Careers

The Agentic Automated Reasoning Group is building the next generation of software verification tools combining advances in artificial intelligence, the computational capacity of the cloud, and our deep expertise in the domain. Join us if you want to be a part of this transformational endeavor. The Strata team (https://github.com/strata-org) is seeking an applied scientist with broad interest and expertise in model checking, interactive theorem proving, programming language semantics, and generative AI. You will combine your expertise with that of your coworkers to build new tools that solve code analysis problems previously considered beyond reach. Our application areas span all the way from Infrastructure as Code to high-performance cryptography written in assembly code, while our methods span from interactive theorem proving to automated test generation. Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. https://aws.amazon.com/security/provable-security/ Key job responsibilities - Work with customer teams to understand the nature of their software and the properties they need to establish of it. - Identify tools and methods capable of addressing the verification needs of customers, including any novel analysis capabilities required. - Use techniques spanning property-based testing to model checkers, and interactive theorem provers to establish program properties. - Explore generative AI techniques to help customers formalize their requirements, find revealing tests, generate required boiler plate for testing and model checking, and find and repair program proofs. About the team The Agentic Automated Reasoning Group at AWS develops and applies state of the art formal methods and automated reasoning techniques to ensure the security, reliability, and correctness of AWS services and customer applications, with a strong focus on AI based agents. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS. We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries.

The Agentic Automated Reasoning Group is building the next generation of software verification tools combining advances in artificial intelligence, the computational capacity of the cloud, and our deep expertise in the domain. Join us if you want to be a part of this transformational endeavor. The Strata team (https://github.com/strata-org) is seeking an applied scientist with broad interest and expertise in model checking, interactive theorem proving, programming language semantics, and generative AI. You will combine your expertise with that of your coworkers to build new tools that solve code analysis problems previously considered beyond reach. Our application areas span all the way from Infrastructure as Code to high-performance cryptography written in assembly code, while our methods span from interactive theorem proving to automated test generation. Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. https://aws.amazon.com/security/provable-security/ Key job responsibilities - Work with customer teams to understand the nature of their software and the properties they need to establish of it. - Identify tools and methods capable of addressing the verification needs of customers, including any novel analysis capabilities required. - Use techniques spanning property-based testing to model checkers, and interactive theorem provers to establish program properties. - Explore generative AI techniques to help customers formalize their requirements, find revealing tests, generate required boiler plate for testing and model checking, and find and repair program proofs. About the team The Agentic Automated Reasoning Group at AWS develops and applies state of the art formal methods and automated reasoning techniques to ensure the security, reliability, and correctness of AWS services and customer applications, with a strong focus on AI based agents. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS. We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries.

As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art LLM systems that revolutionize how millions of customers interact with Alexa across many languages and locales. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate the latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle: from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to adapting and post-training large language models (SFT, RL, DPO) and conducting rigorous A/B testing across diverse devices, endpoints, and languages. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact, helping bring a consistent experience to customers in every language they speak. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices, endpoints, and languages. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to adapting large language models through supervised fine-tuning, reinforcement learning, and preference optimization (SFT, RL, DPO), building and deploying automated training and evaluation pipelines, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of conversational AI, including how it generalizes across multiple languages and scripts. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, fine-tune and align LLMs, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges, from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI, from multilingual natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.

Do you want to lead the development of advanced machine learning systems that protect millions of customers and power a trusted global eCommerce experience? Are you passionate about modeling terabytes of data, solving highly ambiguous fraud and risk challenges, and driving step-change improvements through scientific innovation? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right place for you. We are seeking a Senior Applied Scientist to define and drive the scientific direction of large-scale risk management systems that safeguard millions of transactions every day. In this role, you will lead the design and deployment of advanced machine learning solutions, influence cross-team technical strategy, and leverage emerging technologies—including Generative AI and LLMs—to build next-generation risk prevention platforms. Key job responsibilities Lead the end-to-end scientific strategy for large-scale fraud and risk modeling initiatives Define problem statements, success metrics, and long-term modeling roadmaps in partnership with business and engineering leaders Design, develop, and deploy highly scalable machine learning systems in real-time production environments Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies to automate and transform risk evaluation Influence system architecture and partner with engineering teams to ensure robust, scalable implementations Establish best practices for experimentation, model validation, monitoring, and lifecycle management Mentor and raise the technical bar for junior scientists through reviews, technical guidance, and thought leadership Communicate complex scientific insights clearly to senior leadership and cross-functional stakeholders Identify emerging scientific trends and translate them into impactful production solutions

Do you want to join an innovative team of scientists applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience? Are you excited about modeling terabytes of data and building state-of-the-art algorithms to solve complex, real-world fraud and risk challenges? Do you enjoy owning end-to-end machine learning problems, directly influencing customer experience and company profitability, while collaborating in a diverse, high-performing team? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to design, develop, and deploy advanced algorithmic systems that safeguard millions of transactions every day. In this role, you will independently drive model development from problem formulation to production deployment, build scalable ML solutions, and leverage emerging technologies—including Generative AI and LLMs—to enhance fraud detection and next-generation risk prevention systems. Key job responsibilities Own end-to-end development of machine learning models for large-scale risk management systems Analyze large volumes of historical and real-time data to identify fraud patterns and emerging risk trends Design, develop, validate, and deploy innovative models to production environments Apply GenAI/LLM technologies to automate risk evaluation and improve operational efficiency Collaborate closely with software engineering teams to implement scalable, real-time model solutions Partner with operations and business stakeholders to translate risk insights into measurable impact Establish scalable and automated processes for data analysis, model experimentation, validation, and monitoring Track model performance and business metrics; communicate insights clearly to technical and non-technical stakeholders Research and implement novel machine learning and statistical methodologies

Do you want to join an innovative team of scientists applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience? Are you excited about modeling terabytes of data and building state-of-the-art algorithms to solve complex, real-world fraud and risk challenges? Do you enjoy owning end-to-end machine learning problems, directly influencing customer experience and company profitability, while collaborating in a diverse, high-performing team? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to design, develop, and deploy advanced algorithmic systems that safeguard millions of transactions every day. In this role, you will independently drive model development from problem formulation to production deployment, build scalable ML solutions, and leverage emerging technologies—including Generative AI and LLMs—to enhance fraud detection and next-generation risk prevention systems. Key job responsibilities Own end-to-end development of machine learning models for large-scale risk management systems Analyze large volumes of historical and real-time data to identify fraud patterns and emerging risk trends Design, develop, validate, and deploy innovative models to production environments Apply GenAI/LLM technologies to automate risk evaluation and improve operational efficiency Collaborate closely with software engineering teams to implement scalable, real-time model solutions Partner with operations and business stakeholders to translate risk insights into measurable impact Establish scalable and automated processes for data analysis, model experimentation, validation, and monitoring Track model performance and business metrics; communicate insights clearly to technical and non-technical stakeholders Research and implement novel machine learning and statistical methodologies

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Applied Scientist II will contribute to the development of AI systems. The role requires extending existing scientific techniques and inventing new ones to address specific customer needs at a project level. You should be comfortable working semi-autonomously on difficult problems with visible risks or roadblocks. You'll work closely with technical leaders within the team. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Design and implement solutions that extend or adapt scientific approaches for customer needs at the project level * Deliver components into production that meet high quality standards (efficient, reproducible, testable code) * Produce research reports demonstrating correctness, scholarship, and scientific rigor * Work with product and science teams to deliver impactful AI features * Contribute to operational excellence in the team's deliverables About the team ABOUT AWS: Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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.

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Applied Scientist II will contribute to the development of AI systems. The role requires extending existing scientific techniques and inventing new ones to address specific customer needs at a project level. You should be comfortable working semi-autonomously on difficult problems with visible risks or roadblocks. You'll work closely with technical leaders within the team. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Design and implement solutions that extend or adapt scientific approaches for customer needs at the project level * Deliver components into production that meet high quality standards (efficient, reproducible, testable code) * Produce research reports demonstrating correctness, scholarship, and scientific rigor * Work with product and science teams to deliver impactful AI features * Contribute to operational excellence in the team's deliverables About the team ABOUT AWS: Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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're looking for an Applied Scientist to develop computer vision and machine learning models that keep Amazon's workforce safe. Your research and models will be deployed across hundreds of operations facilities globally, helping to reduce safety incidents for over 1.5 million people. You'll join a team where science meets real-world impact. You'll design and train models for tasks like activity recognition, anomaly detection, object detection, and risk prediction using video, image, and sensor data from Amazon's operational environments. You'll work closely with software engineers to take your models from experimentation through production deployment at scale. If you're excited about applying advanced ML research to a problem that genuinely improves people's lives, and you thrive in an environment where your work ships to production, not just to a paper, this is the role for you. Key job responsibilities - Design, develop, and deploy computer vision and machine learning models for workplace safety applications (e.g., activity recognition, anomaly detection, pose estimation, object detection) - Develop and iterate on model architectures using deep learning frameworks, running experiments on large-scale video, image, and sensor datasets - Collaborate with software engineers to productionize models - optimizing for inference latency, accuracy, and reliability in edge and cloud environments - Analyze operational data to identify patterns and signals indicating safety risks, and translate findings into actionable model improvements - Stay current with the latest research in computer vision, deep learning, and related fields, and evaluate applicability to safety use cases - Communicate findings and technical approaches clearly to both technical and non-technical stakeholders through documents, presentations, and design reviews - Contribute to the team's scientific culture through code reviews, knowledge sharing, and mentorship About the team Amazon's Workplace Health & Safety (WHS) organization is responsible for keeping over 1.5 million employees safe across our global retail operations. Within WHS, our technology team builds the science and engineering capabilities that power Amazon's safety strategy at scale. We're a cross-functional group of applied scientists, software engineers, data engineers, and technical program managers developing computer vision systems, generative AI applications, sensor and IoT solutions, and analytics platforms - all aimed at reducing workplace injuries. As an applied scientist here, you'll partner directly with engineers who build the production infrastructure for your models, and with safety domain experts who ground your work in real operational needs. Our culture values scientific rigor, fast iteration, and shipping models that create measurable safety outcomes.

At Amazon Robotics, we design advanced robotic systems capable of intelligent perception, learning, and action alongside humans, at massive scale. Our mission is to deploy robots that increase productivity and efficiency across Amazon fulfillment centers while operating safely and robustly in complex, contact-rich environments. We are seeking an Applied Scientist to develop manipulation controllers for robotic systems operating in contact-rich, uncertain environments. In this role, you will design force-aware control strategies grounded in impedance/admittance frameworks and augment them with data-driven policy learning to achieve robust, adaptive manipulation behaviors. You will combine physics-based modeling, control-theoretic design, and machine learning to build manipulation capabilities that generalize across objects, tasks, and operational conditions. You will collaborate closely with experts in perception, machine learning, motion planning, controls, and software engineering to deliver solutions that perform reliably on real hardware at production scale. As part of this role, you will study and extend relevant academic and industry research in robot learning and manipulation, prototype and validate learned policies in simulation and on hardware, and transition successful approaches into production systems. Successful candidates demonstrate strong intuition for physical systems, experience applying ML to robotics problems, and the ability to reason about failure modes, edge cases, and deployment constraints in contact-rich manipulation. Clear communication, hands-on experimentation, and a bias toward practical impact are essential. Key job responsibilities - Research, design, implement, and evaluate machine learning–based manipulation policies for contact-rich tasks, integrating learning with feedback control, estimation, and motion planning. - Develop learning frameworks that leverage simulation, real-world data, and hybrid physics- and data-driven models to enable robust agency interaction, grasping, insertion, and object handling. - Design and execute experiments in simulation and on hardware to train, validate, and stress-test learned manipulation policies under real-world variability and uncertainty. - Collaborate with software engineering teams to deliver scalable, real-time, and maintainable implementations of learning-based manipulation algorithms in production robotic systems. - Partner with cross-functional teams across perception, hardware, systems engineering, science, and operations to transition learned policies from research prototypes to reliable, production-ready capabilities across Amazon Robotics platforms. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan 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!