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 |
|---|---|---|
| Machine Learning Compiler Engineer The Machine Learning Compiler Engineer will work on the Amazon Neuron team to develop and scale a deep learning compiler stack for Amazon's custom ML accelerators (Inferentia and Trainium). This role involves optimizing neural network models for inference and training performance, integrating with ML frameworks, and contributing to the software stack that enables large-scale ML workloads. The engineer will be involved in pre-silicon design and bringing new features to market. | 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. | Agent |
| 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 |
| Principal Product Manager, Fleet Demand, EU Fleet Supply Chain Principal Product Manager for Amazon Logistics' EU Fleet Demand team. This role involves defining fleet requirements, driving procurement decisions, and optimizing fleet capacity using statistical modeling, machine learning, and AI-powered optimization. The goal is to ensure efficient delivery capacity while optimizing utilization and cost. The role requires cross-functional collaboration with data engineering, science, and tech teams to build and evolve planning systems like FORCE. | Data | 7 |
| C/C++ Hardware / Software Co-Design SDE, Machine Learning Acceleration Systems This role involves developing bare metal firmware for custom ASIC-based ML Accelerator chips, focusing on hardware/software co-design for machine learning acceleration systems. The engineer will work on the firmware that drives neural network model execution on custom silicon, collaborating with hardware design teams. While no prior ML knowledge is required, the role is core to enabling ML infrastructure. | Serve | 7 |
| 2026 Applied Science Internship - United States - Master's Student Science Recruiting Master's student internship focused on applying machine learning, NLP, computer vision, automated reasoning, or robotics to design and develop end-to-end systems for Amazon Science. The role involves working with large datasets, implementing systems, and potentially deploying solutions into production. | Ship | 7 |
| MTS, Data Infra , AGI The role focuses on building and maintaining a Spark-based infrastructure for processing large multimodal datasets critical for machine learning research, specifically for state-of-the-art agents within the AGI Autonomy organization. It involves data extraction, transformation, and creating tooling for researchers, with a secondary focus on agent development. | DataAgent | 7 |
| Senior Applied Scientist, Sponsored Products and Brands Senior Applied Scientist role focused on developing and launching end-to-end AI solutions, specifically recommendation systems leveraging generative models, for Amazon's Sponsored Products and Brands advertising platform. The role involves defining science vision, designing experiments, and collaborating with engineering and product teams to improve advertiser and shopper experiences. | 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 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 |
| Zappos Data Scientist III, Zappos/Shopbop Catalog Engineering Data Scientist III on the Shopbop/Zappos Catalog Tech team responsible for designing and implementing ML approaches to improve product catalog data quality, automate data capture and classification, and integrate ML models into production systems. The role involves working with computer vision and NLP, and influencing product decisions through data-driven insights. | ShipPost-train | 7 |
| Sr. MLE, Prime Video - Personalization and Discovery Senior Machine Learning Engineer role focused on developing and launching AI solutions for Prime Video's recommendation and personalization systems, utilizing deep learning, GenAI, and reinforcement learning. The role involves end-to-end ownership, experimental design, and collaboration with cross-functional teams to impact millions of customers. | Ship | 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 |
| Applied Scientist II, Translation Services Applied Scientist II role focused on designing and developing LLM-based machine learning solutions for language translation services at Amazon. The role involves applying expertise in LLMs, conducting data analysis, and evaluating new modeling techniques to improve translation accuracy and efficiency for millions of customers across 130+ locales. The team is leveraging Gen AI to build scalable solutions from scratch. | Post-train | 7 |
| Applied Science Manager, Sponsored Products and Brands Ads Response Prediction Manage a team of Applied Scientists, ML Engineers, and Software Development Engineers to develop science and engineering roadmaps for SPB ads CTR prediction using ML and Gen AI solutions. The role involves hiring, developing talent, and staying informed about scientific publications and industrial research trends. The team focuses on personalized shopping experiences through ML and GenAI solutions for response prediction and session-level understanding to optimize ad serving, targeting, sourcing, and bidding. | ShipPost-train | 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.System Development Engineer, AGI Infrastructure The AGI team is seeking engineers to develop and maintain multi-modal and multi-lingual LLMs using scalable training and inference systems. The role involves deeply understanding technology landscapes, evaluating new technologies, and driving operational excellence. Key responsibilities include leading the design and automation of GenAI training compute infrastructure, mentoring engineers, identifying performance bottlenecks, and working with core AWS services, CI/CD pipelines, and Kubernetes. | Serve | 7 |
| Applied Scientist, Central Machine Learning Applied Scientist role focused on building and deploying machine learning models for Amazon's consumer businesses. Responsibilities include analyzing large datasets, designing and evaluating scalable models, and collaborating with engineering teams for real-time implementation. The role emphasizes end-to-end ownership of business problems and optimizing operations through ML. | ShipServe | 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 |
| ML Compiler Engineer , AWS Neuron, Annapurna Labs The AWS Neuron team is seeking ML Compiler Engineers to optimize deep learning and GenAI workloads on AWS custom ML accelerators (Inferentia/Trainium). This role involves analyzing and optimizing system-level performance across the entire technology stack, from frameworks to runtime, and designing/implementing compiler optimizations. The position requires a passion for performance analysis, distributed systems, and machine learning, with a focus on improving the performance capabilities of the AWS Neuron SDK. | 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 |
| Language Engineer, Artificial General Intelligence - Data Services This role focuses on developing diverse datasets for training and evaluating AI models, utilizing methods like synthetic data generation, model-supported generation, and human-in-the-loop collections. The Language Engineer will collaborate with cross-functional teams to innovate and advance the state-of-the-art in AI model evaluation and training. | Data | 7 |
| Senior Applied Science Manager, Selling Partner Growth Senior Applied Science Manager to lead AI initiatives for seller growth at Amazon. The role involves developing scientific models for customer demand, selection identification, and prioritization signals. It also includes leading the development of next-generation agentic experiences for sellers, integrating insights into products like ABA and OX, and driving business impact through ML/LLM solutions. | AgentPost-train | 7 |
| Senior Systems Engineer - Autonomous Drone Perception, Prime Air Senior Systems Engineer for Amazon Prime Air's autonomous drone perception systems. This role involves translating operational requirements into system specifications, bridging ML algorithms with flight control, and ensuring perception systems meet aviation certification standards. The focus is on the integration and validation of ML-based perception for safe autonomous flight. | Agent | 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 |
| Sr. MLE, Prime Video - Personalization and Discovery Senior Machine Learning Engineer role at Amazon Prime Video focused on developing and launching AI solutions for recommendation and personalization systems. The role involves end-to-end ownership of ML models, including design, implementation, experimentation (A/B testing), and deployment for millions of customers. It requires experience with large-scale ML systems and recommendation systems. | Ship | 7 |
| Software Development Engineer, ML Systems, Annapurna Labs Software Development Engineer focused on ML Systems within Amazon Annapurna Labs, working on AWS Neuron software for ML chips (Inferentia and Trainium). The role involves building and applying AI agents to accelerate customer adoption of this technology, optimizing performance, durability, cost, and security for AWS customers. | Serve | 7 |
| Senior ML Kernel Performance Engineer The Annapurna Labs team at Amazon is seeking a Senior ML Kernel Performance Engineer to optimize deep learning and GenAI workloads on Amazon's custom ML accelerators (Inferentia and Trainium). This role involves crafting high-performance kernels, pushing the boundaries of AI acceleration at the hardware-software boundary, and collaborating with customers to enable their models. The engineer will work on compiler optimizations, performance analysis, and contribute to future architecture designs. | Serve | 7 |
| Sr. ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs Senior ML Kernel Performance Engineer for AWS Neuron SDK, focusing on optimizing deep learning and GenAI workloads on custom ML accelerators (Inferentia, Trainium). The role involves designing and implementing high-performance compute kernels, optimizing performance at the hardware-software boundary, and collaborating with customers and internal teams on model enablement and acceleration. | Serve | 7 |
| Applied Scientist II, Prime Video - Personalization and Discovery Science Applied Scientist II at Amazon Prime Video focusing on personalization and discovery science. The role involves developing ML models for recommendation and search systems using deep learning, online learning, and optimization methods. It requires staying updated with the latest modeling techniques, publishing research findings, and applying advanced approaches like foundation models to solve cold-start problems and discover niche customer interests. The scientist will work on highly scalable page personalization solutions and collaborate with engineers and product managers. | Ship | 7 |
| Sr. Applied Scientist, Prime Video - Personalization and Discovery Science This role focuses on developing and launching end-to-end AI solutions for Prime Video's search and discovery systems, utilizing deep learning, GenAI, and reinforcement learning. The scientist will design and conduct experiments, collaborate with engineers and product managers, and publish research findings. The role is within the consumer domain, aiming to improve customer experience for millions of users. | Ship | 7 |
| Senior Machine Learning Compiler Engineer Senior Machine Learning Compiler Engineer responsible for the ground-up development and scaling of a deep learning compiler stack for Amazon's ML accelerators (Inferentia and Trainium). The role involves architecting and implementing business-critical features, optimizing neural net models for custom hardware, and integrating with ML frameworks like PyTorch and TensorFlow. | Serve | 7 |
| Software Development Engineer III, Annapurna Labs Software Development Engineer III at Amazon Annapurna Labs, focusing on building and applying AI agents to simplify and accelerate customer adoption of AWS Neuron ML chips (Inferentia and Trainium). The role involves solving complex technical problems, designing and implementing innovative software solutions, and working with external and internal customers to identify adoption obstacles and opportunities in the Generative AI space. | Agent | 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 Software Development Engineer, Ring AI Senior Software Development Engineer to join Ring's AI Team, focusing on cloud services for machine learning operation pipelines that handle large-scale data and enable rapid model optimization. The role involves building and scaling platforms for AI model development and deployment, collaborating with cross-functional teams, and ensuring the delivery of robust backend systems. | ServePost-train | 7 |
| Senior Software Development Engineer, Ring AI Senior Software Development Engineer to join Ring's AI Team, focusing on cloud services for machine learning operation pipelines that handle large-scale data and enable rapid model optimization. The role involves building and scaling platforms for AI model development and deployment, collaborating with cross-functional teams, and ensuring the delivery of robust backend systems. | ServePost-train | 7 |
| Sr. Applied Scientist, JP Manga Sr. Applied Scientist role focused on developing AI prototypes and concepts for the JP Manga business, involving research, design, and training/tuning of NLP and Computer Vision models for applications like translation, summarization, extraction, boundary detection, image understanding, and generation. The role emphasizes tangible business impact and collaboration with product managers and engineers, with opportunities for publication. | Post-train | 7 |