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 |
|---|---|---|
| Principal Applied Scientist, ML Codesign This role is for a Principal Applied Scientist focused on the joint optimization of model compression and silicon architecture for AI inference accelerators. The scientist will define the hardware-aware compression roadmap, own the optimization of compression algorithms with hardware, and influence silicon architecture decisions. The goal is to ship advanced compression techniques and large models on next-generation accelerators, bridging the gap between model accuracy and hardware efficiency. | ServePost-train | 9 |
| Senior Applied Scientist This role focuses on developing and deploying ML-based perception systems for robots using radar and thermal imaging, fusing this data with traditional sensors to enable operation in challenging conditions. The primary output is the deployed perception system (L3), with significant work also in developing and refining the ML models themselves (L2). |
| ServePost-train |
| 9 |
| Sr Applied Scientist, ML Codesign, Edge AI Platform This role focuses on the joint optimization of model compression and silicon architecture for Amazon's edge and cloud inference accelerators. The scientist will define the hardware-aware compression roadmap, own the optimization of compression algorithms with hardware, and represent applied science in silicon architecture reviews. The goal is to ship advanced quantization and distillation techniques in production for large language models. | ServePost-train | 8 |
| Senior Applied Scientist, Amazon Ads, Demand Tech , Amazon Advertising, Demand Tech Senior Applied Scientist role focused on building and improving deep learning models for response prediction and incrementality in Amazon's advertising platform. The role involves end-to-end ownership from design to production deployment, with a strong emphasis on low-latency, high-throughput inference and online A/B testing. Collaboration with engineers on serving infrastructure and mentoring junior scientists are also key aspects. | ServePost-train | 8 |
| Senior Software Development Engineer, AWS Mantle Senior Software Development Engineer to build and scale the distributed inference engine for Amazon Bedrock, powering enterprise access to foundation models globally. The role involves designing, building, and operating high-performance systems for ML inference at massive scale, focusing on request routing, load balancing, model lifecycle management, and performance optimization across AWS regions. | Serve | 8 |
| Sr GenAI Infra Specialist SA, AWS WWSO Startup Senior GenAI Infrastructure Specialist SA for AWS WWSO Startup team, focusing on AI infrastructure for model training and inference optimization. The role involves advising startup customers on hardware, optimization techniques, and deploying strategies for large-scale AI workloads on AWS. | ServePost-train | 8 |
| Software Development Engineer - AI/ML, Amazon Neuron, Multimodal Inference Software Development Engineer focused on optimizing and accelerating deep learning and GenAI workloads on AWS's custom ML accelerators (Inferentia and Trainium) through the AWS Neuron SDK. This role involves architecting, implementing, and tuning distributed inference solutions, focusing on performance optimization (latency and throughput) from system level to framework level (PyTorch, JAX). The engineer will work on low-level optimizations, system architecture, and ML model acceleration, collaborating across hardware, compiler, runtime, and framework teams. | Serve | 8 |
| Machine Learning Engineer, Alexa AI Machine Learning Engineer for Alexa AI focused on LLM training, production deployment, and inference optimizations. Will collaborate with Applied Scientists and other MLEs to leverage Amazon's data and computing resources for Generative AI solutions. Responsibilities include investigating design approaches, prototyping, evaluating technical feasibility, processing data, scaling ML models, and delivering high-quality software in an Agile environment. Experience with PyTorch/JAX, vLLM, SGLang, TensorRT, and developing large model hosting platforms is preferred. | ServePost-train | 8 |
| Senior Manager, AI Red Team, Threat Operations Senior Manager to lead an AI Red Team focused on security research and offensive operations targeting AI systems, infrastructure, and emerging threats. The role involves building and leading a team, establishing the AI offensive security research program, driving Red Team operations, and partnering with stakeholders to protect AI offerings and customer trust. | ServeData | 8 |
| ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs The role focuses on optimizing ML kernel performance for AWS Neuron SDK on custom ML accelerators (Inferentia and Trainium). It involves designing and implementing high-performance compute kernels, analyzing and optimizing kernel-level performance, implementing compiler optimizations, and collaborating with customers and internal teams to enable and optimize ML models. The work is at the hardware-software boundary, combining deep hardware knowledge with ML expertise. | Serve | 8 |
| Software Engineer II- AI/ML, AWS Neuron Software Engineer II role focused on optimizing and enabling deep learning and GenAI workloads on AWS custom ML accelerators (Inferentia and Trainium) by developing and enhancing the AWS Neuron SDK. This involves working across the stack from frameworks like PyTorch/JAX to hardware-software boundaries, optimizing ML compilers, runtimes, and high-performance kernels for inference and training. The role requires strong software development skills in Python/C++, system-level programming, ML knowledge, and collaboration with various teams to ensure optimal performance for customers. | ServePost-train | 8 |
| 2026 Annapurna Labs at AWS, Early Career (US) - Machine Learning Systems & Silicon Innovation This role focuses on building and optimizing the systems and silicon that power AI infrastructure, including custom ML accelerator chips, distributed training systems, and compiler optimizations for ML training. It's an early career role within Annapurna Labs at AWS, aiming to accelerate AI development. | Serve | 8 |
| Applied Scientist, AWS Neuron Science Team Applied Scientist role focused on enhancing AWS software stack for Trainium and Inferentia accelerators, involving ML/RL for kernel/code generation, ML compiler techniques, system robustness, and efficient kernel development. Collaborates with customers and engineering teams to optimize ML systems and adoption. | ServePost-train | 8 |
| Software Development Engineer, AI/ML, AWS Neuron, Model Inference Software Development Engineer focused on optimizing and enabling AI/ML model inference on AWS's custom hardware accelerators (Inferentia and Trainium), working across the stack from frameworks like PyTorch/JAX to hardware-specific optimizations and kernel development. | Serve | 8 |
| Sr. Software Engineer- AI/ML, AWS Neuron Apps Senior Software Engineer role focused on optimizing and deploying large AI models (LLMs, vision generative AI) on AWS's custom AI accelerators (Inferentia, Trainium). The role involves architecting distributed inference solutions, optimizing performance from high-level frameworks to hardware implementations, and developing tools for LLM accuracy and efficiency. It bridges ML frameworks (PyTorch, JAX) with AI hardware, focusing on inference performance and scaling. | Serve | 8 |
| Senior Software Development Engineer, AI/ML, AWS Neuron, Model Inference Senior Software Development Engineer role focused on optimizing and enabling AI/ML model inference on AWS's custom hardware accelerators (Inferentia and Trainium) through the Neuron SDK. The role involves system-level optimizations, performance tuning for latency and throughput, building infrastructure for model onboarding, and collaborating across hardware, software, and framework teams to ensure optimal performance for customers running large language models and other GenAI workloads. | Serve | 8 |
| Software Development Engineer AI/ML, Inference Serving, AWS Neuron Software Development Engineer to lead and architect next-generation model serving infrastructure for generative AI applications on AWS Inferentia and Trainium accelerators, focusing on performance, reliability, and scalability of inference serving systems. | Serve | 8 |
| Software Engineering Manager, ML Kernel Performance, AWS Neuron, Annapurna Labs The Annapurna Labs team at AWS is seeking an Engineering Manager to lead a team focused on optimizing ML kernel performance for AWS Neuron, their custom ML accelerators (Inferentia and Trainium). The role involves designing and implementing high-performance kernels, optimizing compiler and runtime performance, and working closely with customers to enable their ML models. This position operates at the hardware-software boundary, combining deep hardware knowledge with ML expertise to accelerate deep learning and GenAI workloads. | Serve | 8 |
| Software Development Engineer, AI/ML, AWS Neuron, Model Inference Software Development Engineer focused on optimizing and enabling AI/ML model inference on AWS's custom hardware accelerators (Inferentia and Trainium), working across the stack from frameworks like PyTorch/JAX to hardware-specific optimizations and kernel development. | Serve | 8 |
| SDE II, ML Infra Services, Annapurna Labs Software Engineer to lead the development of machine learning tools to run, optimize, and analyze machine learning workloads on AWS Neuron ML accelerators. Focus on ML infrastructure platform, capacity management, workload scheduling, and fleet orchestration. | Serve | 7 |
| Software Development Engineer, Health & Wellness, Health Tech Software Development Engineer role focused on architecting and implementing ML systems for health initiatives, integrating genomic, proteomic, and clinical data. The role involves building high-throughput pipelines, low-latency inference services for biological foundation models, and productionizing ML models for tasks like neoantigen prediction, with a strong emphasis on collaboration with researchers and biologists in an early-stage environment. | ServePost-train | 7 |
| Sr. Systems Development Engineer (AWS Generative AI & ML Servers), AWS HW Engineering This role focuses on building and operating AWS cloud infrastructure for AI training and inference, specifically targeting generative AI and large language models. The engineer will be responsible for designing, delivering, and optimizing server hardware and software systems to enable high performance and scalability for AI/ML workloads, with a focus on price-performance improvements. The role involves creating automation through agentic workflows and implementing AI-driven tools to enhance engineer productivity and influence AI implementation and core architecture. | Serve | 7 |
| Software Development Engineer, WHS Data-Tech Software Development Engineer role focused on building and deploying AI and computer vision systems for workplace safety at Amazon. The role involves designing, developing, and maintaining production services, optimizing data pipelines, integrating ML model outputs, and collaborating with applied scientists to productionize models. It emphasizes end-to-end ownership from data ingestion to edge deployment and operational maintenance. | ServePost-train | 7 |
| Software Development Engineer, WHS Data-Tech Software Development Engineer to build AI and computer vision systems for workplace safety, focusing on real-time inference, ML model deployment at the edge, and integrating ML outputs into internal tools. The role involves end-to-end software development, from data ingestion to production services. | ServePost-train | 7 |
| Principal PMT - Personalization ML Platform, Prime Video Personalization & Discovery The Principal PMT will drive the vision, strategy, and execution of a Machine Learning platform and infrastructure for Prime Video, powering personalization, discovery, and customer/content intelligence at a global scale. This role owns the strategy and roadmap for foundational platforms across Data, ML, and Measurement, enabling teams to rapidly build, experiment, and productionize ML solutions. Key responsibilities include defining the multi-year vision for ML platform and infrastructure, developing data platform strategy, building end-to-end ML tooling, supporting large-scale model training and real-time inference, defining feature store strategy, owning the developer experience for ML builders, enhancing the measurement platform, influencing senior leadership, and driving adoption of platform capabilities. | ServeData | 7 |
| Software Development Manager , EC2 Nitro This role leads a performance engineering group focused on optimizing ML infrastructure for EC2, covering diverse workloads like LLMs and multimodal models. The responsibilities include building and managing a team, driving architectural decisions, developing performance measurement infrastructure, and establishing regression coverage across the ML systems stack from low-level optimization to serving layers. | Serve | 7 |
| Software Development Manager, Worldwide Returns & ReCommerce This role is for a Software Development Manager on the Worldwide Returns & ReCommerce team at Amazon. The team builds AI and machine learning infrastructure for global reverse logistics, focusing on automating decision-making, maximizing financial recovery, and optimizing processing efficiency. The manager will lead teams in developing and deploying NLP, Computer Vision, and Classical ML models, as well as the associated infrastructure for model hosting, grading pipelines, and low-latency inference. | ServeData | 7 |
| Software Development Engineer III, Unified Intelligent Matching Systems (UIMS) Software Development Engineer III role focused on building and owning end-to-end large-scale distributed systems and AI/ML-powered applications for Amazon's product catalog. The role involves designing, implementing, and operating systems for product identity, matching, and relationship management, leveraging AI/ML solutions including multimodal LLMs, embedding-based systems, and agentic systems. Key responsibilities include leading architecture decisions, building and optimizing inference infrastructure, and partnering with Applied Scientists to productionize ML research. | ServeAgent | 7 |
| Sr. Software Development Engineer, Amazon Robotics Manipulation Senior Software Development Engineer role focused on building the intelligence layer for Amazon Robotics manipulation workcells. This involves designing, building, and operating distributed systems for work selection, data processing, ML lifecycle management, and predictive modeling. The role operates across the full ML and data lifecycle, impacting millions of packages and directly influencing fulfillment cost. | ServeData | 7 |
| Software Development Engineer, Data Analytics Integration AI and Platform Excellence Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows within Amazon's AWS Utility Computing organization. The role involves designing, developing, and optimizing AI/ML systems, collaborating with data scientists, and contributing to the full software development lifecycle. | Serve | 7 |
| Software Development Engineer, Data Analytics Integration AI and Platform Excellence Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows within Amazon's AWS Utility Computing organization. The role involves designing, developing, and optimizing AI/ML systems, collaborating with data scientists, and contributing to the full software development lifecycle. | Serve | 7 |
| Sr. Delivery Consultant - AI/ML, AWS Professional Services This role focuses on designing, implementing, and deploying GenAI and ML applications and models on AWS for customers. It involves providing technical guidance, gathering requirements, and advising on model training and deployment strategies, with a strong emphasis on AWS AI/ML services. | ServePost-train | 7 |
| Software Development Engineer, Amazon Search Autocomplete and Navigation AI Software Development Engineer for Amazon Search Autocomplete and Navigation AI. This role focuses on building next-generation mission understanding models and data collection frameworks, integrating models into large-scale, real-time production systems, and analyzing data to optimize system design and model performance. The position involves developing scalable data pipelines, designing and executing experiments, and managing ML initiatives. | ServeAgent | 7 |
| Senior Machine Learning Engineer, Sponsored Products and Brands Relevance Senior Machine Learning Engineer responsible for building and owning real-time ML serving systems for ad selection in Sponsored Products and Brands at Amazon. The role involves driving technical direction, designing scalable pipelines, optimizing model performance, and mentoring engineers, operating at massive scale with strict latency SLAs. It touches on deep learning, NLP, LLMs, and distributed systems, impacting shopper experience and advertiser ROI. | ServeAgent | 7 |
| Software Development Engineer, Data Integration AI and Platform Excellence (APEX) Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows at Amazon. The role involves designing, developing, and optimizing systems, collaborating with data scientists, and contributing to the full software development lifecycle. Requires experience with ML/LLM fundamentals and optimization of model execution. | Serve | 7 |
| Software Dev Engineer, Machine Learning Compilers Software Development Engineer focused on building the compiler infrastructure and software stack for custom neural accelerator silicon designed for edge AI capabilities. The role involves optimizing deep learning workloads, model quantization, and compression for efficient execution on hardware with limited memory, ultimately enabling large AI models to run on edge devices. | Serve | 7 |
| Research Engineer, Prime Video - Content Understanding Research Engineer role focused on building experiment frameworks, infrastructure, and deployment packages for Generative AI models within Prime Video. Responsibilities include managing GPU clusters, containerizing models, and developing monitoring pipelines for production deployment. The role supports applied scientists and involves end-to-end ownership of model training and deployment. | ServePost-train | 7 |
| Delivery Consultant- GenAI/ML & Data Science, Professional Services, AWS Industries This role focuses on designing, implementing, and managing GenAI and ML solutions on AWS for customers. The consultant will provide technical guidance, collaborate with stakeholders on model training and deployment strategies, and act as a trusted advisor on emerging technologies. The role emphasizes using AWS AI/ML services and involves working with customers to achieve their business outcomes. | ServePost-train | 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 work on hardware and software validation, ensuring performance, accuracy, and reliability of ML accelerators used in AWS data centers. Responsibilities include developing validation strategies, executing test plans, debugging hardware and software issues, and collaborating with cross-functional teams. | Serve | 7 |
| Sr. System Development Engineer, High-Performance Accelerator Servers for AI/ML This role is for a Senior System Development Engineer focused on high-performance accelerator servers for AI/ML at AWS. The engineer will be responsible for designing, delivering, and operating next-generation infrastructure for AI training and inference, focusing on performance, efficiency, and scalability. The role involves deep technical understanding of the full stack from hardware to software, systems debugging, and leading complex projects. | Serve | 7 |
| Delivery Consultant- GenAI/ML & Data Science, Professional Services, AWS Industries This role focuses on designing, implementing, and managing GenAI and ML solutions on AWS for customers. The consultant will provide technical guidance, collaborate with stakeholders on model training and deployment strategies, and act as a trusted advisor on emerging technologies. The role requires experience in hosting and deploying GenAI/ML solutions, including pre-processing, training, fine-tuning, and inference. | ServePost-train | 7 |
| Delivery Consultant- GenAI/ML & Data Science, Professional Services, AWS Industries This role focuses on designing, implementing, and managing AWS GenAI/ML solutions for customers, providing technical guidance, and acting as a trusted advisor. It involves working with customers to understand their needs and proposing effective strategies for model training, building, and deployment, with a strong emphasis on using AWS AI/ML services. | ServePost-train | 7 |
| Post-Silicon Systems Validation Engineer, Annapurna Labs This role focuses on validating next-generation machine learning accelerators for AWS cloud infrastructure, covering the entire vertical stack from silicon to system. The engineer will be responsible for developing validation strategies, executing test plans, conducting hands-on bring-up and debug, and validating ML accelerator performance using real-world workloads. The role requires collaboration with various engineering teams and a strong understanding of computer architecture and ML fundamentals. | Serve | 7 |
| Senior Video Compression Development Engineer, AWS Elemental, Elemental Video Engine Senior Software Development Engineer focused on video compression, responsible for writing code to process customer video and metadata. The role involves working on video technologies like VVC, AV1, HEVC, AVC, high dynamic range video, and enhancement filters. A key aspect is utilizing ML and Generative AI to solve new problems, improve video quality, enable new use cases, and enhance compute performance of video processing. The engineer will also design and implement improved video filters and contribute to home-grown video encoders. | Serve | 7 |
| Professional Services III AMZ13646.13 This role focuses on building and deploying scalable ML/AI solutions within AWS, leveraging Big Data, AppDev, or DevOps experience. It involves close collaboration with Data Scientists and Data Engineers to deliver end-to-end solutions for customers, utilizing ML frameworks, algorithms, and cloud technologies. | ServeData | 7 |
| Sr Solutions Architect, Annapurna ML This role is for a Sr. Solutions Architect focused on AWS Machine Learning accelerators (Inferentia and Trainium). The individual will work with customers to develop and deploy Deep Learning models on these accelerators, acting as a trusted advisor and thought leader. Responsibilities include designing architectures, owning PoCs, driving adoption through technical engagements, and sharing best practices. The role bridges customer needs with engineering roadmaps and involves creating technical content for various audiences. | Serve | 7 |
| Delivery Consultant - AI/ML, Professional Services - AWS Industries This role focuses on designing, implementing, and deploying GenAI and ML applications for customers on AWS. It involves providing technical guidance, gathering requirements, and supporting model training, building, and deployment strategies. The role requires experience with AWS AI/ML services and hosting/deploying ML solutions, with a preference for deep learning experience. | ServePost-train | 7 |
| Delivery Consultant - AI/ML, Professional Services - AWS Industries This role focuses on designing, implementing, and managing AI/ML solutions on AWS for customers, with a strong emphasis on deploying these solutions. The consultant provides technical guidance, collaborates on model training and deployment strategies, and acts as a trusted advisor on AI/ML trends. The role requires experience in software development, cloud architecture, and specifically hosting/deploying GenAI/ML solutions. | ServePost-train | 7 |
| Delivery Consultant - AI/ML & Data Science, Professional Services - AWS Industries This role focuses on designing, implementing, and managing AWS solutions for customers, with a specific emphasis on GenAI and ML applications. The consultant will provide technical guidance, gather requirements, and propose strategies for model training, building, and deployment, acting as a trusted advisor on industry trends and emerging technologies. The role involves hands-on experience with deploying GenAI/ML solutions on AWS. | ServePost-train | 7 |
| Delivery Consultant- GenAI/ML & Data Science, Professional Services, AWS Industries This role focuses on designing, implementing, and managing GenAI and ML applications and models on AWS for customers. The consultant will provide technical guidance, collaborate with stakeholders on model training and deployment strategies, and act as a trusted advisor on emerging technologies. Experience with hosting and deploying GenAI/ML solutions is required. | ServePost-train | 7 |