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 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.

Do you want to lead the Ads industry and redefine how we measure the effectiveness of Amazon Ads business? Are you passionate about causal inference, Deep Learning & AI, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation? If so, come join Amazon Ads to be a science leader within our Advertising Incrementality Measurement science team! Our work builds the foundations for providing customer-facing advertising measurement tools, furthering internal research & development, and building out Amazon's advertising measurement offerings. Incrementality is a lynchpin for the next generation of Amazon Advertising measurement solutions, and this role will play a key role in the release and expansion of these offerings. We are looking for a thought leader that has an aptitude for delivering customer-focused solutions and who enjoys working on the intersection of Big-Data analytics, Machine/Deep Learning, and Causal Inference. A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine learning and/or econometric modeling to solve business problems. You should have strong analytical and communication skills, be able to work with product managers to define key business questions and work with the engineering team to bring our solutions into production. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon advertising, and also allow you to become part of our large science community. Key job responsibilities • Apply expertise in ML/DL, AI, and causal modeling to develop new models that describe how advertising impacts customers’ actions • Own the end-to-end development of novel scientific models that address the most pressing needs of our business stakeholders and help guide their future actions • Improve upon and simplify our existing solutions and frameworks • Review and audit modeling processes and results for other scientists, both junior and senior • Work with leadership to align our scientific developments with the business strategy • Identify new opportunities that are suggested by the data insights • Bring a department-wide perspective into decision making • Develop and document scientific research to be shared with the greater science community at Amazon About the team AIM is a cross disciplinary team of engineers, product managers, economists, data scientists, and applied scientists with a charter to build scientifically-rigorous causal inference methodologies at scale. Our job is to help customers cut through the noise of the modern advertising landscape and understand what actions, behaviors, and strategies actually have a real, measurable impact on key outcomes. The data we produce becomes the effective ground truth for advertisers and partners making decisions affecting millions in advertising spend.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.

Are you inspired by invention? Do you want to see how your work impacts the bigger picture? If yes, you'll fit right in at Amazon's Last Mile Simulations and Analytics Engineering team. The WW AMZL Simulations and Analytics Engineering team drives innovation across our Last Mile network delivery stations through digital twin technology and the seamless integration of process engineering, physics, design, technology, and robotics. We start with the customer and work backwards in everything we do. If you're interested in joining a rapidly growing team building a unique, solutions-advisory group with a relentless focus on the customer, you've come to the right place. This is a blue-sky role where you'll roll up your sleeves and dive into big data sets to build digital twins—discrete event simulations, robotics models, and physics-based 3D simulations using tools like Flexsim, AnyLogic, and Emulate 3D. You'll develop experimentation systems at scale, integrating process workflows, physical dynamics, facility design, emerging technologies, and robotic automation to create comprehensive virtual replicas of our operations. Build optimization algorithms and leverage advanced technologies across Amazon. This is an opportunity to think big about solving challenging problems for our customers. As a Senior Simulation Scientist, you'll deep dive into complex problems and drive relentlessly towards innovative solutions with cross-functional teams. You'll interface and influence various functional teams and individuals at all levels of the organization. Lead strategic digital twin and simulation projects that integrate process design, physics modeling, technology innovation, and robotics to drive operational decisions. Your expertise in synthesizing and communicating insights to audiences of varying technical sophistication will enable you to answer specific business questions and innovate for the future. You'll apply advanced multi-disciplinary methodologies—combining process optimization, physics simulation, design thinking, and robotic systems—to complex use cases across the Last Mile network. You'll also contribute to the end-state vision for digital twin simulation and experimentation of future delivery stations at Amazon. Key job responsibilities • Lead the design, implementation, and delivery of the simulation data science solutions to perform system of systems discrete event simulations for significantly complex operational processes that have a long-term impact on a product, business, or function using FlexSim, Demo 3D, AnyLogic or any other Discrete Event Simulation (DES) software packages • Lead strategic modeling and simulation research projects to drive process design decisions • Be an exemplary practitioner in simulation science discipline to establish best practices and simplify problems to develop discrete event simulations faster with higher standards • Identify and tackle intrinsically hard process flow simulation problems (e.g., highly complex, ambiguous, undefined, with less existing structure, or having significant business risk or potential for significant impact • Deliver artifacts that set the standard in the organization for excellence, from process flow control algorithm design to validation to implementations to technical documents using simulations • Be a pragmatic problem solver by applying judgment and simulation experience to balance cross-organization trade-offs between competing interests and effectively influence, negotiate, and communicate with internal and external business partners, contractors and vendors for multiple simulation projects • Provide simulation data and measurements that influence the business strategy of an organization. Write effective white papers and artifacts while documenting your approach, simulation outcomes, recommendations, and arguments • Lead and actively participate in reviews of simulation research science solutions. You bring clarity to complexity, probe assumptions, illuminate pitfalls, and foster shared understanding within simulation data science discipline • Pay a significant role in the career development of others, actively mentoring and educating the larger simulation data science community on trends, technologies, and best practices • Use advanced statistical /simulation tools and develop codes (python or another object oriented language) for data analysis , simulation, and developing modeling algorithms • Lead and coordinate simulation efforts between internal teams and outside vendors to develop optimal solutions for the network, including equipment specification, material flow control logic, process design, and site layout • Deliver results according to project schedules and quality A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

Employer: Amazon Data Services, Inc. Position: Manager III, Data Science - AMZ14164.12 Location: Herndon, VA Multiple Positions Available: 1. Lead a team of data scientists in developing and deploying machine learning models for infrastructure capacity planning and demand forecasting at global scale. 2. Design predictive models and statistical frameworks to optimize resource utilization and inform long-term infrastructure investment decisions. 3. Develop risk-based planning approaches utilizing advanced statistical methods and ML techniques to quantify uncertainty and set operational targets. 4. Build and maintain end-to-end ML pipelines for model training, inference, and monitoring in production environments. 5. Collaborate with engineering, product, and finance partners to translate complex business requirements into quantifiable metrics and automated decisionsupport systems. 6. Design experimentation frameworks and model validation methodologies to ensure accuracy and reliability of forecasts. 7. Lead weekly business reviews of model performance, presenting findings and recommendations to senior leadership. 8. Manage and mentor a team of data scientists and engineers across multiple levels, driving best practices in ML development, code quality, and production deployment. 9. Utilize Python, SQL, and cloud-based ML infrastructure to deliver scalable data science solutions. (40 hours / week, 8:00am-5:00pm, Salary Range $175100 - $236900) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000

Are you passionate about solving big problems from ground-up? Do you enjoy building new state-of-the-art products at internet scale? Come lead the innovation in this startup team, vertical ad products. This is a green field problem without a known answer or a pattern to follow. We have ambitious vision to simplify full funnel advertising solutions, at scale, with specialized agentic AI-powered models and diversify the demand to strategic verticals including finserv, autos, locals.. etc. We are seeking an experienced Applied Scientist to drive innovation in our Ads Foundational Model. In this individual contributor role, you will apply advanced machine learning techniques to improve advertiser performance and customer experience. Key job responsibilities - Drive the science vision for developing evaluations of the Ads Agent - Partner with senior and principal scientists from across Ads to develop best practices for evaluating agent performance both online and offline - Raise the science bar for all agent evaluations developed in Ads. - Deliver a data driven foundation for making decisions about when new features are ready to launch in Ads Agent.

Amazon Business System Integrations connects Amazon Business with millions of business users and thousands of partner procurement, ERP, and finance systems. We build the APIs, protocols, and agentic experiences that let customers buy on Amazon Business directly from the systems they already use. As an Applied Scientist on this team, you will own and advance the ML and GenAI capabilities that make these integrations smarter, faster, and more reliable. You will drive model accuracy, scientific innovation, and global scale across external systems integrations. Our work includes API-based and protocol-based shopping, such as punchout and emerging agent protocols, along with agentic interactions where buyers and AI agents search, compare, and purchase through natural language. It also covers partner onboarding and integration automation, mapping and normalizing catalog, product, and order data across many partner formats, and evaluation frameworks that measure the quality, accuracy, and latency of our agents. Key job responsibilities As an Applied Scientist on this team, you will work across three dimensions: Invent, Implement, and Influence. Invent: You bring deep domain knowledge and fluency with state-of-the-art scientific approaches and emerging research. You practice customer-obsessed science, working backwards from the needs of business buyers, procurement teams, and integration partners to extend or invent new ML approaches, even when no textbook solution exists. You design novel ML and LLM-based methods for agentic shopping, product search and matching, schema and data mapping across partner systems, and automated evaluation of agent quality. You help define the research agenda for our agentic and protocol-based capabilities, and you lead the scientific strategy for accurate, low-latency responses in conversational and API-driven procurement. You author or co-author articles for internal or external peer-reviewed venues when appropriate and not precluded by business considerations. Implement: The ML components you develop are integrated directly into production systems serving Amazon Business customers and partners worldwide. You make sound tradeoffs between accuracy and latency, innovation and stability, and short-term and long-term solutions, favoring reuse and established frameworks where appropriate. You make progress semi-autonomously with only occasional guidance, implement at the right level of complexity the first time, and evaluate emerging technologies, including LLMs and GenAI frameworks, largely on your own. You ensure your models and pipelines integrate robustly with catalog, offer, cart, order, and partner data sources and with the services that power external integrations. Influence: You contribute to planning for the team, including goals, priorities, and roadmaps for ML and GenAI capabilities. You lead the scientific strategy for expanding agentic and integration capabilities across new partners, protocols, and countries. You collaborate with engineering, product, and program teams across Amazon Business so that data integration and ML pipelines are robust and scale with adoption. You mentor scientists and engineers, champion best practices for the AI-Driven Development Life Cycle (AIDLC), and provide peer feedback on research methods and results. You help recruit bar-raising talent through interview drives, and you are visible in the broader scientific community as a subject matter expert, including serving as a Program Committee member or reviewer for peer-reviewed venues.

Amazon Business System Integrations connects Amazon Business with millions of business users and thousands of partner procurement, ERP, and finance systems. We build the APIs, protocols, and agentic experiences that let customers buy on Amazon Business directly from the systems they already use. As an Applied Scientist on this team, you will own and advance the ML and GenAI capabilities that make these integrations smarter, faster, and more reliable. You will drive model accuracy, scientific innovation, and global scale across external systems integrations. Our work includes API-based and protocol-based shopping, such as punchout and emerging agent protocols, along with agentic interactions where buyers and AI agents search, compare, and purchase through natural language. It also covers partner onboarding and integration automation, mapping and normalizing catalog, product, and order data across many partner formats, and evaluation frameworks that measure the quality, accuracy, and latency of our agents. Key job responsibilities As an Applied Scientist on this team, you will work across three dimensions: Invent, Implement, and Influence. Invent: You bring deep domain knowledge and fluency with state-of-the-art scientific approaches and emerging research. You practice customer-obsessed science, working backwards from the needs of business buyers, procurement teams, and integration partners to extend or invent new ML approaches, even when no textbook solution exists. You design novel ML and LLM-based methods for agentic shopping, product search and matching, schema and data mapping across partner systems, and automated evaluation of agent quality. You help define the research agenda for our agentic and protocol-based capabilities, and you lead the scientific strategy for accurate, low-latency responses in conversational and API-driven procurement. You author or co-author articles for internal or external peer-reviewed venues when appropriate and not precluded by business considerations. Implement: The ML components you develop are integrated directly into production systems serving Amazon Business customers and partners worldwide. You make sound tradeoffs between accuracy and latency, innovation and stability, and short-term and long-term solutions, favoring reuse and established frameworks where appropriate. You make progress semi-autonomously with only occasional guidance, implement at the right level of complexity the first time, and evaluate emerging technologies, including LLMs and GenAI frameworks, largely on your own. You ensure your models and pipelines integrate robustly with catalog, offer, cart, order, and partner data sources and with the services that power external integrations. Influence: You contribute to planning for the team, including goals, priorities, and roadmaps for ML and GenAI capabilities. You lead the scientific strategy for expanding agentic and integration capabilities across new partners, protocols, and countries. You collaborate with engineering, product, and program teams across Amazon Business so that data integration and ML pipelines are robust and scale with adoption. You mentor scientists and engineers, champion best practices for the AI-Driven Development Life Cycle (AIDLC), and provide peer feedback on research methods and results. You help recruit bar-raising talent through interview drives, and you are visible in the broader scientific community as a subject matter expert, including serving as a Program Committee member or reviewer for peer-reviewed venues.

Amazon Web Services (AWS) is assembling an elite team of world-class scientists and engineers to pioneer the next generation of AI-driven development tools. Join the Amazon Kiro LLM-Training team and help create groundbreaking generative AI technologies including Kiro IDE and Amazon Q Developer that are transforming the software development landscape. Key job responsibilities As a key member of our team, you'll be at the forefront of innovation, where cutting-edge research meets real-world application: - Push the boundaries of reinforcement learning and post-training methodologies for large language models specialized in code intelligence - Invent and implement state-of-the-art machine learning solutions that operate at unprecedented Amazon scale - Deploy revolutionary products that directly impact the daily workflows of millions of developers worldwide - Break new ground in AI and machine learning, challenging what's possible in intelligent code assistance - Publish and present your pioneering work at premier ML and NLP conferences (NeurIPS, ICML, ICLR , ACL, EMNLP) - Accelerate innovation by working directly with customers to rapidly transition research breakthroughs into production systems About the team The AWS Developer Agents and Experiences (DAE) team is reimagining the builder experience through generative AI and foundation models. We're leveraging the latest advances in AI to transform how engineers work from IDE environments to web-based tools and services, empowering developers to tackle projects of any scale with unprecedented efficiency. Broadly, AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Search's mission is to connect customers worldwide to Amazon's vast selection, helping them quickly evaluate their options and find what they need while also inspiring exploration and discovery. We are working on delivering a search results page that understands the full spectrum of customer intent, from open-ended discovery to spearfishing, and assembles itself accordingly with every part of the page reflecting the customer's specific context, query, intent, preferences and real-time browsing signals adapting as their mission evolves. We are looking for a Senior Applied Science Manager to lead the development of leading AI/ML solutions that power intelligent, adaptive search experiences for hundreds of millions of customers worldwide. This is a rare opportunity to shape the science strategy for one of Amazon's most impactful programs at the intersection of massive-scale behavioral data, real-time decision systems, and generative AI. You will lead cross-functional teams of scientists, engineers, and product managers to integrate LLMs into existing search systems while delivering low-latency solutions that serve billions of daily interactions. Key job responsibilities A Sr. Manager, Applied Science in this role develops a comprehensive science strategy that brings deep expertise in page optimization and faceout optimization to drive adaptive search experiences, working with Principal Scientists to innovate on LLM integration and real-time personalization. You translate this strategy into measurable business impact by leading cross-functional teams through experimentation, ensuring every component of the search results page reflects customer intent and context while maintaining strict latency requirements.