connect Customer AI for different customer profiles and usage patterns - Collaborate with AI Architects and Customer Success Specialists across your three active AIVT engagements, providing data science guidance on model selection, evaluation frameworks, and success metrics for each customer's unique use cases - Wrap up by reviewing a design document for an agentic AI feature that will use conversation analytics to automatically surface coaching recommendations for contact center supervisors, providing feedback on the evaluation methodology and success metrics 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.

The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.

Are you interested in shaping the future of entertainment through cutting-edge AI? Prime Video’s technology teams are redefining the digital video experience at scale. As a Principal Applied Scientist at Prime Video, you will be a technical and strategic leader responsible for inventing, developing, and deploying groundbreaking AI solutions that power personalized, relevant, and delightful experiences for millions of global customers. You will help shape the vision and direction of key ML systems that support Prime Video’s mission to deliver AI-powered customer experiences. This role demands a unique blend of deep technical expertise in machine learning and recommendation systems, industry leadership, and strong collaboration skills. You will guide the development of high-impact systems end-to-end - leading innovation from foundational research through production deployment - while mentoring scientists and influencing product and engineering roadmaps. We are looking for a thought leader who brings a strong track record of delivering ML innovations at scale, along with the curiosity and drive to push boundaries. This is a rare opportunity to drive meaningful impact at one of the largest streaming services in the world. Key job responsibilities - Invent, prototype, and productionize large-scale AI solutions across Prime Video’s personalization and discovery ecosystem using deep learning, generative AI, reinforcement learning, and optimization techniques; - Provide technical leadership and influence product vision by collaborating closely with engineers, product managers, and senior stakeholders; - Design and lead high-impact A/B tests and data analyses to validate hypotheses and guide product direction; - Drive technical bar-raising across science and engineering teams through mentorship, design reviews, and collaboration; - Stay ahead of industry trends and emerging research; leverage them to evolve long-term strategy and architecture; - Publish impactful research internally and externally (e.g. top-tier conferences and journals). About the team Prime Video Personalization and Discovery (PVPD) is dedicated to creating a highly personalized content discovery experience that not only delights our customers but also drives both short-and long-term business goals. Our scope includes personalized recommendations, search, marketing, and the advanced machine learning technology and infrastructure that underpins these experiences. Our mission is to automate and enhance customer engagement through personalization, using ML and Generative AI.

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI), Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems. You will be at the forefront of transforming how Audible harnesses the power of AI to enhance productivity, unlock new value, and reimagine how we work. In this unique role, you'll apply ML/AI approaches to solve complex real-world problems while helping build the blueprint for how Audible works with AI. ABOUT YOU You are passionate about applying scientific approaches to real business challenges, with deep expertise in Machine Learning, Natural Language Processing, GenAI, and large language models. You thrive in collaborative environments where you can both build solutions and empower others to leverage AI effectively. You have a track record of developing production-ready models that balance scientific excellence with practical implementation. You're excited about not just building AI solutions, but also creating frameworks, evaluation methodologies, and knowledge management systems that elevate how entire organizations work with AI. As an Applied Scientist, you will... - Design and implement innovative AI solutions across our three pillars: driving internal productivity, building the blueprint for how Audible works with AI, and unlocking new value through ML & AI-powered product features - Develop machine learning models, frameworks, and evaluation methodologies that help teams streamline workflows, automate repetitive tasks, and leverage collective knowledge - Enable self-service workflow automation by developing tools that allow non-technical teams to implement their own solutions - Collaborate with product, design and engineering teams to rapidly prototype new product ideas that could unlock new audiences and revenue streams - Build evaluation frameworks to measure AI system quality, effectiveness, and business impact - Mentor and educate colleagues on AI best practices, helping raise the AI fluency across the organization ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

We are seeking a Principal Applied Scientist 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. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. We leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Define and drive the long-term scientific roadmap for whole body control and dexterous manipulation, working with autonomy and delivering artifacts that set the standard for scientific and engineering excellence - Serve as the primary technical authority on whole body control methods — including reinforcement learning, imitation learning, hierarchical quadratic programming, and model-predictive control — across the organization - Identify and tackle intrinsically hard, open-ended research problems in loco-manipulation, acquiring expertise as needed and proposing innovative solutions that span multiple teams - Collaborate with hardware and robotics leads to co-design systems for loco-manipulation, ensuring science solutions are grounded in real-world deployment constraints - Represent scientific capabilities to senior leadership and external partners; communicate complex technical concepts to both technical and non-technical audiences - Mentor and develop a community of Applied Scientists and engineers, raising the scientific bar across the organization

How can we improve the customer experience by tailoring what we display on our pages based on available data? How do we build models that help us innovate in different ways to enhance customer experience? What is the relationship between what customers do on the site vs. what they actually buy? How do we do all of this without asking the customer a single question? Our team's stated missions is to "grow each customer’s relationship with Amazon by leveraging our deep understanding of them to provide relevant and timely product, program, and content recommendations." Recommendations at Amazon is a way to help customers discover products. Our team strives to better understand how customers shop on Amazon (and elsewhere) and build recommendations models to streamline customers' shopping experience by showing the right products at the right time. Understanding the complexities of customers' shopping needs and helping them explore the depth and breadth of Amazon's catalog is a challenge we take on every day. Using Amazon’s large-scale computing resources, you will ask research questions about customer behavior, build state-of-the-art models to generate recommendations, and run these models directly on the retail website. You will participate in the Amazon ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and the retail business and you will measure the impact using scientific tools. We are looking for a passionate, hard-working, and talented Applied Scientist who has experience building mission critical, high volume applications that customers love. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of cutting edge products used everyday by people you know.

Interested in modeling and understanding customer behavior through machine learning, artificial intelligence, and data mining over TB scale data with huge business impact on millions of customers? Join our team of Scientists and Engineers developing models to predict customer behavior and optimize the customer experience with Amazon Prime. This includes identifying who our customers are, modeling customer behavior, and creating personalization systems to optimize the experience. As an ML expert, you will partner directly with product owners to intake, build, and directly apply your modeling solutions. There are numerous scientific and technical challenges you will get to tackle in this role, such as global scalability of models, combinatorial optimization, cold start problem, accelerated experimentation, short/long term goals modeling, GenAI based content creation, foundation modeling, and multi-step optimization leading to reinforcement learning of the customer journey. We employ techniques from GenAI, LLMs, deep learning, supervised learning, bandits, optimization, and RL. As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of. You will also utilize and be exposed to the latest in AI/ML technologies and infrastructure: AWS technologies (EMR/Spark, Redshift, Sagemaker, DynamoDB, S3, ...), various AI/ML algorithms and techniques (GenAI, LLMs, transformers, sequential models, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning), and statistical modeling techniques. Major responsibilities - Build and develop AI and machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams. - Leverage GenAI, LLMs, deep learning, reinforcement learning for building production AI/ML systems - Develop backtesting/offline policy estimation tools and integrate with reporting systems. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes. - Work closely with the business to understand their problem space, identify the opportunities and formulate the problems. - Use AI, machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems. - Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.

Join us at the forefront of Amazon's sustainability initiatives to work on environmental and social advancements that support Amazon's long-term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people who are passionate about making a meaningful impact on communities and the environment while helping shape the future of sustainable business practices. Sustainability Science and Innovation (SSI) is a multi-disciplinary team within WW Sustainability combining science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use data across the sustainability imperatives (carbon, water, waste, biodiversity, environmental risk and more) and these skills and capabilities to identify, develop, experiment, and scale the scientific solutions and innovations necessary for Amazon, customers and partners to help them solve their hardest unmet and evolving sustainability needs and goals. The Worldwide Sustainability (WWS) organization is seeking an exceptional scientific leader to join Amazon's Sustainability Science and Innovation team as a Senior Researcher for Materials Chemistry Innovation. This role focuses on hands-on experimental research in materials chemistry to accelerate the discovery and validation of sustainable materials through systematic synthesis, characterization, and performance testing. You will lead the design and execution of experimental research campaigns targeting catalysts, functional materials, and sustainability-relevant chemistries across multivariate parameter spaces. You will establish scientific strategy and technical roadmaps for materials discovery while leading research initiatives that tackle complex sustainability challenges in critical industrial sectors. This position requires driving breakthrough solutions in materials synthesis and characterization through internal capabilities and strategic partnerships with universities, industry scientists, and government laboratories. You will mentor junior scientists and engineers while collaborating across Amazon's Innovation Lab Network to translate research into scalable solutions. Your leadership will be essential in developing early-stage, cost-effective materials that address significant technical and economic challenges fundamental to Amazon's operations, requiring you to navigate complex trade-offs between immediate deliverables and long-term environmental impact. You will also shape how emerging automation and AI tools are applied to accelerate materials discovery workflows. The ideal candidate demonstrates extensive experience in materials synthesis, advanced characterization techniques, and systematic experimental design for performance validations. You must possess proven ability to lead cross-functional teams, establish research priorities, and drive scientific innovation from concept to implementation. Deep technical expertise in materials testing methods, combined with strategic vision for translating research into practical applications is essential. Experience with high-throughput and combinatorial experimental approaches to efficiently explore large design spaces is highly valued. Your work will establish new paradigms in sustainable materials discovery through rigorous experimental research and performance testing, directly contributing to Amazon's sustainability goals while creating scalable solutions that extend beyond the company's immediate operations. Key job responsibilities - Develop scientific models that help solve complex and ambiguous sustainability problems, and extract strategic learnings from large datasets. - Work closely with applied scientists and software engineers to implement your scientific models. - Support early-stage strategic sustainability initiatives and effectively learn from, collaborate with, and influence stakeholders to scale-up high-value initiatives. - Support research and development of cross-cutting technologies for industrial decarbonization, including building the data foundation and analytics for new AI models. - Drive innovation in key focus areas including packaging materials, building materials, and alternative fuels. About the team Diverse Experiences: World Wide Sustainability (WWS) 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. Inclusive Team Culture: 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.

We are seeking a passionate, talented, and inventive individual to join the Applied AI team and help build industry-leading technologies that customers will love. This team offers a unique opportunity to make a significant impact on the customer experience and contribute to the design, architecture, and implementation of a cutting-edge product. The mission of the Applied AI team is to enable organizations within Worldwide Amazon.com Stores to accelerate the adoption of AI technologies across various parts of our business. We are looking for a Senior Applied Scientist to join our Applied AI team to work on LLM-based solutions. On our team you will push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business. If you have a passion for AI technologies, a drive to innovate and a desire to make a meaningful impact, we invite you to become a valued member of our team. You will be responsible for developing and maintaining the systems and tools that enable us to accelerate knowledge operations and work in the intersection of Science and Engineering. You will push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business. If you have a passion for AI technologies, a drive to innovate and a desire to make a meaningful impact, we invite you to become a valued member of our team. We are seeking an experienced Scientist who combines superb technical, research, analytical and leadership capabilities with a demonstrated ability to get the right things done quickly and effectively. This person must be comfortable working with a team of top-notch developers and collaborating with our research teams. We’re looking for someone who innovates, and loves solving hard problems. You will be expected to have an established background in building highly scalable systems and system design, excellent project management skills, great communication skills, and a motivation to achieve results in a fast-paced environment. You should be somebody who enjoys working on complex problems, is customer-centric, and feels strongly about building good software as well as making that software achieve its operational goals.