Careers

Are you passionate about helping customers achieve business transformation through AI? Do you want to lead forward-deployed teams that embed directly into the enterprise and unlock real business outcomes? And are you ready to operate as a general manager across engineering, science, and commercial strategy in the fastest-moving space in AI and infrastructure? The AWS Generative AI Innovation Center (GenAIIC) is on a mission to accelerate enterprise AI transformation across global customers going from beyond isolated use cases to holistic, C-suite-sponsored initiatives that reshape how organizations operate. We combine deep AI expertise across science, strategy, and business transformation. We start with the customer's most critical operational challenges and work backwards, and deploy multidisciplinary teams that embed with the customer, prove impact in 45-day sprints, and expand across the enterprise. We are a fast-moving, entrepreneurial team that values leaders who can operate across technical depth and commercial breadth. As the Head of AI Transformation, GenAIIC APJC Geo, you will own the end-to-end success of AI transformation engagements across the Asia Pacific, Japan, and Greater China region. You will lead a team of ML engineers, AI scientists, and AI strategists who work alongside customers to architect and deliver AI solutions that move and stay in production, realizing value. You will regularly engage with CFOs, CIOs, and C-suite executives — selling transformation, not technology. You must bring a GM mindset: equal fluency in engineering, applied science, go-to-market, and customer delivery. You are ready to roll up your sleeves alongside the team — whether that means scoping an agentic AI architecture, presenting to a board, or operationalizing a repeatable delivery motion across geos. You will partner with customers, AWS Sales, AWS service teams, AWS industry teams and AWS Professional Services delivery teams to meet the specific needs of the customer, and extend that use to other customers. Key job responsibilities Lead a high-performing, multidisciplinary team of ML engineers, AI scientists and strategists. Own the regional engagement pipeline — identify, qualify, and land C-suite-sponsored AI transformation programs with enterprise customers. Guide the team in designing, building, and deploying production AI solutions. Drive a land-and-expand motion: prove value in focused sprints, then scale across business units with executive sponsorship. Operate as a GM — balancing technical delivery, talent development, commercial outcomes, and operational excellence. Advise and influence customers on enterprise AI strategy, including architecture decisions, organizational readiness, and change management. Drive adoption of AWS generative AI services by delivering AI expertise and developing repeatable transformation playbooks. Develop new strategies and mechanisms to address evolving customer needs while increasing business velocity and impact for AWS. Influence product roadmap with service teams based on customer feedback. A day in the life Diverse Experiences AWS 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. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.

The NASC & TOM Science team owns Operations Research, Machine Learning, and AI projects across the North America Sort Center (NASC) and Transportation Operations Management (TOM) planning and operations organizations. We turn complex network, labor, and capacity problems into deployed models that drive multi-million-dollar planning decisions every day. As a Data Scientist II, you will own the end-to-end Machine learning Operation cycle: Design, build, and ship machine learning and/or optimization models that directly shape Amazon's middle miles planning decisions. You will own end-to-end delivery — from problem framing with business partners, through modeling and validation, to deployment in internal model hosting platform and integration with downstream planning tools. You will work on problems such as: - Long- and short-horizon forecasting - Network and capacity optimization - GenAI / agentic systems - Defect prevention and adaptive planning You will partner closely with Engineering, Product, Engineering, and stakeholders to translate ambiguous operational pain points into measurable model outcomes. Key job responsibilities - Design and implement complex ML and optimization solutions (forecasting, MIP/LP, simulation, Deep learning / foundation model); - Drive end-to-end delivery of scalable models — from data exploration and feature engineering through training, evaluation, deployment, and post-launch monitoring; - Develop new modeling patterns and analytical frameworks for forecasting (multivariate, hierarchical, causal-DAG, model-chaining) and optimization; - Build robust model validation, backtesting, and monitoring pipelines; identify and eliminate sources of leakage, bias, and silent failure; - Define and own model performance metrics (e.g., WAPE) tied to business outcomes; - Partner with Data Engineering and Software Development to productionize models and define I/O contracts, packaging, and model CI/CD; - Excellent communication to present findings, tradeoffs, and recommendations clearly to stakeholders and senior leadership.

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 frontier 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 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. As a Senior Research Engineer embedded in our science team, you'll be instrumental in transforming innovative research into high-performance production systems. You'll collaborate directly with scientists to build and optimize large-scale transformer models for robotics applications. In this role, you'll balance deep technical optimization work with strategic input on model architecture decisions, ensuring our innovative robotics models are designed with performance in mind from the ground up. You'll leverage PyTorch and NVIDIA's acceleration stack and other compilation techniques to tackle ambitious performance targets, working at the intersection of large language models and real-world robotics applications. Key job responsibilities - Design, implement, and optimize distributed training systems that scale across thousands of GPUs and nodes for large-scale training workloads. - Develop high-performance optimizations to maximize throughput and efficiency. - Develop reusable frameworks and libraries to improve training reproducibility, reliability, and scalability for new model architectures. - Establish standards for reliability, maintainability, and security, ensuring systems are robust under rapid iteration. - Collaborate with researchers to influence model architectures for optimal hardware utilization - Develop comprehensive benchmarking frameworks to measure and optimize model performance A day in the life In this role, you will: - Optimize transformer blocks using custom CUDA kernels and TensorRT optimization techniques - Partner with scientists to analyze model architectures and propose efficiency improvements - Implement and benchmark various optimization strategies for large-scale models - Debug performance bottlenecks using NVIDIA profiling tools - Participate in technical discussions about new model architectures with the science team - Manage pre/post training runs and continue improve system stability and throughput - Prototype new acceleration approaches using emerging compilation frameworks

As a Data Scientist on our team, you will leverage advanced analytics and machine learning to protect our cloud infrastructure from security threats. You'll develop and deploy sophisticated anomaly detection models, predictive algorithms, and real-time analysis systems that identify and help automate the mitigation of cyber threats across Amazon's infrastructure. Your expertise in statistical analysis, machine learning, and big data processing will be crucial in building scalable security solutions. You'll collaborate with software engineers, security engineers, and fellow data scientists to: - Analyze large-scale security data using statistical methods and data mining techniques - Create automated systems for real-time pattern recognition and risk assessment - Build data pipelines and ETL processes to handle massive security datasets - Translate complex analytical findings into actionable security insights We use the full power of AWS technologies, including Amazon SageMaker, EMR, and other ML/AI services to protect every AWS customer from security threats. Experience with Python and a strong background in statistical analysis and machine learning are essential. We're looking for a new teammate who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers. We want someone who will help us amplify the positive & inclusive team culture we've been building. We understand that life is dynamic and we have a flexible work environment that enables individuals to adjust their work schedule to accommodate personal needs. Our team is distributed, though most of the team is located in Maryland and Virginia. We generally keep core business hours of 10:00 AM EST - 3:00 PM EST, while allowing flexibility as needed. At AWS Security, it’s not about clocking hours, it’s about delivering results. On-Call Responsibility This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice. Key job responsibilities - Running experiments to assess potential risk of security responses. - Expanding our existing LLM agent pipelines - Analyzing post mortems to understand what data signals could have prevented the occurence About the team 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.

Employer: Amazon Development Center U.S., Inc. Position: Applied Scientist II - AMZ27057.1 Location: Boston, MA Multiple Positions Available: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. (40 hours / week, 8:00am-5:00pm, Salary Range $161803 - $193200) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

The Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers on a mission to develop a fault-tolerant quantum computer. Throughout your internship journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied science, where your contributions will shape the future of Quantum Computing and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available for Quantum Research Science and Applied Science Internships in Santa Clara, CA and Pasadena, CA. We are particularly interested in candidates with expertise in any of the following areas: superconducting qubits, cavity/circuit QED, quantum optics, open quantum systems, superconductivity, electromagnetic simulations of superconducting circuits, microwave engineering, benchmarking, quantum error correction, fabrication, etc. Key job responsibilities In this role, you will work alongside global experts to develop and implement novel, scalable solutions that advance the state-of-the-art in the areas of quantum computing. You will tackle challenging, groundbreaking research problems, work with leading edge technology, focus on highly targeted customer use-cases, and launch products that solve problems for Amazon customers. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. About the team 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. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

The Amazon Experience and Technology (AET) team provides technology and services that Amazon’s entire global workforce, over 1M people and counting, relies on every day. We operate at the intersection of technology and empathy, reimagining HR conventions. Our customers are our colleagues—and we’re innovating for them. As a survey scientist you will you will design and carry out surveys to address business questions; analyze survey and other forms of data with regression models; perform weighting and multiple imputation to reduce bias due to nonresponse. You will conduct methodological and statistical research to understand the quality of survey data. You will work with economists, engineers, and computer scientists to select samples, draft and test survey questions, calculate nonresponse adjusted weights, and estimate regression models on large scale data. You will evaluate, diagnose, understand, and surface drivers and moderators for key research streams, including (but are not limited to) attrition, engagement, productivity, inclusion, and Amazon culture. Key job responsibilities * Design a scalable global content development and validation strategy to drive more effective decisions and improve the employee experience across all of Amazon * Conduct psychometric and econometric analyses to evaluate integrity and practical application of survey questions and data * Identify research streams to evaluate how to mitigate or remove sources of measurement error * Drive effective collaborations across multi-disciplinary research and product teams * Manage full life cycle of large-scale research programs (Develop strategy, gather requirements, manage and execute)

Amazon Ads is building Ads Agent, an AI-powered agent that understands advertiser intent, reasons over campaign strategy, and executes across the full Amazon Ads portfolio. If you want to work at the frontier of agentic AI and large language models while directly impacting a multi-billion dollar business, this is your team. We are seeking an experienced Applied Scientist passionate about building intelligent agents that reason, plan, and act across complex advertising workflows. Ads Agent is an AI agent that simplifies how advertisers plan, launch, and optimize campaigns. Powered by AI, Ads Agent works alongside advertisers to automate time-consuming tasks, like identifying targeting segments, adjusting pacing across hundreds of campaigns, and generating SQL queries for advanced analytics. It also provides data-driven recommendations and simplifies analysis—all while providing transparency and control. With a broad mandate to experiment and innovate, we need applied scientists to define and build the future of advertising. Key job responsibilities - Design, build, and evaluate agentic systems that plan multi-step workflows, invoke tools, and take autonomous actions across Amazon Ads products on behalf of advertisers. - Define evaluation frameworks and benchmarks for agent reliability, correctness, safety, and advertiser satisfaction. - Analyze agent behavior through deep data analysis and rigorous A/B experimentation to identify failure modes, measure effectiveness, and derive business insights. - Partner with engineers, product managers, and UX designers to ship end-to-end agent experiences that are scalable, efficient, and reliable at Amazon scale. About the team We are a small, fast-moving team building a unified AI-native interface to all of Amazon Advertising. We sit at the intersection of large language models, agentic AI, and one of the world's most complex advertising ecosystems. If you want to shape how millions of advertisers interact with Amazon Ads, come build with us.

Amazon is seeking a Language Data Scientist to join the Alexa International science team as domain expert. This role focuses on expanding analysis and evaluation of conversational interaction data deliverables. The Language Data Scientist is an expert in conversation assessment processes, working closely with a team of skilled machine learning scientists and engineers, and is a key member in developing new conventions for relevant annotation workflows. The Language Data Scientist will be own unique data analysis and research requests that support the training and evaluation of LLMs and machine learning models, and the overall processing of a data collection. Key job responsibilities To be successful in this role, you must have a passion for data, efficiency, and accuracy. Specifically, you will: - Own data analyses for customer-facing features, including launch go/no-go metrics for new features and accuracy metrics for existing features - Handle unique data analysis requests from a range of stakeholders, including quantitative and qualitative analyses to elevate customer experience with speech interfaces - Lead and evaluate changing dialog evaluation conventions, test tooling developments, and pilot processes to support expansion to new data areas - Continuously evaluate workflow tools and processes and offer solutions to ensure they are efficient, high quality, and scalable - Provide expert support for a large and growing team of data analysts - Provide support for ongoing and new data collection efforts as a subject matter expert on conventions and use of the data - Conduct research studies to understand speech and customer-Alexa interactions - Collaborate with scientists and product managers, and other stakeholders in defining and validating customer experience metrics

We are seeking a Senior Applied Scientist to join the Alexa Availability team within Alexa Excellence. This role leads the research and development of machine learning and statistical models that power Alexa's reliability at massive scale — serving hundreds of millions of customers globally. The ideal candidate will tackle complex, ambiguous problems spanning time series multivariate modeling, statistical anomaly detection, LLM-based operational intelligence, and adaptive threshold systems. They will design production-grade ML solutions, establish rigorous evaluation frameworks, and ensure AI systems are grounded, reliable, and free from systematic bias — leveraging techniques such as RAG, confidence scoring, knowledge graph integration, and counterfactual testing. This scientist will partner with engineers, product managers, and operations leaders to translate scientific innovation into production systems that directly impact Alexa's availability worldwide. They will drive the scientific agenda for the team, mentor fellow scientists, and influence the broader Alexa Excellence organization through technical leadership and cross-team collaboration. Key Focus Areas: Anomaly detection and predictive failure modeling Cross-service correlation and LLM-driven operational intelligence Production ML at the intersection of large-scale distributed systems and applied science Model reliability, hallucination mitigation, and grounding for operational AI Key job responsibilities As a Senior Applied Scientist on the Alexa Availability team, you will lead the research and development of machine learning and statistical models that power Alexa's reliability at scale. You will work on some of the most complex and ambiguous problems in the space — from time series multivariate modeling and statistical anomaly detection to LLM-based operational intelligence and adaptive threshold systems. A day in the life You will design and implement production-grade ML solutions, establish rigorous model evaluation frameworks, and ensure our LLM-powered systems are grounded, reliable, and free from systematic bias. You will apply techniques such as Retrieval-Augmented Generation (RAG), confidence scoring, knowledge graph integration, and counterfactual testing to ensure our AI systems make trustworthy operational decisions at scale. You will partner closely with software engineers, product managers, and operations leaders to translate scientific innovation into production systems that directly impact Alexa's availability for customers worldwide. You will drive the scientific agenda for your team, mentor fellow scientists, and influence the broader Alexa Excellence organization through your technical leadership and cross-team collaboration. About the team The Alexa Excellence team is at the heart of delivering a world-class Alexa experience to hundreds of millions of customers globally. Within Alexa Excellence, the Alexa Availability team is responsible for ensuring Alexa is always on, always responsive, and always reliable. We own the systems, signals, and science that detect, diagnose, and drive resolution of availability issues at scale — before customers ever notice. We are building the next generation of intelligent availability solutions powered by machine learning, large language models, and advanced statistical modeling. Our work spans anomaly detection, predictive failure modeling, cross-service correlation, and LLM-driven operational intelligence — all operating at the scale and reliability bar that Alexa demands. We operate at the intersection of large-scale distributed systems, applied machine learning, and operational excellence, and we are looking for scientists who can bring both deep technical rigor and a bias for production impact.