Currently tracking 1110 active AI roles, down 16% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).
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.
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 |
|---|---|---|
| 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 |
| 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 |
| 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 |
| 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 |
| 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. 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |