Careers

The AOP (Analytics Operations and Programs) team is responsible for creating core analytics, insight generation and science capabilities for ROW Ops. We develop scalable analytics applications, AI/ML products and research models to optimize operation processes. You will work with Product Managers, Data Engineers, Data Scientists, Research Scientists, Applied Scientists and Business Intelligence Engineers using rigorous quantitative approaches to ensure high quality data/science products for our customers around the world. As a Data Scientist, you will play a crucial role in supporting the team by creating and maintaining the data infrastructure necessary for the advanced analytics and machine learning solutions. Our team solves a broad range of problems that can be scaled across ROW (Rest of the World including countries like India, Australia, Singapore, MENA and LATAM). Here is a glimpse of the problems that this team deals with on a regular basis: • Using live package and truck signals to adjust truck capacities in real-time • HOTW models for Last Mile Channel Allocation • Using LLMs to automate analytical processes and insight generation • Ops research to optimize middle mile truck routes • Working with global partner science teams to affect Reinforcement Learning based pricing models and estimating Shipments Per Route for $MM savings • Deep Learning models to synthesize attributes of addresses • Abuse detection models to reduce network losses Key job responsibilities 1. AI Agent development for data analytics. 2. Analyze data with statistical and ML techniques. 3. Develop analysis/model in scripting languages (e.g. Python, R) and statistical/mathematical software (e.g. SAS, Matlab, etc.). 4. Develop science-based Supply Chain solutions. 5. Analysis/model documentation. 6. Learn and understand state-of-the-art statistical and ML techniques/tools. 7. Learn and understand Amazon Supply Chain operations.

The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Scientist in the Processor Test and Measurement group. You will join a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers working at the forefront of quantum computing. This role focuses on the verification and validation of the circuit components that make up a quantum error correction (QEC) code — such as gates, reset, and readout — and on understanding how the performance of those components contributes to overall QEC performance. We are looking for someone who enjoys connecting component-level measurements to integrated system behavior, and who is motivated by working across teams to understand it. Much of the work involves partnering with processor design, theory, and QEC colleagues to validate that new devices behave as their Hamiltonians predict, and to explore the gaps when they don't. A comfort with error budgeting — reasoning about where component performance comes from and what limits it — is central to the role. Candidates with a track record of original scientific contributions will be preferred. We value strong engineering principles, resourcefulness, problem solving, and clear communication, along with the ability to work effectively within a team. As an Applied Scientist you will have the opportunity to pursue new ideas and stay abreast of the field of experimental quantum computation. Key job responsibilities We are looking to hire an Applied Scientist to help verify and validate the circuit components of our error-corrected quantum processors and to understand how their performance maps to QEC requirements. Depending on background and interest, the work may include: - Collaborating with theory and processor design teams to develop experimental test plans that validate new processor designs and check that fabricated devices meet their intent. - Characterizing the building blocks of a QEC code and building error budgets that explain and bound their performance. - Designing experiments that help separate effects such as crosstalk and spectator interactions from intrinsic component performance. - Prototyping calibration and measurement approaches that can later be matured for automated, large-scale processor bring-up and QEC demonstrations. - Investigating discrepancies between measured and expected behavior, and feeding what you learn back into design and theory. You will have the opportunity to take part in high-impact research projects that intersect with our engineering roadmap, working closely with processor, theory, and QEC stakeholders so that component-level decisions are informed by overall system performance. A day in the life About the team The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. Inclusive Team Culture Here at Amazon, 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. 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. 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. Export Control Requirement Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.

Amazon Seller Assistant is our flagship GenAI-first, multi-agent system that reimagines Seller experience. Our vision is to provide each seller with a proactive, autonomous, agentic assistant that understands their business and helps them navigate the complexities of selling by anticipating their needs, surfacing insights, resolving issues, taking actions on their behalf, and helping them grow. Amazon Seller Assistant helps millions of sellers on Amazon serve billions of customers worldwide. We are seeking a world-class Senior Data Scientist to help define and build the next generation of Amazon Seller Assistant. You will partner with top-tier scientist, engineers and product teams to launch production-grade agentic capabilities at Amazon's scale — owning your problem space end-to-end, from a crisp customer insight to a shipped product that millions of sellers rely on. Key job responsibilities • Own the science vision, strategy, and roadmap for a key Seller Assistant capability area. • Define and ship agentic experiences — sub-agent onboarding, tool onboarding, evaluations— that solve hard seller problems at scale. • Partner with scientists and engineers to translate frontier AI research into production-grade features sellers trust and depend on. • Design rigorous evaluation frameworks — automated and human-in-the-loop — to measure agent quality, accuracy, and business impact. • Deep-dive into seller data, identify unmet needs, and write compelling PRFAQs that set the direction for your team. • Drive cross-functional alignment across science, engineering, UX, and business teams to deliver with speed and quality. About the team Amazon Seller Assistant team operates at the very frontier of agentic AI and agentic commerce — not as a research group, but as a team shipping production-grade, multi-agent systems used by millions of sellers worldwide. We move with the urgency of a startup and the resources of the world's most customer-obsessed company, the latest breakthroughs in science and engineering into capabilities that sellers rely on every day.

How to use the world’s richest collection of e-commerce data to improve payments experience for our customers? Amazon Payments Data Science team seeks a Data Scientist for building analytical solutions that will address increasingly complex business questions in the Amazon Currency convertor space. Amazon.com has a culture of data-driven decision-making and demands insights that are timely, accurate, and actionable. This team provides a fast-paced environment where every day brings new challenges and new opportunities. As a Data Scientist in this team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the Amazon currency convertor business team through a combination of Gen AI, LLM and other machine learning techniques for text analytics, segmentation and prediction. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. Key job responsibilities • Understand the applications of causal inference models on real datasets, including assessment of marketing campaigns, online experiments, uplift analysis etc • Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management • Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus are • Innovate by adapting new modeling techniques and procedures • Effective exploratory data analysis, and model building using industry standard regression and classification techniques such as Random Forest, XGBoost package, Keras framework • Demonstrate thorough technical knowledge Fine Tuning of Amazon LLMs to handle large blocks of text, using Generative AI to solve for summarization tasks and prevent catastrophic forgetting, feature engineering of massive datasets, • Be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets • Have exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive

Amazon is looking for talented Postdoctoral Scientists to join our research team for a full-time research position focused on visual localization and navigation for real-world applications. Our work focuses on developing next-generation assistive technologies and logistics platforms that rely on robust, scalable visual perception systems. We are building solutions that enable devices and agents to understand, localize within, and navigate complex real-world environments—from indoor spaces with dynamic layouts to large-scale outdoor settings. We are looking for Postdoctoral Scientists to work at the intersection of computer vision, SLAM, and scene understanding—supporting innovations that will be deployed to real systems at global scale. The core technical challenges include building metric-semantic maps of complex environments, performing robust visual relocalization under appearance change, maintaining long-term map consistency, and achieving accurate monocular localization using both geometric and learning-based approaches—all under real-time constraints on real hardware. The solution space is deliberately open-ended. We are looking for researchers who want to push the boundaries of visual localization and spatial AI—and see their work running on real platforms within months. Key job responsibilities In this role you will: * Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. * Publish your innovation in top-tier academic venues and hone your presentation skills. * Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. A day in the life 0

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.

Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to lead key initiatives in robotic intelligence. As a Member of Technical Staff, you'll spearhead the development of breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence in areas such as perception, manipulation, science understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll combine hands-on technical work with scientific leadership, ensuring your team delivers robust solutions for dynamic real-world environments. You'll leverage Amazon's vast computational resources to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Lead technical initiatives in robotics foundation models, driving breakthrough approaches through hands-on research and development in areas like open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for specific research initiatives, ensuring robust performance in production environments - Mentor and support fellow scientists while maintaining strong individual technical contributions - Collaborate with engineering teams to optimize and scale models for real-world applications - Influence technical decisions and implementation strategies within your area of focus A day in the life - Develop and implement novel foundation model architectures, working hands-on with our extensive compute infrastructure - Guide and support fellow scientists in solving complex technical challenges, from sim2real transfer to efficient multi-task learning - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions within your team and with key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster - Mentor team members while maintaining significant hands-on contribution to technical solutions 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! About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through ground breaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

About the Team Our team builds and operates automated reasoning technology that powers security and privacy assurance across Amazon and AWS at scale. Our technology is deeply integrated into critical Amazon and AWS security workflows. We operate at the intersection of automated reasoning, program analysis, and applied security — and our work directly impacts the security posture of every AWS service. About the Role We are looking for an experienced Applied Science Manager to lead the team's static analysis platform science team. In this role, you will own the technical vision and roadmap for our automated reasoning engine's static analysis capabilities, drive innovation in scalable program analysis, and lead a team of applied scientists working at the frontier of automated reasoning for security while also contributing technically as a player/coach. You will partner closely with security, privacy, and compliance stakeholders across AWS to expand the reach and impact of provably correct code analysis. You will also partner closely with automated reasoning experts across the company and contribute to the science of security Key job responsibilities Technical Leadership: Own the science roadmap for our automated reasoning engine, including taint analysis, compositional heap analysis, modular method summarization, and dataflow graph generation Hands-on Contribution: Personally contribute to key research and design decisions, including prototyping novel analyses and reviewing technical artifacts Team Building & Management: Hire, develop, and retain a world-class team of applied scientists; foster a culture of scientific rigor, innovation, and operational excellence Product Integration: Partner with application security and service teams to expand our platform's integration footprint and deliver new security and privacy analysis capabilities Research & Innovation: Advance the state of the art in static program analysis, including exploring formal verification of analysis correctness (e.g., using Lean, Coq, or Dafny), expanding language support beyond Java, and developing novel analysis techniques for emerging security properties Stakeholder Engagement: Collaborate with AWS AppSec, Privacy Engineering, and service teams to understand their security assurance needs and translate them into analysis capabilities Strategic Influence: Represent our team in the broader Automated Reasoning community at Amazon; contribute to automated reasoning initiatives, and academic partnerships About the team Our team builds and operates automated reasoning technology that powers security and privacy assurance across Amazon and AWS at scale. Our automated reasoning engine is the core technology behind our managed dataflow mapping service, which automatically tracks how data flows through AWS service teams’ code and infrastructure. Our technology is deeply integrated into critical Amazon and AWS security workflows. We operate at the intersection of automated reasoning, program analysis, and applied security — and our work directly impacts the security posture of every AWS service. Diverse Experiences Amazon Security 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. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 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.

Amazon Optics owns the design, delivery, and operation of the unified physical security platform that protects Amazon's global infrastructure. We consolidate alarm management, device monitoring, and video surveillance data to deliver real-time situational awareness and actionable insights for security professionals. We work on complex challenges spanning automated threat detection, signal processing, and AI-driven security evaluation, and we are looking for talented people who want to help protect Amazon's people, assets, and operations at scale. You will join a diverse team of software engineers, data scientists, security specialists, and operations managers. You will collaborate with teams across Amazon to deliver the highest standards for physical security while enabling our customers to scale their security operations efficiently. You will experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Come work for the Optics Incident Response Tech team, specializing in the detection, triage, and resolution of physical security incidents across Amazon's global footprint. We are looking for an Applied Scientist who is passionate about applying artificial intelligence and machine learning to physical security operations. You will build services and tools that leverage AI/ML to automate false alarm resolution, enable intelligent signal processing, and deliver predictive insights from security event data. You will be part of a team building Large Language Model (LLM)-based services focused on enabling security teams to interact with alarm, access control, and video surveillance data in real time. The team works in close collaboration with other Optics services including Signals, Access Control Management, Video Surveillance and Analytics to power automated mitigations that protect Amazon's global infrastructure. If you are excited about transforming physical security operations through applied science, we would love to talk to you. Key job responsibilities Design and develop ML models for automated alarm triage, false alarm suppression, and anomaly detection across physical security signal streams (access control events, intrusion alarms, video analytics triggers) Build and optimize LLM-based systems that enable security operators to query, summarize, and interact with incident data using natural language Develop predictive models that identify emerging security patterns, correlate multi-source signals, and enable proactive incident response before threats materialize Research and implement computer vision applications for video-based threat detection, object classification, and automated situational awareness during active incidents Architect end-to-end ML pipelines from data ingestion through model training, evaluation, deployment, and monitoring in production Collaborate with software engineers to integrate ML solutions into the Optics platform's real-time event processing infrastructure Define evaluation frameworks including precision/recall metrics for alarm classification, latency requirements for real-time inference, and A/B testing protocols for model improvements Own model performance in production including drift detection, retraining cadences, and incident-driven model updates Identify and scope ambiguous problem areas where ML can transform incident response workflows, even when the business problem is not yet fully defined Drive scientific breakthroughs in areas such as multi-modal fusion (combining video and sensor data), few-shot learning for rare security events, and reinforcement learning for dynamic response prioritization Advise team members on ML best practices, model selection, feature engineering, and experimental design Influence product roadmaps by translating scientific capabilities into customer-facing features that reduce mean time to resolution and false alarm rates Engage with cross-functional stakeholders including security operations, hardware engineering, and partner teams (Signals, Access Control Management, Analytics) to align scientific investments with operational needs Reduce false alarm rates through intelligent signal classification and contextual filtering Decrease mean time to detection and resolution for genuine security incidents Increase automation coverage for routine incident types, freeing human operators for complex threat assessment Publish internal research and contribute to the broader ML/security community through papers and patents About the team Our team and customers are distributed across the globe with most of our team members on the East Coast heavily concentrated in the DMV area and JFK and some members in the Seattle area. Diverse Experiences Amazon Security 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. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 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.

Are you a PhD interested in machine learning, natural language processing, computer vision, automated reasoning, robotics, or quantum technologies? We are looking for skilled scientists capable of putting theory into practice through experimentation and invention, leveraging science techniques and implementing systems to work on massive datasets in an effort to tackle never-before-solved problems. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Scientist, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Key job responsibilities Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work. For more information on the Amazon Science community please visit https://www.amazon.science.