Amazon has 1472 active AI-related job listings. The company is heavily focused on roles within the "agents" stage, which accounts for 38% of its AI hiring, followed by "application" at 26%. Engineering is the dominant function, with 1172 positions. Over the last 30 days, Amazon has added 667 new AI roles, representing a 74% increase compared to the previous 30-day period. Frequent tech tags include agent_orchestration, model_serving, and multimodal.
Currently tracking 1110 active AI roles, down 16% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).
Amazon currently has 1573 active AI-related roles in our index. The most common open titles are: ML Data Associate-II (9), 2026 Applied Scientist Intern, Amazon University Talent Acquisition (8), AI Data Associate (Dutch) , Artificial General Intelligence Data Services (8), Software Development Engineer, AWS (8), Senior Delivery Consultant - Data , Professional Services, AWSI HCLS (7). Most positions are in Engineering and Research.
Amazon's active AI hiring is concentrated in: agents (41%), application (26%), serving infrastructure (13%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Amazon is hiring AI talent in: United States (1023 roles), Canada (59 roles), United Kingdom (47 roles), India (23 roles).
Job postings at Amazon most frequently mention: Machine Learning, Generative AI, Large Language Models (LLMs), Software Engineering, Agentic Systems.
In the past 30 days, Amazon has posted 696 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Sr Risk Manager, Amazon Business Payments & Lending The Sr. Risk Manager will drive the strategy and performance of lending portfolios within Amazon Business Payments & Lending. This role involves product management, data analytics, and portfolio strategy, with a unique focus on leveraging and shaping an AI Agent for portfolio management. Responsibilities include defining metrics, identifying trends, driving strategic initiatives, cross-functional leadership, data-driven innovation, and operational excellence, all while working with a generative AI tool to automate analysis and generate insights. | Agent | 7 |
| Sr. Software Development Manager - Compiler, AWS Neuron, Annapurna Labs The Sr. Software Development Manager will lead a team of compiler engineers developing, deploying, and scaling a compiler targeting AWS Inferentia and Trainium ML accelerators. This role involves deep knowledge of resource management, scheduling, code generation, and optimization for new instruction architectures, with a focus on delivering high-performance, low-cost ML inference and training solutions for AWS customers. |
| Serve |
| 7 |
| Data Scientist, SPX AI Lab, SPX Science The role focuses on applying advanced analytical, statistical, and machine learning techniques to improve Amazon's Selling Partner experience through a Generative AI-powered conversational assistant. Responsibilities include analyzing seller pain points, evaluating feature performance, designing measurement frameworks (A/B testing, causal inference), applying NLP and statistical modeling to unstructured data, and partnering with cross-functional teams to influence product roadmaps. The goal is to enhance the Selling Assistant by responding to seller feedback and implementing fixes in the GenAI solution. | Ship | 7 |
| Software Engineer- AI/ML, AWS Neuron Distributed Training - Performance Optimization Software Engineer focused on performance optimization for distributed training of large-scale AI/ML models (LLMs, multi-modal) on AWS Neuron accelerators. This involves tuning across the software stack, including collective communications, memory utilization, compiler optimizations, and kernel performance, working with PyTorch and JAX. | ServePost-train | 7 |
| Applied Scientist, Amazon Ads, Demand Forecasting & Guidance Applied Scientist role at Amazon Ads focusing on Generative AI, AI Agents, and large-scale ML for demand forecasting. Responsibilities include leading ML initiatives, developing and optimizing forecasting models, building and deploying ML models, designing A/B experiments, establishing scalable ML infrastructure, and researching innovative ML techniques. Requires 3+ years of model building experience, a PhD or Master's with 4+ years of experience in a related field, and programming experience in Java, C++, or Python. Preferred qualifications include experience with experimental design and deep learning frameworks. | ShipServe | 7 |
| ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs The role focuses on optimizing the performance of machine learning kernels for AWS's custom ML accelerators (Inferentia and Trainium) by developing and implementing high-performance compute kernels, optimizing compiler optimizations, and analyzing kernel-level performance. This involves working at the hardware-software boundary to ensure optimal performance for deep learning and GenAI workloads. | Serve | 7 |
| Software Development Engineer 2, Amazon Business Software Development Engineer 2 role on the Unified Risk Evaluation System team at Amazon Business, focusing on fraud prevention and risk management using machine learning and scalable systems to process billions of transactions globally. The team builds self-service capabilities for ML model experimentation and manages numerous risk use cases. | Ship | 7 |
| Software Development Manager - Compiler, AWS Neuron, Annapurna Labs Seeking a Software Engineering Manager to lead a team developing compiler optimization algorithms and deploying a new compiler for AWS custom hardware (Inferentia and Trainium chips). The role involves technical leadership, mentoring, and partnering with AWS ML services teams to improve deep learning model performance and productivity. | Serve | 7 |
| Sr Applied Scientist, Amazon Shipping Lead ML teams building large-scale forecasting and optimization systems for Amazon's global transportation network, impacting customer experience and cost. The role involves setting scientific direction, mentoring scientists, and delivering production-grade ML solutions at scale, using techniques like deep learning and reinforcement learning. | Ship | 7 |
| Software Development Engineer II, AI/ML Elastic Collectives - Annapurna Labs Software Development Engineer II at Amazon's Annapurna Labs, focusing on distributed AI/ML systems and collective operations for scaling AI across multiple accelerators and servers. The role requires strong C/C++ and Linux skills, with experience in embedded systems, high-speed networking, or HPC interconnects being valuable. This position is on the forefront of AI/ML, working with large-scale clusters and models within AWS's EC2 infrastructure. | Serve | 7 |
| Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs This role is for a Sr. Machine Learning Compiler Engineer III on the AWS Neuron team, focusing on the development and scaling of a compiler for ML accelerators. The role involves architecting and implementing features for a deep learning compiler stack that optimizes neural network performance on custom AWS hardware, integrating with frameworks like PyTorch and TensorFlow. The goal is to provide significant performance improvements for large-scale ML workloads. | Serve | 7 |
| Senior Applied Scientist, Amazon Industrial Robotics Senior Applied Scientist role focused on developing next-generation advanced robotics systems that combine AI, control systems, and mechanical design for automation at Amazon's scale. The role involves research and implementation of deep learning and LLMs for robotics, with a focus on simulation, physics-based modeling, and sim-to-real gap reduction. | Ship | 7 |
| Software Development Manager, Neuron Tools, Annapurna Labs Software Development Manager for AWS Neuron Tools team, responsible for leading engineers to develop and maintain high-performance monitoring and profiling tools for AI accelerators (Inferentia, Trainium). The role involves managing the full development lifecycle of the Neuron Profiler, ensuring scalability, reliability, and usability, and collaborating with cross-functional teams to optimize AI workloads. Experience with ML-specific profiler tools and performance analysis is required. | Serve | 7 |
| Applied Scientist, AWS Applied AI Solutions Applied Scientist role focused on developing Agentic AI solutions using Gen AI within AWS Applied AI Solutions. The role involves extending scientific techniques, inventing new ones, and delivering components into production with high quality standards. Requires experience in building models for business applications and strong programming skills. | Agent | 7 |
| Applied Scientist II, Amzn Shipping-Prd & Tech Applied Scientist II at Amazon Shipping focused on building production-quality ML models for transportation logistics. This role involves improving package movement planning and execution by addressing challenges in cost auditing, financial data quality, delivery delay prediction, and first-mile shipping cost reduction. The scientist will utilize various ML paradigms, ensure scalability across regions, and contribute to the ML community through publications and mentorship. | Agent | 7 |
| Sr. Manager, Applied Science, Marketing Measurement and Performance Science (MAPS) Senior Manager, Applied Science for Marketing Measurement and Performance Science (MAPS) at Amazon. This role focuses on building scalable ML and causal inference solutions to estimate marketing effectiveness and provide insights for marketing teams. It involves leading a team of scientists, developing end-to-end causal inference models, and influencing multi-billion dollar investment decisions. The role requires expertise in ML/DL, statistics, economics, and handling large datasets at scale, with a focus on delivering data-driven solutions that impact business strategy and customer behavior. | Ship | 7 |
| Manager, Software Development, Alexa AI, Alexa AI India Manager, Software Development for Alexa AI in India, focusing on speech and language solutions. The role involves leading a team to pioneer ML tools and processes, build scalable applications, and contribute to system architecture and technical vision for Alexa AI. | Serve | 7 |
| Software Development Engineer, Amazon Ads Software Development Engineer role focused on applying Generative AI and LLMs to enhance Amazon Ads, improving ad retrieval, allocation, and recommendations for a personalized shopping experience. The role involves building large-scale distributed systems and data pipelines, collaborating with scientists and product managers, and driving operational excellence. | AgentServe | 7 |
| Applied Scientist, Private Brands Discovery Applied Scientist role focused on designing and building machine learning solutions for customer discovery of Amazon's Private Brands. The role involves end-to-end project management from ideation to launch, with a strong emphasis on causal ML, deep learning, and deploying models to production. The goal is to drive customer awareness and product discovery, impacting Amazon's own brands and contributing to broader discovery solutions across the company. | Ship | 7 |
| Sr. Applied Scientist, Pricing Science The role involves applying deep learning, neural networks, and transformer architectures to price prediction and forecasting problems within Amazon's Pricing Optimization group. It focuses on developing and deploying ML models at scale to improve pricing and promotion strategies, requiring collaboration with product, engineering, and science teams. | Ship | 7 |
| Software Development Engineer, ML Systems, Annapurna Labs Software Development Engineer focused on building and applying AI agents to simplify and accelerate customer adoption of AWS Neuron ML chips (Trainium and Inferentia). The role involves working with external and internal customers to identify obstacles and opportunities for accelerating adoption, and transforming service performance, durability, cost, and security. | Serve | 7 |
| Applied Scientist Intern, International Technology, 2026 Beijing The Applied Scientist Intern will work on improving Amazon's product search service by designing and integrating machine learning models using TB-scale data. The role involves balancing business metrics and response times, and requires a PhD student in Computer Science, AI, ML, or related fields with experience in ML experiment design, statistical analysis, and coding. | ServeData | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition Internship role focused on machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. The intern will own the design and development of end-to-end systems, write technical white papers, create roadmaps, and drive production-level projects. Collaboration with scientists and other interns is expected, with opportunities to design new algorithms and models. | Ship | 7 |
| Machine Learning Engineer, AWS Neuron Inference, Annapurna ML Machine Learning Engineer role focused on optimizing and tuning inference performance for AWS Neuron accelerators, specifically for large language models (LLMs) and other key ML model families. The role involves developing and performance tuning building blocks for the distributed inference library, ensuring high performance and efficiency on Trn2 and Trn3 servers. Requires experience with LLM inference optimization, kernels, Python, PyTorch, or JAX. | Serve | 7 |
| Senior Applied Scientist, Amazon Stores Economics & Science (SEAS) Senior Applied Scientist role focused on applying optimization, statistical learning, and algorithm development to solve complex supply chain and marketplace problems within Amazon's Stores organization. The role involves leading science initiatives from research to production, designing algorithms for mechanism design, and influencing technical strategy. | Ship | 7 |
| Sr. AI Platform Data Engineer, Ring Decision Science, Ring Decision Science This role is for an AI Platform Builder, a Data Engineer focused on developing Platforms and Agentic AI solutions. The role involves designing, implementing, and maintaining data pipelines and platforms that power AI/ML initiatives, using AI for code generation, optimization, and building AI-native self-service data platforms. It emphasizes prompt-driven development and creating self-improving systems. | AgentData | 7 |
| Software Development Manager, ML Accelerators, AWS Neuron, Annapurna Labs Software Engineering Manager to lead a team focused on machine learning compiler design and development for AWS Neuron, driving optimization techniques, hardware bring-up, and influencing pre-silicon design decisions to accelerate ML infrastructure. | Serve | 7 |
| Machine Learning Performance Engineer, Annapurna Labs This role focuses on optimizing the performance of the AWS Neuron software stack, which supports Generative AI and ML workloads on AWS's custom ML accelerators (Inferentia and Trainium). The engineer will analyze ML workloads, develop high-performance kernels, enhance the Neuron SDK, and collaborate with compiler, frameworks, and hardware teams to maximize end-to-end performance. Responsibilities include instruction scheduling, memory management, parallelism, kernel optimization, and compiler enhancements, with a focus on ML inference and training performance. | Serve | 7 |
| Sr. Data Scientist, Amazon Pay Data Products Senior Data Scientist at Amazon Pay to lead innovation in machine learning and artificial intelligence solutions, focusing on multi-agent systems and Generative AI applications. The role involves end-to-end ML project leadership, MLOps pipeline development, and deployment of ML solutions, with a secondary focus on inference infrastructure. | AgentServe | 7 |
| Senior Language Engineer, Artificial General Intelligence - Data Services This role focuses on developing diverse datasets for training and evaluating AI models, utilizing synthetic data generation, model-based generation, and human-in-the-loop approaches. The Senior Language Engineer will define data creation strategies, lead complex data collections, and analyze large datasets. They will also build tools for data analysis and creation, and collaborate with scientists to evaluate AI model performance. | Data | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on designing and implementing state-of-the-art solutions for complex business problems, potentially leading to production-level projects and technical white papers. Collaboration with scientists and other interns is expected. | Ship | 7 |
| Senior Software Development Engineer, Luna Gen AI Senior Software Development Engineer role focused on building Gen AI native games and gameplay experiences, and enhancing internal team productivity through agentic solutions. The role involves architecting, developing, and operating infrastructure for proprietary and third-party models, building intelligent agents, and optimizing AI solutions for performance and cost. It also includes leading internal GenAI adoption and ensuring enterprise-grade security and responsible AI. | AgentServe | 7 |
| Sr. Applied Scientist, Last Mile Science The Sr. Applied Scientist role in Amazon Logistics focuses on optimizing last-mile delivery operations through the development and application of machine learning models and algorithms. The role involves estimating costs, improving metrics, developing scalable processes, and working with technology teams to build new tools and systems that impact customer experience and delivery efficiency. It requires a PhD or equivalent experience in a quantitative field and strong analytical and program management skills. | Ship | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on designing and implementing state-of-the-art solutions for complex problems, potentially leading to production deployment and publication. | Ship | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on designing and developing end-to-end systems, writing technical white papers, creating roadmaps, and driving production-level projects. Opportunity to design new algorithms and models, potentially publish work at top-tier conferences. | Ship | 7 |
| 2026 Data Scientist Internship , Amazon University Talent Acquisition MS student internship focused on building and deploying machine learning models for Amazon's business problems, with potential for worldwide scale. The role involves working with large datasets and cloud technology, and defining metrics for customer satisfaction. | Ship | 7 |
| Post-Silicon Systems Validation Engineer, Annapurna Labs This role focuses on validating next-generation machine learning accelerators for AWS, covering the entire vertical stack from silicon to system. The engineer will develop and execute validation strategies, conduct hands-on bring-up and debug, and collaborate with various teams to ensure the quality and performance of AI/ML accelerators used in AWS data centers for AI training and inference. | Serve | 7 |
| Senior SDE, Luna Gen AI Senior Software Development Engineer to join the Gen AI & Strategic Initiatives team for Amazon Luna. The role involves architecting and building next-generation tools and platform infrastructure to support proprietary and third-party AI models, enabling Gen AI native games and enhancing internal team productivity through agents. Responsibilities include driving platform architecture, building scalable API infrastructure, launching cross-functional agents, optimizing performance, supporting developer experience, implementing observability, designing throttling systems, ensuring security and compliance, and driving operational excellence. | Agent | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship focused on research in machine learning, deep learning, generative AI, LLMs, speech, robotics, computer vision, optimization, OR, quantum computing, automated reasoning, or formal methods. The role involves designing and developing end-to-end systems, writing technical papers, creating roadmaps, and driving production-level projects. Experience with publications at top-tier conferences and solving business problems with ML/data mining/statistical algorithms is preferred. | Post-train | 7 |
| Sr Software Dev Engineer, Machine Learning, Sponsored Products and Brands Ads Response Prediction This role focuses on enhancing the scalability, automation, and efficiency of large-scale training and real-time inference systems for Amazon Ads' Sponsored Products and Brands. The engineer will pioneer LLM inference infrastructure and work with applied scientists to optimize ML models and infrastructure, implementing end-to-end solutions. The team builds advanced ML models and infrastructure, from training to inference, including LLM-based systems, to deliver relevant ads. | ServePost-train | 7 |
| Machine Learning - Compiler Engineer , AWS Neuron, Annapurna Labs Software Engineer role focused on building and optimizing the AWS Neuron compiler for custom AI chips (Inferentia and Trainium). The role involves transforming ML models (PyTorch, TensorFlow, JAX) into optimized code for these accelerators, with a focus on large language models and diffusion models. Requires strong software engineering skills, particularly in C++, and experience with compiler technologies is preferred. | Serve | 7 |
| Sr. Manager, Applied Science, Sponsored Products and Brands This role leads science and engineering for AI-powered sponsored product ads in offsite shopping experiences, focusing on generative AI and large-scale ML solutions. The goal is to revolutionize advertising by bridging human creativity with AI, impacting ad creation, optimization, performance analysis, and customer insights. The role involves extending campaigns to reach customers off-store and on third-party sites, working with external and internal partners, and driving results at scale with a GenAI-first approach. It requires significant experience in building large-scale ML/AI solutions and people management. | Ship | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech, robotics, vision, optimization, OR, quantum computing, automated reasoning, or formal methods. Focus on designing and developing end-to-end systems, writing technical white papers, creating roadmaps, and driving production-level projects. Opportunity to design new algorithms and models, deploy solutions into production, and potentially publish work. | Post-train | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech, robotics, computer vision, optimization, OR, quantum computing, automated reasoning, or formal methods. Focus on inventing, designing, and implementing state-of-the-art solutions for complex problems. Will own design and development of end-to-end systems, write technical white papers, create roadmaps, and drive production-level projects. Opportunity to design new algorithms and models, and deploy them into production, potentially publishing work at top-tier conferences. | Ship | 7 |
| Sr. Post-Silicon Systems Software Validation Engineer, Annapurna Labs This role focuses on validating next-generation machine learning accelerators for AWS, covering the full vertical stack from silicon to system. The engineer will be responsible for developing validation strategies, executing test plans, debugging hardware and software, and collaborating with cross-functional teams to ensure the quality and performance of AI/ML accelerators used in AWS data centers. | Serve | 7 |
| Principal Applied Scientist, Personalization Principal Applied Scientist role focused on building next-generation personalized shopping experiences at Amazon using LLMs, transformer models, and large-scale ranking systems. The role involves innovating features and models, leading science innovation, driving the science roadmap, and mentoring scientists. It aims to create a personalized shopping experience tailored to customer intent and product catalog understanding. | ShipAgent | 7 |
| Sr. Software Development Engineer, Annapurna Labs Senior Software Development Engineer at Amazon Annapurna Labs focused on leading a technical team to develop profiling and optimization tools for the Neuron ML accelerators fleet. The role involves working with hardware and software teams to identify bottlenecks and provide recommendations for improving performance of large ML workloads, including custom kernels. | Serve | 7 |
| Sr. AI ML Consultant, Tech & Industry, Tech & Industry This role involves designing, implementing, and managing AWS solutions, with a focus on AI/ML and GenAI models. The consultant will act as a trusted advisor to customers, providing technical expertise and guidance on cloud journeys, including migrating to AWS and deploying production-grade ML solutions. The role requires hands-on experience with building, validating, and deploying GenAI models, as well as serving ML models through real-time APIs. | AgentServe | 7 |
| Software Development Manager, LLM Inference Model Enablement, Neuron SDK Software Development Manager to lead a team optimizing LLMs for inference on AWS custom accelerators (Neuron, Trainium, Inferentia). Focus on improving model enablement speed, experience, usability, and quality through features, infrastructure, tools, and automation. Requires strong background in LLM architectures, performance optimizations, and distributed inference. | Serve | 7 |
| Research Scientist, Last Mile Science Research Scientist role focused on applying machine learning and data-driven solutions to optimize Amazon's last-mile delivery logistics. The role involves building ML models for business applications, developing scalable processes, and making strategic, data-driven decisions to improve customer experience and operational efficiency within the logistics network. | Ship | 7 |
