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 1109 active AI roles, down 11% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).
Amazon currently has 1575 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), Senior Delivery Consultant - Data , Professional Services, AWSI HCLS (8), Software Development Engineer, AWS (8). 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 (1022 roles), Canada (59 roles), United Kingdom (49 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 732 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Amazon Industrial Robotics - Applied Scientist II Intern / Co-op - 2026, Amazon Industrial Robotics This role focuses on developing next-generation advanced robotics systems by combining AI, control systems, and mechanical design for automation at Amazon's scale. The intern will contribute to research bridging theoretical advancements and practical implementation in robotics, focusing on areas like dexterous manipulation, locomotion, and human-robot interaction, leveraging deep learning and LLMs. | Ship | 8 |
| Applied Science Manager III, RBKS AI Manager for an Applied Science team focused on innovating AI features for Ring and Blink cameras, combining computer vision and generative AI for home security. The role involves leading the team in developing and productizing advanced CV and GenAI models, driving technical strategy for privacy-preserving solutions, and ensuring delivery of high-quality science artifacts for customer-facing products. |
| ShipPost-train |
| 8 |
| Principal Applied Scientist, Sponsored Products and Brands Principal Applied Scientist role focused on developing and deploying generative AI solutions for Amazon's Sponsored Products and Brands advertising platform. The role involves defining science vision, building ML/LLM models for advertiser and shopper experiences, optimizing campaign performance, and leading scientific rigor. Requires strong ML, LLM, and GenAI expertise with experience in production systems and digital advertising. | ShipPost-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. Manager, Applied Science, Sponsored Products and Brands Senior Manager role leading a team of Applied Scientists and Engineers to develop and deploy generative AI solutions for Amazon's Sponsored Products and Brands advertising platform, focusing on multi-lingual and multi-modal applications to drive growth in non-US markets. | Ship | 8 |
| SDE- ML Engineer, Frontier AI Robotics Machine Learning Systems Engineer for Frontier AI Robotics team, focusing on building and optimizing distributed training infrastructure for large-scale deep learning and transformer models. Role involves engineering scalable, high-performance systems for AI research and applications, with a focus on robotics, multimodal perception, and manipulation strategies. Requires strong software development, ML infrastructure, and deep learning framework expertise. | Data | 8 |
| AI Platform Data Engineer, Ring Decisions Sciences Platform AI Platform Data Engineer responsible for designing, building, and maintaining data pipelines, curated datasets for AI/ML consumption, and AI-native self-service data platforms using an AI-first development methodology. The role emphasizes leveraging AI at every layer of the data stack, including using AI agents for code optimization, building AI-powered platforms for AI models, and deploying intelligent agents for data accessibility. Experience with Gen AI enhanced development pipelines, agentic workflows, and prompt engineering is mandatory. | DataAgent | 8 |
| Senior Applied Science Manager, Amazon Sponsored Products & Brands Lead a team to invent and build the SPB-Agent, a GenAI platform transforming retail-media advertising for Amazon advertisers. This agent will act as an intelligent advisor integrated into Amazon Ad Console and Seller/Vendor portals, using conversational interfaces and deep reasoning to help advertisers discover growth opportunities, optimize campaigns, and execute strategies at scale. | Agent | 8 |
| Applied Scientist III, RBKS AI The RBKS AI team at Amazon is seeking Applied Scientists to innovate AI features for Ring and Blink cameras, focusing on the intersection of computer vision, generative AI, and ambient intelligence. The role involves productizing research into advanced computer vision and multimodal GenAI models for video understanding, object detection, and real-time applications, with an emphasis on privacy-preserving, efficient fine-tuning, and on-device/in-cloud inference. The goal is to ship AI solutions that enhance home security for millions of customers. | ShipPost-train | 8 |
| Senior Applied Scientist , RBS Tech This role focuses on designing and deploying GenAI, NLP, and Computer Vision solutions to enhance customer experience and automate operations within Amazon's retail business. It involves developing novel ML models for task automation, text and image processing, and anomaly detection, with a strong emphasis on multi-modal LLM agents and retrieval systems. | AgentPost-train | 8 |
| Applied Scientist The AWS Neuron Science Team is seeking scientists to enhance their software stack for ML accelerators (Trainium and Inferentia). The role involves working with customers to identify adoption barriers, collaborating with engineering teams on solutions, and advancing ML systems. Key areas include AI for Systems (kernel/code generation), ML Compiler techniques, System Robustness, and Efficient Kernel Development. | Serve | 8 |
| Senior Applied Scientist, Translation Services Senior Applied Scientist role focused on applying advanced NLP and LLM techniques to improve machine translation quality and pipeline efficiency for Amazon's e-commerce platform. The role involves architecting and implementing scalable ML solutions, driving data analysis, and pioneering modeling techniques for translation quality assessment and optimization. The scientist will also serve as an expert in LLM applications for translation and mentor team members. | Post-train | 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 |
| Sr. Applied Scientist, SSG Science This role focuses on optimizing and fine-tuning Generative AI models for edge platforms, working closely with custom ML hardware. The scientist will train custom models, analyze deep learning workloads, and collaborate with cross-functional teams to build ML-centric solutions for consumer devices. The role also involves publishing research and presenting at ML conferences. | Post-trainServe | 8 |
| Senior Applied Scientist, LLM Code Agents, Kiro Science Senior Applied Scientist role focused on advancing LLM code intelligence through reinforcement learning and post-training methodologies, with a strong emphasis on research, publication, and deploying these models into production systems for developers. | Post-trainAgent | 8 |
| Applied Scientist II, Strategic Account Services (SAS) Applied Scientist II role focused on developing and deploying sophisticated AI solutions for Amazon's Strategic Account Services (SAS) organization, leveraging deep learning, LLMs, and advanced ML techniques to improve seller operations and internal consultancy. The role involves end-to-end development from research to production, including architecting recommendation and optimization systems, pioneering applications of foundation models, and conducting rigorous A/B experiments. | ShipServe | 8 |
| Principal Applied Scientist, Advertiser Growth, Amazon Sponsored Products & Brands This role leads the development of generative AI applications for advertisers, focusing on agentic experiences for recommendations and guidance. It involves fine-tuning, reinforcement learning, and preference optimization, with a strong emphasis on creating customer-facing products and mentoring AI talent. | AgentPost-train | 8 |
| Software Engineer- AI/ML, AWS Neuron Software Engineer role focused on building and tuning distributed training solutions for AWS Inferentia and Trainium accelerators, specifically for large language models and other ML model families. The role involves working with PyTorch, Jax, XLA, and the Neuron compiler/runtime to maximize performance and efficiency on AWS Trainium. | PretrainServe | 8 |
| Sr. SDE- ML Data Infrastructure, Frontier AI Robotics Senior Software Development Engineer focused on ML Data Infrastructure for Frontier AI Robotics at Amazon. The role involves building and maintaining scalable data infrastructure, designing dataset management systems, developing visualization tools, and implementing advanced data filtering techniques to support cutting-edge AI robotics research. Collaboration with science teams is key, requiring both infrastructure development and hands-on technical contribution to data preparation. | Data | 8 |
| Research Scientist, SSG Science Research Scientist role focused on developing and optimizing Generative AI models for edge devices, involving model compression techniques, custom ML hardware, and theoretical understanding of deep learning and information theory. The role involves co-authoring research papers and collaborating with cross-functional teams. | ServePost-train | 8 |
| Robotics - Applied Scientist II Intern / Co-op - 2026 (Robotics, Manipulation, Perception, Motion Planning, Autonomous Mobile Robots, Computer Vision, Machine Learning, Controls, and more) This role is for a PhD student intern/co-op focused on robotics research, specifically in areas like manipulation, perception, motion planning, and autonomous mobile robots. The role involves applying machine learning, computer vision, and potentially LLMs to solve real-world robotics problems, with a focus on developing research prototypes and seeing them through from concept to working prototype. The work touches on data collection/preparation for training and research. | AgentData | 8 |
| Sr. Applied Science , AWS Agentic AI This role focuses on building next-generation models for intelligent automation within AWS Agentic AI. The scientist will develop innovative solutions for complex problems, focusing on areas like autonomous agents, API orchestration, planning, large multimodal models (especially vision-language), reinforcement learning, and sequential decision making. The role involves partnering with technology and business teams, utilizing extensive data and computational resources, and collaborating with engineers. There's an expectation to publish findings at peer-reviewed conferences. | Agent | 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 |
| Sr. Manager Applied Science, MLA Lead a team of scientists to research and prototype Machine Learning applications, focusing on Agentic AI and LLM solutions for seller experience, trust, and safety. The role involves designing and implementing large-scale, end-to-end business solutions and influencing technical strategy. | Agent | 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 |
| Senior Applied Scientist, Last Mile Delivery Automation Senior Applied Scientist role focused on developing and deploying machine learning models for Amazon's autonomous delivery systems, specifically in perception, prediction, and decision-making for autonomous vehicles. The role involves designing algorithms, leading research, transforming concepts into production, creating evaluation frameworks, and collaborating with engineering teams. | AgentServe | 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 |
| Software Engineer II - AI/ML, AWS Neuron, LLM Inference, AI/ML, AWS Neuron, Model Inference Software Engineer II role focused on optimizing LLM inference performance on AWS custom ML accelerators (Inferentia and Trainium) using the AWS Neuron SDK. This involves developing and tuning ML models and frameworks, building infrastructure for model onboarding, implementing low-level optimizations, and collaborating across hardware, software, and ML teams to ensure peak performance for customers. | 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). The role involves working across the stack from frameworks (PyTorch, JAX) to hardware, building infrastructure, optimizing performance (latency and throughput), and collaborating with various teams and customers to ensure efficient execution of large language models and other GenAI workloads. Experience with inference serving platforms like vLLM is required. | Serve | 8 |
| Sr. SDE, Simulation, Frontier AI Robotics Seeking a Simulation Engineer to join an AI robotics research team, focusing on developing 3D physics-based simulation frameworks and tools to enable large-scale machine learning model training for robotics. The role involves developing simulations for reinforcement learning, closed-loop simulations, synthetic data generation, implementing robotics features, building real-to-sim workflows, and collaborating with ML researchers. | DataPost-train | 8 |
| Principal Applied Scientist, Console Science Principal Applied Scientist role focused on building industry-leading Conversational AI Systems using Generative AI, LLMs, NLU, Dialog Systems, and Applied ML. The role involves developing novel algorithms and modeling techniques to advance human language technology, impacting millions of customers through products and services. It requires a PhD, extensive experience in ML model building for business applications, and a strong publication/patent record. The team uses generative AI and foundation models to reimagine customer experiences on AWS. | AgentPost-train | 8 |
| Sr. Software Engineer- AI/ML, AWS Neuron Distributed Training - Performance Optimization Senior Software Engineer focused on performance optimization for distributed AI model training on AWS Trainium accelerators. The role involves working with frameworks like PyTorch and JAX, optimizing the Neuron software stack, and improving training throughput and efficiency for large-scale models. | Post-trainServe | 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 |
| Principal Applied Scientist, Alexa International Tech The Principal Applied Scientist role at Amazon's Alexa International team focuses on defining research directions, inventing and applying ML techniques, conducting experiments, publishing results, and translating research into practice for expanding Alexa's reach across countries, languages, devices, and cultures. The role requires a PhD in AI/ML/NLP with 10+ years of experience, a strong publication record, and expertise in building and deploying ML solutions at scale. | Post-train | 8 |
| Software Development Engineer, Amazon Pharmacy, Amazon Phamarcy Software Development Engineer role at Amazon Pharmacy focusing on building ML-driven supply chain systems. Responsibilities include system design, development, operational ownership, and collaboration, with an emphasis on productionizing ML models for demand forecasting, procurement, and inventory placement. The role involves working with large-scale datasets, distributed systems, and operations research techniques within a regulated healthcare environment. | ServeData | 7 |
| Sr. Software Development Engineer, Data Center Design Engineering - BIM & AI Technologies Senior Software Development Engineer to lead the design and implementation of generative AI applications for data center design automation, integrating BIM platforms and AWS services. The role involves productionizing ML models, mentoring junior engineers, and building scalable systems in a greenfield opportunity. | Agent | 7 |
| 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 |
| Senior Delivery Consultant - Data, Professional Services, AWSI, Healthcare and Life Sciences This role focuses on designing and implementing modern data platforms, pipelines, and RAG architectures for AI and agentic systems within the Healthcare and Life Sciences industry. The consultant will work with complex data, regulatory requirements, and legacy systems to deliver production-grade data products that support ML model training and agent orchestration. | DataAgent | 7 |
| Data Scientist, IES CFX & Prime This role focuses on developing and deploying machine learning systems to detect fraudulent customer behavior, analyze customer risk, and optimize customer promotions within Amazon's online marketplace. It involves building end-to-end ML solutions in a production environment, collaborating with cross-functional teams, and applying advanced statistical techniques and GenAI technology. | Agent | 7 |
| Software Development Engineer, ISS Software Development Engineer to build innovative products and tools leveraging generative and agentic AI to transform workflows for Account Managers (AMs) in the International Seller Services (ISS) organization. The role involves developing new products and services from the ground up, enhancing existing tools, and working with product managers and applied science teams to create compelling user experiences. | Agent | 7 |
| Software Development Engineer, ISS Software Development Engineer to build innovative products and tools leveraging generative and agentic AI to transform workflows for Account Managers (AMs) in the International Seller Services (ISS) organization. The role involves developing new products and services from the ground up and enhancing existing tools, with a focus on AI Assistant functionalities and automation. | Agent | 7 |
| Applied Scientist II, Buyer Risk Prevention (BRP) This role focuses on applying machine learning and advanced statistical techniques to build and deploy systems for fraud and risk prevention in an e-commerce environment. The scientist will own end-to-end model development, from problem formulation to production, leveraging Generative AI and LLMs to enhance detection and prevention systems. The role involves analyzing large datasets, identifying fraud patterns, and collaborating with engineering and business teams to deliver measurable impact. | Ship | 7 |
| Applied Scientist, Amazon Compliance and Safety Services Research Scientist role focused on applying and extending state-of-the-art NLP, multi-modal modeling, and LLM research to improve product compliance and safety at Amazon. The role involves researching algorithms, designing new ML solutions, and collaborating with engineering and product teams to implement them across Amazon's product catalog. | Post-train | 7 |
| Software Development Engineer I, ML Infra Services, Annapurna Labs Software Development Engineer I role focused on building and evolving machine learning infrastructure services, specifically tooling for profiling, optimization, and resource management of ML workloads on custom AI accelerators. The role involves working across the stack from infrastructure orchestration to developer-facing tooling, with a focus on shipping solutions to a large customer base and contributing to the development of AI accelerators like AWS Neuron. | Serve | 7 |
| Software Development Engineer I, ML Infra Services, Annapurna Labs Software Development Engineer to build and evolve machine learning infra services for custom AI accelerators (AWS Neuron). Role focuses on tooling for profiling, optimization, and resource management of ML workloads, working at the intersection of Kubernetes, custom silicon, and large-scale ML workloads. | Serve | 7 |
| Software Dev Engineer III, ICON Software Development Engineer III role focused on building systems that apply generative AI and agentic architectures to automate infrastructure operations at scale for Amazon's e-commerce platform. The role involves designing, implementing, and delivering large-scale services, influencing technical strategy, and collaborating with stakeholders to develop new products. Experience with production systems integrating generative AI is strongly valued. | Agent | 7 |
| Software Development Engineer I, ML Infra Services, Annapurna Labs Software Development Engineer I role focused on building and evolving machine learning infrastructure services and tooling for AWS Neuron AI accelerators. The role involves designing and implementing solutions for profiling, optimization, and resource management of ML workloads, working across the stack from infrastructure orchestration to developer-facing tools. | Serve | 7 |
| Senior Security Engineer, AI Red Team, Threat Operations Senior Security Engineer focused on offensive security operations for AI systems, including training pipelines, inference systems, and model architectures. Responsibilities include security research on AI attack surfaces, developing automated offensive security tools, and collaborating with engineering teams to improve AI security posture. | Agent | 7 |
| Senior Delivery Consultant - Data , Professional Services, AWSI HCLS Senior Delivery Consultant specializing in Data for AWS Professional Services, focusing on Healthcare and Life Sciences (HCLS). The role involves designing and implementing modern data platforms (lake, lakehouse, mesh), architecting data pipelines, and building enterprise RAG architectures, vector stores, semantic ontologies, and knowledge graphs to enable AI readiness for customers. The consultant will work within regulated environments (GxP, HIPAA) and deliver production-grade data products for ML training and agentic orchestration. | DataAgent | 7 |
