Careers

Amazon 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. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon 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 - Design and implement whole body control methods for balance, locomotion, and dexterous manipulation - Utilize state-of-the-art in methods in learned and model-based control - Create robust and safe behaviors for different terrains and tasks - Implement real-time controllers with stability guarantees - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for loco-manipulation - Mentor junior engineer and scientists

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC. Offered Position: Research Scientist III Job Location: Seattle, Washington Job Number: AMZ10061595 Position Responsibilities: Develop and apply state of the art machine learning methods to large, multi source datasets to build and implement risk prevention, detection and mitigation solutions. Contribute to the development of ML Ops infrastructure, as well as the creation and delivery of Amazon’s science roadmap, including Gen AI efforts. Work closely with software engineering teams to deploy innovations. Mentor and coach junior scientists, including through lunch-and-learn sessions, tech talks, and regular office hours. Publish insights in and champion industry best practices at internal and external journals and conferences. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Engineering, Mathematics, or a related field and three years of experience in the job offered or a related occupation. Employer will accept a bachelor’s degree or foreign equivalent degree in Computer Science, Engineering, Mathematics, or a related field and five years of progressive postbaccalaureate experience in the job offered or a related occupation as equivalent to a master’s degree and three years of experience. Must have three years of experience in the following skill(s): (1) conducting research in machine learning, natural language processing, computer vision, or a related functionality, and publishing findings; (2) building machine learning models including generative models for business applications, and (3) programming in Java, C++, Python or related language. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $164,955/year to $215,300/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits#0000

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON WEB SERVICES, INC. Offered Position: Applied Scientist II Job Location: Seattle, Washington Job Number: AMZ9971140 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Design and implement algorithms and formal methods for automated reasoning — including constraint solving, model checking, static analysis, and theorem proving — to verify the correctness, security, and reliability of cloud computing systems and generative AI applications. Develop new decision procedures, heuristics, and search strategies that improve the scalability and accuracy of verification tools. Build and deploy capabilities that enhance automated reasoning systems, such as learning-based heuristics for search and optimization, neural approaches to symbolic reasoning tasks, and data-driven techniques for abstraction and generalization. Extend and apply deep learning architectures (e.g., graph neural networks, transformers, recurrent models) and statistical modeling techniques (e.g., Bayesian inference, probabilistic programming) to problems in formal verification, program analysis, and code generation. Develop automated reasoning techniques for generative AI and agentic coding systems, including methods for verifying the correctness of AI-generated code, ensuring the safety and alignment of autonomous software agents, and applying formal guarantees to large language model (LLM) outputs. Design and build tools that combine symbolic reasoning with generative models to produce provably correct code and system configurations. Conduct original research at the intersection of machine learning and formal methods, including areas such as neuro-symbolic reasoning, program synthesis, interactive and automated theorem proving, abstract interpretation, scalable verification techniques, and formal methods for AI safety. Publish findings in peer-reviewed conferences and journals. Research and implement novel approaches combining ML with symbolic and logical reasoning to improve automated verification tools used across AWS services, including applications in access control policy analysis, network configuration verification, resource compliance checking, and system reliability assurance. Develop optimization methods — including linear and integer programming, convex optimization, and heuristic search — to solve constraint satisfaction, resource allocation, and scheduling problems arising in cloud computing and AI system development environments. Build and maintain production-grade automated reasoning tools and ML pipelines for AWS infrastructure. Design and execute experiments, analyze results using rigorous statistical methods, and iterate on model architectures and algorithmic strategies to improve performance at scale. Mentor junior engineers and scientists on formal methods, ML techniques, and best practices for building reliable automated reasoning systems. Position Requirements: Master's degree or foreign equivalent degree in Computer Science, Machine Learning, Statistics, or a related field and one year of research or work experience in the job offered or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Employer will accept a Bachelor's degree or foreign equivalent degree in Computer Science, Machine Learning, Statistics, or a related field and five years of progressive post baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master's degree and one year of research or work experience. Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $153,456/year to $193,200/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000

At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity—from electronics to groceries to digital content. The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data—while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily. Amazon's Item and Relationship Platform group is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers. Key job responsibilities * Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval—translating ambiguous business challenges into tractable scientific frameworks * Design and implement leading models leveraging VLMs, foundation models, and agentic architectures to solve product identity, relationship inference, and catalog understanding at billion-product scale * Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions * Own end-to-end ML pipelines from research ideation to production deployment—processing petabytes of multimodal data with rigorous evaluation frameworks * Define research roadmaps aligned with business priorities, balancing foundational research with incremental product improvements * Mentor peer scientists and engineers on advanced ML techniques, experimental design, and scientific rigor—building organizational capability in GenAI and multimodal AI * Represent the team in the broader science community—publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research

Employer: Amazon.com Services LLC Position: Data Scientist II - AMZ27596.1 Location: Irving, TX Multiple Positions Available: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. (40 hours / week, 8:00am-5:00pm, Salary Range $141773 - $184000) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000

Are you excited about developing agentic AI, LLM and computer vision models that revolutionize Amazon's Fulfillment network? Are you looking for opportunities to apply state-of-the-art AI on real-world problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics, we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience — at Amazon scale. To this end, we are looking for an Applied Scientist who will build and deploy models that make smarter decisions on a wide array of multi-modal signals. Together, we will be pushing beyond the state of the art in optimizing one of the most complex systems in the world: Amazon's Fulfillment Network. Key job responsibilities In this role, you will build agentic AI solutions and multi-modal deep learning models that understand how products and packages flowing through Amazon’s fulfillment network. You will build models that solve challenging problems like understanding warehouse operations systems, or visual defect detection on Amazon's entire retail catalog (billions of different items, thousands of new items every day). You will work with a diverse set of very large multi-modal real-world datasets, including imagery, natural language and structured data. You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. A day in the life AFT AI delivers the AI solutions that empower Amazon’s fulfillment network to make smarter decisions. You will work on an interdisciplinary project involving scientists and engineers with deep expertise in developing state-of-the-art AI solutions at scale. You will work with images, videos, natural language, and sequences of events from existing or new hardware. You will adapt state-of-the-art agentic AI, deep learning, language understanding and computer vision techniques to develop solutions for business problems in the Amazon Fulfillment Network. About the team Amazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment network. We invent and deliver software, hardware, and science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. AFT AI is spread across NA (Bellevue, WA) and Europe (Berlin, Germany). We are hiring candidates to work out of the Berlin location. Publicly available articles showcasing some of our work: - Visual Defect Detection: https://www.amazon.science/blog/novel-kaputt-dataset-sets-new-benchmark-for-large-scale-visual-defect-detection - Eluna: https://www.aboutamazon.com/news/operations/new-robots-amazon-fulfillment-agentic-ai

Are you interested in how to build AI reasoning systems that give provably correct answers? Are you excited by science at the interface of classical AI reasoning and Large Language Models (LLMs)? Would you like to apply your technology to serve operations customers better? Amazon Robotics is looking for a talented Applied Scientist. You will innovate on combining language models (LMs) with classical AI reasoning. You will work with a team of scientists and engineers to achieve this. You will publish your results in papers at leading venues in AI. You will be part of a larger team and have the opportunity to work on problems such as: using LMs to generate plans, using AI reasoning to verify plan correctness, learning efficient reasoning strategies, self-improving models. You will work on basic science and on business problems in robotics, automation and fulfillment across our operations. Key job responsibilities In this role you will: • Work closely with other scientists and engineers, and be part of Amazon’s diverse global science community. • Publish your research in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent new techniques in your area(s) of expertise. A day in the life You'll meet regularly with your technical lead and your team on your ideas, get guidance and feedback, work together on architectures and algorithms, author papers, build AI systems, all with the aim of delivering results for your operations customers. You'll work closely with other scientists to review your plans and results. You'll meet with engineers to implement your ideas at scale. About the team The Veritas team is a science team working at the boundary between language models and classical AI reasoning. We work across on customer problems in fulfillment, automation and robotics. We focus on high quality research science informed by practical problems.

We are seeking an Applied Scientist to help build Amazon’s next-generation customer memory and personalization systems. Are you interested in building systems that move beyond reacting to customer behavior, to actually understanding and remembering it over time? Our team is building Amazon’s customer memory layer – a system that extracts, curates, and reasons over customer knowledge to power next-generation personalization. This includes transforming noisy, unstructured signals into durable, high-quality representations of customer preferences, intents, and life events, and using them in real time to improve customer experiences. We are part of Amazon’s Personalization organization, a high-performing group that leverages large-scale machine learning, generative AI, and distributed systems to deliver highly relevant customer experiences. We tackle challenging problems at the intersection of information extraction, knowledge representation, LLM reasoning, and recommendation systems. Our systems operate under real-world constraints of scale, latency, and quality, requiring careful tradeoffs between precision, recall, and responsiveness. This team plays a central role in defining how Amazon understands its customers, and how that understanding is applied across the shopping experience. As an Applied Scientist, you will design and build ML and LLM-powered solutions for Amazon's customer memory and personalization systems. You will work on how customer knowledge is extracted, validated, and applied in production systems. You will own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale. You will deliver high-quality, scalable systems that power customer-facing experiences. You will drive work across areas such as fact extraction, memory quality and lifecycle, temporal reasoning, and grounded personalization, while navigating tradeoffs between quality, latency, and coverage. You will collaborate closely with engineering and product teams to translate research into measurable customer impact. Please visit https://www.amazon.science for more information.

Amazon DynamoDB is a fully managed NoSQL database that serves more than 1 million customers and delivers single-digit millisecond performance at any scale. It supports individual tables over 200TB and sustains over half a million requests per second for hundreds of customers, with up to 99.999% availability. Behind that scale sits a large fleet of capacity that must be placed and balanced continuously. We are looking for an Applied Scientist to advance the science of capacity utilization and data placement across the DynamoDB fleet. You will work backwards from customer experience and fleet economics to find where capacity is used inefficiently, where scaling bottlenecks constrain the service, and where smarter data placement can raise utilization without degrading latency or availability. You will turn these findings into models and algorithms that inform capacity profile decisions and placement policy. You will partner closely with the DynamoDB teams to bring your inputs into production decisions. This is a customer-obsessed science role for a self-driven scientist. Many of the problems are not yet well defined and no textbook solution exists. You will frame the problem, extend state-of-the-art approaches or invent new ones, and drive the work to production impact with a strong bias for action. Key job responsibilities Identify capacity usage optimization opportunities across the DynamoDB fleet. Quantify the customer and cost impact of each opportunity. - Model the scaling bottlenecks of the service and characterize how they constrain placement and utilization. - Develop data placement approaches that balance customer experience (latency, availability, throughput headroom) against optimal capacity utilization. - Partner with the DynamoDB performance team to incorporate your inputs into capacity profile decisions and placement policy. Validate impact with production data. - Build components that integrate directly into production systems or that directly support the large systems making placement and capacity decisions. - Scrutinize the performance of your algorithms and software during implementation. Resolve root causes and leave systems easier to maintain. - Author or co-author papers for internal or external peer-reviewed venues when the work is novel and business considerations allow.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC. Offered Position: Applied Scientist III Job Location: New York, New York Job Number: AMZ10165497 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and two years of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and five years of progressive post-baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master’s degree and two years of research or work experience. Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language; and (2) conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $183,800/year to $248,700/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000