Careers

Work on ML teams building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost. As an Applied Scientist II, you will set scientific direction, mentor applied scientists, and partner with engineering and product leaders to deliver production-grade ML solutions at massive scale. Key job responsibilities 1. Lead and grow a high-performing team of Applied Scientists, providing technical guidance, mentorship, and career development. 2. Define and own the scientific vision and roadmap for ML solutions powering large-scale transportation planning and execution. 3. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning. 4. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions. 5. Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability. 6. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing. A day in the life Your day includes reviewing model performance and business metrics, guiding technical design and experimentation, mentoring scientists, and driving roadmap execution. You’ll balance near-term delivery with long-term innovation while ensuring solutions are robust, interpretable, and scalable. Ultimately, your work helps improve delivery reliability, reduce costs, and enhance the customer experience at massive scale.

We are seeking a Principal Applied Scientist to own the scientific vision across Agentic WorkSpaces. This is a foundational role spanning the full portfolio - Personal Applications and Core and the agentic surfaces (WS4Builders and WorkSpaces for Agents). You will define how we measure, improve, and guarantee the performance of AI agents and human-AI teams. A core part of the role is defining the science agenda itself - identifying which problems are most worth solving and where the highest-leverage bets lie. Directions worth exploring might include Organizational Intelligence (turning institutional knowledge into agent-consumable skills) AI Agent Experience / AiAX (agent observability and autonomous remediation) and contextual behavioral security that adapts enforcement in real time for human and agent sessions - but these are illustrative examples not a fixed roadmap and many other directions are possible. You will help define which ones we pursue. The problems you will solve do not have established industry patterns. You will set the direction for the science of how AI agents and people perceive, reason about, and act reliably within computing environments at enterprise scale. Key job responsibilities • Set the long-term scientific vision: Define what best-in-class agent performance evaluation and learning look like across Agentic WorkSpaces - for computer-using agents and human-AI teams alike. Identify the unsolved scientific problems chart a multi-year research roadmap and secure buy-in from VP-level leadership. • Solve highly ambiguous novel problems: Independently frame and deliver solutions to foundational challenges in agent perception, reasoning, evaluation, reliability, and human-AI collaboration - problems where neither the approach nor the success criteria are pre-defined. • Own the evaluation and measurement foundation: Build the benchmarks datasets and metrics that quantify agent and team accuracy, cost, productivity, and safety across the portfolio and diverse enterprise workflows and that gate what we ship. • Drive cross-organizational scientific alignment: Work across partner teams (AgentCore, Bedrock model teams, Identity, Security, the MCP ecosystem) and across the Applied AI Solutions product portfolio to shape how models and agent frameworks are applied and ensure scientific decisions compose into a coherent system. • Deliver measurable business impact: Ensure research translates to customer outcomes: higher task accuracy, lower cost-per-action, faster time-to-production, measurable productivity for human-AI teams and the trust that lets enterprises scale agent workflows. • Raise the scientific bar: Establish rigor in experimentation evaluation and reproducibility. Mentor and grow senior scientists and engineers. Set the standard for applied science quality across the organization. • Advance the state of the art: Contribute to the external technical community through publications patents and open-source contributions that position AWS as the leader in the science of secure agent-computer interaction and human-AI teamwork. About the team 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. 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. 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. 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. 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.

The Models, Quantum, and Silicon (MQS) 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. We are looking to hire a Senior Applied Scientist to join our growing Software team. You’ll work closely with our partners on the control hardware development and quantum error correction theory teams to build a quantum control system capable of supporting the next generation of fault-tolerant workloads This requires someone who (1) has a strong desire to work within a team of scientists and engineers, and (2) demonstrates ownership in initiating and driving projects to completion. 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 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. Key job responsibilities - Contribute to the software/gateware runtime for our next-generation quantum control system - Build emulation tooling to enable exploring the requirements space of control systems for real-time quantum error detection and correction - Make opinionated decisions about engineering tradeoffs to inform our control hardware/software roadmap - Demonstrate thought leadership in FTQC by releasing open-source software and publishing research - Empower other scientists to actively contribute to the codebase through mentorship and documentation We are looking for candidates with strong engineering principles, a bias for action, superior problem-solving, and excellent communication skills. Working effectively within a team environment is essential. A day in the life The majority of your time will be spent on projects that extend the functional capabilities or performance of our internal control stack. This requires working backwards from the needs of our science staff in the context of our larger experimental roadmap. You will translate science and software requirements into design proposals balancing implementation complexity against time-to-delivery. Once a design proposal has been reviewed and accepted, you’ll drive implementation and coordinate with internal stakeholders to ensure a smooth roll out. Because many high-level experimental goals have cross-cutting requirements, you’ll often work closely with other engineers or scientists or on the team. About the team You will be joining the Software group within the MQS Center of Quantum Computing. Our team is comprised of scientists and software engineers who are building scalable software that enables quantum computing technologies.

Do you want to create intelligent, adaptable robots with global impact? The Vulcan Stow team (https://www.amazon.science/latest-news/how-amazon-robotics-researchers-are-solving-a-beautiful-problem) at Amazon Robotics builds high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans—at Amazon scale. We invent and deploy machine learning, optimization algorithms, and geometric reasoning models that empower robots to identify the best available placement opportunities, learn effective stow strategies, and continuously improve capacity utilization. Our mission is to deliver robust, real-time 3D scene understanding that drives downstream manipulation decisions - spanning semantic occupancy prediction, multi-view 3D reconstruction, depth estimation, and panoptic segmentation. We hire and develop subject matter experts in 3D computer vision, deep learning, and generative modeling, targeting high-impact algorithmic unlocks in scene completion, shape reasoning, and edge-optimized inference. We are seeking an experienced Applied Science Manager to lead the Perception team - a group of applied scientists and engineers pushing the frontier of 3D computer vision for robotics. You will drive technical vision using transformer-based architectures, generative 3D models, and scalable data pipelines to deliver sub-250ms perception outputs with the accuracy, robustness, and latency that production robots demand. Collaborating with cross-functional teams across match & affordances, motion planning, and fulfillment operations, you will ship models that run on real robots in real fulfillment centers. Key job responsibilities People Leadership: Prioritize being a great people manager - motivating, rewarding, and coaching your diverse team is the most important part of this role. Recruit and retain top talent in 3D computer vision, deep learning, and perception systems. Excel in day-to-day people and performance management tasks. Technical Vision: Set a vision for your team and create technical roadmaps focused on 3D scene understanding, semantic occupancy prediction, depth estimation, and multi-view fusion. Guide research, design, deployment, and evaluation of perception models - including encoder-decoder networks, query-based transformers, and generative architectures - that produce actionable 3D representations for downstream robot decision-making. Cross-functional Collaboration: Work closely with match & affordances, motion planning, hardware, and fulfillment teams to deliver integrated perception solutions that are robust to occlusion, clutter, and sensor noise. Partner with ML infrastructure teams on scalable training pipelines, pseudo-ground-truth data generation, and edge deployment optimization. Delivery Excellence: Implement best practices in applied research and software development. Manage project timelines, resources, and deliverables effectively. Keep technical skills current to contribute meaningfully to architecture decisions, model reviews, and inference optimization discussions. Problem Solving: Regularly participate in deep-dive troubleshooting exercises and drive technical post-mortem discussions to identify root causes of perception regressions, model failures, depth/segmentation misalignments, and latency degradations. A day in the life - Prioritize being a great people manager: motivating, rewarding, and coaching your diverse team is the most important part of this role. You will recruit and retain top talent and excel in people and performance management tasks. - Set a vision for the team and create the technical roadmap that deliver results for customers while thinking big for future applications. - Guide the research, design, deployment, and evaluation of complex computer vision and machine learning algorithms for contact-rich, cluttered, real-world manipulation problems. - Work closely with motion, hardware, and software teams to create integrated robotic solutions that are better than the sum of their parts. - Implement best practices in applied research and software development, managing project timelines, resources, and deliverables effectively. Amazon offers a full range of benefits for 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 Watch this video to learn more about Vulcan program in Amazon Robotics: https://www.amazon.science/latest-news/how-amazon-robotics-researchers-are-solving-a-beautiful-problem

Are you passionate about solving complex problems and protecting one of the world’s largest cloud platforms? The AWS Payments and Fraud Prevention team is looking for an innovative Applied Scientist to help keep AWS a safe and trusted environment for millions of customers worldwide. In this role, you will design, build, and deploy machine learning models that detect, prevent, and mitigate fraudulent activity across the AWS ecosystem. You will work with massive, real-world datasets, develop new detection strategies, and apply advanced and practical technologies to tackle ever-evolving threats. You will also explore Generative AI (GenAI) techniques to uncover new fraud patterns and strengthen our fraud defenses. At AWS, we support hundreds of thousands of businesses, powering billions of transactions every day. Fraudsters are constantly innovating — and so are we. If you enjoy thinking like a fraudster, building resilient defenses, and making a real-world impact, we invite you to join us and help shape the future of secure cloud computing. Key job responsibilities * Design, build, and deploy machine learning models to detect, prevent, and mitigate fraudulent activities across the AWS platform. * Analyze large-scale behavioral, transactional, and historical datasets to uncover fraud patterns and emerging threats. * Explore and apply GenAI techniques, including large language models (LLMs), synthetic data generation, and adversarial simulations to enhance fraud detection capabilities. * Collaborate closely with engineering, product, and operations teams to translate business needs into scalable technical solutions. * Experiment, prototype, and iterate on new detection strategies, algorithms, and evaluation metrics. * Continuously monitor model performance and improve robustness against adversarial behaviors and evolving fraud tactics. * Communicate findings and technical insights clearly and effectively to both technical and non-technical audiences. * Contribute to the broader fraud prevention strategy, driving innovation and best practices across the organization. About the team AWS Payments and Fraud Prevent is responsible for detecting & mitigating AWS account risks. You’ll be part of a team of Scientists, Analysts, and Technical & non-Technical Program Managers. The team’s goal is to identify and neutralize fraudsters from unauthorized access to legitimate AWS customers accounts. We have a formal mentor search application that lets you find a mentor that works best for you. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members.

Are you passionate about building machine learning systems that protect one the world's largest cloud platform? The AWS Payments & Fraud Prevention (P&FP) Science team is looking for a driven Applied Scientist to help safeguard AWS and its millions of customers from evolving fraud threats. In this role, you will design, build, and deploy end-to-end machine learning models that detect and prevent fraudulent activity. You will work with massive, real-world datasets across the AWS payments, signup and usage ecosystem, develop new detection strategies, and take models from concept to production. You will also apply Generative AI (GenAI) techniques to enhance fraud signal discovery and strengthen our detection capabilities. At AWS, we process billions of transactions every day for hundreds of thousands of businesses worldwide. Fraud patterns shift constantly and our defenses must stay ahead. If you enjoy owning problems end-to-end, shipping models that make real-time decisions at scale, and making a direct impact on customer trust and financial protection, we invite you to join us and help shape the future of fraud prevention at AWS. Key job responsibilities Design, build, and deploy end-to-end machine learning models and rules to detect, prevent, and mitigate fraudulent activities across the AWS payment and usage ecosystem. Source, extract, and analyze large-scale behavioral, transactional, and historical datasets to uncover fraud patterns and emerging threats. Apply hands-on expertise in statistical modeling, traditional machine learning, and analytics to identify and isolate issues across the fraud landscape. Explore and apply GenAI techniques, including large language models (LLMs) and synthetic data generation, to enhance fraud detection capabilities. Own the full model lifecycle — from data extraction and feature engineering through evaluation, productionalization, and deployment. Continuously monitor model and rule performance and improve robustness against adversarial behaviors and evolving fraud tactics. Experiment, prototype, and iterate on new detection strategies, algorithms, and evaluation metrics with a focus on rapid time-to-production. Collaborate closely with engineering, product, and operations teams to translate business needs into scalable technical solutions. Communicate findings and technical insights clearly and effectively to both technical and non-technical stakeholders at all levels. Contribute to the broader fraud prevention strategy, driving innovation and best practices across the organization. A day in the life You will have the opportunity to enhance our existing models and develop new ones that have a direct impact on the business from reducing financial losses to protecting customer accounts in real time. You will own your models end-to-end, from sourcing data and building features through evaluation and productionalization, and you will be expected to move quickly as fraud threats evolve. As part of this role, you will also support core fraud operations reviewing model outputs, tuning detection thresholds, and ensuring our mechanisms are performing as expected in production. This operational closeness to the data and to real fraud cases is what gives our scientists a unique edge: you will develop a deep, practical understanding of how fraud actually works, which directly sharpens the models and strategies you build. It is this combination of science and operational insight that makes our team's work so impactful. Your role will also allow you to leverage your customer-obsession skills by thoughtfully considering the user experience and ensuring it is not adversely affected by the mechanisms you design. You will explore new techniques, including Generative AI, to stay ahead of increasingly sophisticated adversaries. About the team Our team plays a crucial role in safeguarding secure and profitable business operations. Our mission is to position AWS as the most cost-effective and user-friendly cloud service provider by protecting legitimate customer experiences from the financial, operational, and reputational impacts of fraudulent activities. We develop services that prevent, detect, contain, and mitigate the actions of fraudulent and malicious users. As part of an analytics-driven team, you will leverage large-scale data to inform business decisions, respond to fraud, and automate decision-making at scale. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Diverse Experiences AWS 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. About 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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness. 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. 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.

Are you a scientist interested in pushing the state of the art in machine learning and recommendation systems? Are you interested in working on novel ideas that can positively impact millions of customers? Do you wish you had access to large datasets and tremendous computational resources? Answer yes to any of these questions and you will be a great fit for our team at Amazon. As an Senior Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for Personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Key job responsibilities - Using Amazon’s large-scale computing resources, you will ask research questions about customer behavior, build state-of-the-art models to optimize the shopping experience, and run these models directly on the retail website. - Develop AI solutions for Recommendation systems using Deep learning, LLMs, Reinforcement Learning, distillation, and Optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field;

Are you excited to figure out not just what is happening but why — and to help build a delivery business that's still taking shape? We're looking for a Data Scientist who thrives on ambiguity and wants to own measurement, modeling, and experimentation across how customers experience Amazon's drone-delivery service. Your work will span the full data-science toolkit: designing and analyzing experiments (A/B tests), deep-diving customer-experience issues to find root causes, building propensity and behavioral models, forecasting demand, and applying causal methods to understand what actually drives our metrics. You'll work with large, evolving operational and customer datasets; partner closely with data engineers, scientists, and business stakeholders; and translate rigorous analysis into clear, decision-ready recommendations. Because the business is early and moving fast, you'll help define the right problems as much as solve them — with real room to explore new methods and shape how we measure and improve as we scale. If you're a curious, collaborative problem-solver who's energized by turning complex, ambiguous data into insight and clear direction, we'd love to hear from you. Key job responsibilities - Design and execute data science solutions using a range of methodologies—including machine learning, statistical modeling, and generative AI techniques—to address business problems where the approach is not immediately clear. - Acquire, transform, and validate large, evolving operational and customer datasets dive deep to investigate anomalies and data quality; and partner with data engineers to bring models and metrics into production. - Design, run, and analyze experiments (A/B and quasi-experimental studies) to measure impact, size opportunities, and guide product and operational decisions. - Deep-dive customer-experience issues and metric movements to identify root causes — the why behind the what, including how our metrics and their drivers relate and translate findings into clear, actionable recommendations. - Communicate complex analyses to technical and non-technical audiences, earn the trust of senior leaders, and influence roadmap and prioritization decisions with your recommendations. - Own your workstream end-to-end, from problem definition through delivery and ongoing measurement partnering across data engineering, product, and business teams as the business scales. A day in the life You might start your morning reviewing model performance metrics before joining a working session with engineers to refine a data pipeline. After lunch, you could be prototyping a new machine learning approach, running experiments, and comparing results against baseline models. Later, you might present preliminary findings to business partners, translating statistical outputs into plain-language recommendations. You will regularly participate in team discussions, scientific reviews, and mentoring conversations that keep you learning and growing.

We’re pioneering frontier science solutions to detect and treat product quality issues and enhance post-order experience in Amazon. Our goal is to enhance support for our diverse seller community and foster improved outcomes for both sellers and consumers for broader Amazon ecosystem. We are looking for passionate innovators who are excited about technology, driven by customer experience, and eager to make a lasting impact on the industry. In this role, you'll collaborate with top-tier scientists, engineers, and technical program managers (TPMs) to drive innovation in GenAI foundation models, adapt Large language model to our domain, develop efficient tabular foundation model, innovate on behavior foundation model. You will lead the effort to leverage Amazon's large-scale computing resources to accelerate advances in GenAI and frontier ML solutions. If you’re enthusiastic about joining a dynamic and motivated team, this is your chance to be part of an exciting journey. Apply now and help us shape the future of seller support at Amazon! Key job responsibilities 1. Develop domain-specific foundation models. 2. Apply the domain-specific foundation model to product risk detection, seller interactions capturing, future seller behaviors prediction, and seller responses simulation across varied conditions. 3. Work with business and engineers to develop and deploy the solutions.

Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, Amazon's International Seller Services team has an exciting opportunity for you as an Applied Scientist. At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our International Seller Services team plays a pivotal role in expanding the reach of our marketplace to sellers worldwide, ensuring customers have access to a vast selection of products. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences for our customers and sellers. You will be part of a global team that is focused on acquiring new merchants from around the world to sell on Amazon’s global marketplaces around the world. The position is based in Seattle but will interact with global leaders and teams in Europe, Japan, China, Australia, and other regions. Join us at the Central Science Team of Amazon's International Seller Services and become part of a global team that is redefining the future of e-commerce. With access to vast amounts of data, cutting-edge technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way sellers engage with our platform and customers worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Please visit https://www.amazon.science for more information Key job responsibilities Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the international seller services domain. Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. Continuously explore and evaluate state-of-the-art NLP techniques and methodologies to improve the accuracy and efficiency of language-related systems. Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact.