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 |
|---|---|---|
| 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.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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| Senior Software Development Engineer - Generative AI, Neuron SDK Senior Software Development Engineer focused on Generative AI within Amazon's Annapurna Labs, specifically working with the Neuron SDK and ML chips (Inferentia and Trainium). The role involves building and applying AI agents to improve customer adoption of these chips, optimizing software solutions for performance, durability, cost, and security, and collaborating with cross-functional teams including compiler, hardware, and ML engineers. Experience in the Generative AI space is a hard requirement. | Serve | 7 |
| Software Development Engineer, JWO Software Development Engineer role on the AWS Solutions team, focusing on building and scaling the Machine Learning platform for Just Walk Out (JWO) Technology. The role involves developing algorithms for computer vision, image recognition, and machine learning within a distributed systems environment, with a focus on scaling ML platforms. | Serve | 7 |
| Sr. SDM, AI Inference Technology, Neuron SDK Senior Manager for AI Inference Technology, leading a team to build fundamental inference technology building blocks and libraries for AWS Neuron SDK, optimizing models for Trainium and Inferentia devices. Focuses on the full development life cycle of inference libraries, enabling customers to optimize LLMs, multimodal, and generative models. | Serve | 7 |
| Software Development Manager - ML Performance Tooling and Benchmarking, AWS Neuron, Annapurna Labs Manager III leading a team of compiler engineers to develop, deploy, and scale a compiler targeting AWS Inferentia and Trainium ML accelerators. The role involves technical leadership, innovation, and collaboration with AWS ML services teams to ensure the Neuron SDK meets customer needs for high performance, low cost, and ease of use. Deep knowledge of resource management, scheduling, code generation, and optimization is required. | Serve | 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 |