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 |
|---|---|---|
| Sr. Applied Scientist, Ads AI Core Infrastructure Research and develop novel approaches for agent-data interaction using generative AI and agentic systems to provide instant, strategic advice to advertisers. Focus on agent orchestration, context optimization, code generation, and RAG-based embeddings for real-time data access with minimal latency and token consumption. Balances applied research (60%) with productionization (40%). | Agent | 9 |
| Applied Scientist II, Alexa Sensitive Content Intelligence (ASCI) This role focuses on building AI safety systems for Alexa, ensuring LLMs provide safe and trustworthy responses. It involves pioneering solutions in Responsible AI, designing automated testing systems, creating intelligent evaluation systems, building models that understand human values, and crafting AI agents for real-time detection and fixing of production issues. The role emphasizes frontier research with immediate real-world impact, aiming to set industry standards for responsible AI. |
| Eval GatePost-train |
| 9 |
| Applied Scientist, Alexa Connections Applied Scientist role focused on building and evaluating LLMs and multimodal systems for Alexa Connections, involving fine-tuning, post-training, and contributing to research and production delivery. | Post-trainAgent | 9 |
| Applied Scientist, Amazon Robotics Research scientist role focused on combining LLMs with classical AI reasoning for robotics and automation applications. The role involves generating plans, verifying correctness, learning strategies, and self-improving models, with an emphasis on publishing research and applying technology to operational problems. | Agent | 9 |
| Applied Scientist, Amazon Robotics Research scientist role focused on combining LLMs with classical AI reasoning for robotics and automation applications. The role involves generating plans, verifying correctness, learning strategies, and self-improving models, with an emphasis on publishing research and applying technology to operational problems. | Agent | 9 |
| Sr. Applied Scientist, Amazon Robotics The role focuses on building AI reasoning systems that combine classical AI reasoning with Large Language Models (LLMs) for applications in robotics, automation, and fulfillment. The scientist will innovate on techniques for plan generation, verification, learning reasoning strategies, and self-improving models, with an emphasis on publishing research in leading AI venues. | AgentPost-train | 9 |
| Sr. Applied Scientist, Trust CX Innovations&AI Policy Senior Applied Scientist role focused on Generative AI, LLMs, and multimodal models for Alexa+, emphasizing AI trust, privacy, safety, and alignment. The role involves leading research, developing optimization techniques, pioneering responsible AI methods, and collaborating with product and engineering teams to deliver production-ready AI solutions. | Post-trainAgent | 9 |
| Applied Scientist Research scientist role focused on applying Generative AI, VLMs, and multimodal reasoning to product catalog understanding and agentic shopping experiences. The role involves formulating research problems, pushing boundaries of foundation models, advancing efficient model deployment, and ensuring reliability through interpretability and uncertainty calibration. It spans the full research lifecycle from problem formulation to production deployment, with a strong emphasis on publishing findings and mentoring. | AgentServe | 9 |
| Principal Applied Scientist, Conversational Assistant Modeling & Learning Principal Applied Scientist to lead science behind Alexa+, Amazon's LLM-powered conversational assistant. Owns technical direction for LLM fine-tuning, alignment, agentic reasoning, and evaluation, impacting hundreds of millions of customers. Defines research directions, designs experiments, ensures translation to production systems, mentors scientists, and represents Amazon in the research community. | Post-trainAgent | 9 |
| Applied Scientist, Demand Forecasting Research scientist role focused on designing and building large-scale foundation models for time series demand forecasting. The role involves developing novel architectures, training strategies, and data generation techniques, with a strong emphasis on both scientific research (publications) and production deployment impacting millions of dollars in automated decisions. Experience with transfer learning, zero-shot forecasting, and synthetic data generation is key. | PretrainServe | 9 |
| Principal Applied Scientist, Sponsored Products and Brands This role focuses on designing and developing generative AI solutions, specifically large language models and multimodal AI, for real-time ad allocation and ranking in a high-volume consumer advertising system. It involves research into semantic relationships, dynamic optimization, and integration into existing systems, with a strong emphasis on efficiency and strict latency requirements. | AgentServe | 9 |
| Applied Scientist III, Alexa International This role focuses on advancing the state of the art with LLMs and multimodal systems for Alexa's international products. The scientist will develop novel algorithms, build evaluation metrics, fine-tune/post-train LLMs using advanced techniques (SFT, DPO, RLHF, RLAIF), and contribute to industry-first research. The role involves end-to-end delivery from research to production, influencing cross-team scientific strategy, and mentoring junior scientists. Key areas include multi-lingual applications, text, speech, and vision domains, with a strong emphasis on LLM evaluation and post-training methodologies. | Post-trainAgent | 9 |
| Senior Applied Scientist, GEM Senior Applied Scientist role focused on shaping visual shopping experiences using agentic AI, multimodal personalization, and real-time image/video generation. The role involves defining scientific vision, architecting multimodal understanding and generation systems, and establishing evaluation frameworks for visual agentic experiences. It requires strong research skills, practical engineering instincts, and influencing cross-functional teams, with a focus on delivering scalable solutions and contributing to publications/patents. | AgentPost-train | 9 |
| Applied scientist, Agentic AI, AWS Agentic AI This role focuses on building the next generation of models for intelligent automation using autonomous agents, API orchestration, large multimodal models (especially vision-language models), reinforcement learning, and sequential decision making. The role involves developing innovative solutions, publishing findings, and partnering with engineers and developers. | Agent | 9 |
| Applied Scientist II, Ads AI Core Infrastructure Research and develop novel approaches for agent-data interaction using generative AI and agentic systems, focusing on agent orchestration, context optimization, and code generation for real-time advertiser data at scale. This role involves applied research (60%) and productionization (40%), aiming to improve latency, token consumption, and accuracy. | AgentData | 9 |
| Applied Scientist Applied Scientist role focused on leveraging Generative AI, VLMs, and multimodal reasoning to solve complex product identity and relationship inference problems at Amazon's scale. The role involves pioneering advanced GenAI solutions for next-generation agentic shopping experiences, working with massive multimodal data, and deploying algorithmic ideas at scale. Responsibilities include formulating research problems, designing and implementing models, pioneering explainable AI, owning ML pipelines, defining research roadmaps, and mentoring peers. | AgentPost-train | 9 |
| Sr. Applied Scientist, AWS Just-Walk-Out Science Team This role focuses on developing novel frameworks and techniques for multi-object tracking, re-identification, person activity understanding, and multi-modal foundation models within the context of Amazon's Just Walk Out technology. The scientist will advance the theory and practice of these areas, create efficient visual processing techniques, and reduce computational/data requirements for visual AI systems. The role requires a strong publication record in top-tier conferences and experience in computer vision, deep learning, and multi-modal foundation models. | AgentPost-train | 9 |
| Sr. Applied Science Manager, Agentic AI Ads, Sponsored Products and Brands Lead a new applied science organization focused on building agentic AI systems for advertising campaigns. This role involves defining the scientific vision, research agenda, model architectures, and evaluation frameworks for LLM-based agents, multi-step planning, tool use, RAG, and RLHF, with a focus on delivering measurable value and transforming the advertiser journey. The role requires building and mentoring a team, partnering with cross-functional teams, and driving execution from research to production at scale. | AgentEval Gate | 9 |
| Applied Scientist Gen AI - Amazon Advertising, CreativeX Applied Scientist role focused on developing novel multi-modal generative AI agentic architectures and models for advertising creatives, integrating and deploying ML projects, curating datasets, and performing analysis. The role involves research, publication, and collaboration with cross-functional teams. | AgentData | 9 |
| Sr. Principal Scientist, AWS Developer Agents and Experiences (DAE) Senior Principal Scientist role focused on developing industry-leading Agentic AI solutions for AWS, including autonomous agents for incident detection/resolution and proactive code repair, leveraging advanced deep learning and foundation models for cloud observability and security. | AgentPost-train | 9 |
| Member of Technical Staff, Multimodal Reasoning - Applied Science , AGI Autonomy Applied Science role focused on developing foundational capabilities for useful AI agents, leveraging large vision language models (VLMs) with reinforcement learning (RL) and world modeling. Responsibilities include model training, dataset design, and pre- and post-training optimization in an applied research setting. | Post-trainAgent | 9 |
| Member of Technical Staff, AGI Autonomy Research role focused on developing foundational capabilities for AI agents, combining LLMs with reinforcement learning for reasoning, planning, and world modeling in virtual and physical environments. Involves model training, dataset design, and pre/post-training optimization. | AgentPost-train | 9 |
| Applied Scientist, LLM Code Agents, Kiro Science Research role focused on advancing LLM code intelligence through reinforcement learning and post-training methodologies, with a goal of deploying these models into developer tools like Kiro IDE and Amazon Q Developer at Amazon scale. The role involves publishing research and transitioning breakthroughs into production systems. | Post-trainAgent | 9 |
| Senior Applied Scientist, ASCS AI Lab Team Senior Applied Scientist role focused on AI research and development, including Generative AI, Agentic AI, LLMs, and Diffusion Models for Amazon's catalog systems. The role involves designing, training, and deploying AI solutions, with a focus on scaling models and integrating them into production. | AgentPost-train | 9 |
| Sr. Principal Scientist, Amazon Health Science & Analytics Senior AI/ML researcher to define ML strategy for a healthcare foundation model and inference system, focusing on frontier models, proprietary domain models, and monetizable features under regulatory constraints. Requires expertise in training/adapting large models, distributed training, RLHF/DPO, retrieval, evaluation, and ML systems engineering, with experience in high-stakes/regulated domains. | PretrainServe | 9 |
| 2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & Robotics Internship role focused on developing novel algorithms at the intersection of LLMs and generative AI for robotics, involving research in perception, manipulation, and control. Requires strong ML/DL/robotics background and publication record. | Agent | 9 |
| 2026 Applied Science Internship - United States, Undergrad Student Science Recruiting, Frontier AI & Robotics This internship focuses on developing novel algorithms and modeling techniques at the intersection of LLMs and generative AI for robotics, tackling research problems in robotic perception, manipulation, and control. The role involves collaboration with cross-functional teams and requires a strong background in machine learning, deep learning, and/or robotics, with a publication record at top conferences. | Agent | 9 |
| 2026 Applied Science Internship - United States, PhD Student Science Recruiting, Frontier AI & Robotics This internship focuses on developing novel algorithms at the intersection of LLMs and generative AI for robotics, involving research in robotic perception, manipulation, and control, with an emphasis on multimodal models and vision-language-action systems. | AgentPost-train | 9 |
| Applied Scientist, LLM Code Agents, Kiro Science Research role focused on advancing LLM code intelligence through reinforcement learning and post-training methodologies, with a goal of deploying these models into developer tools like Kiro IDE and Amazon Q Developer at Amazon scale. The role involves publishing research and transitioning breakthroughs into production systems. | Post-trainAgent | 9 |
| Applied Scientist, Artificial General Intelligence Seeking an Applied Scientist to develop industry-leading technology with LLMs and multimodal systems, focusing on advanced approaches, model-in-the-loop and human-in-the-loop for high-quality data collection and LLM training, and enhancing customer experiences. | Post-trainAgent | 9 |
| Member of Technical Staff Intern (2026), Artificial General Intelligence (AGI) Research intern role focused on developing foundational capabilities for AI agents, combining LLMs with RL for reasoning, planning, and world modeling. The role involves running experiments, building tools to accelerate research workflows, and scaling AI systems within a fast-paced, iterative research lab environment. | Agent | 9 |
| Computer Vision Scientist, International Machine Learning, Australia Computer Vision Scientist role focused on developing and evaluating generative AI models for e-commerce media content, leveraging large datasets and cloud resources. The role involves research, implementation of novel ML techniques, and communication with stakeholders. | Post-trainServe | 9 |
| Member of Technical Staff - Reinforcement Learning, AGI Autonomy Research role focused on developing foundational capabilities for AI agents that can act in digital and physical worlds, with a focus on multimodal LLMs, automation agent systems, and applying GenAI to real-world problems. Involves rapid invention, experimentation, and collaboration. | AgentPost-train | 9 |
| Principal Applied Scientist, Ring AI Principal Applied Scientist role focused on computer vision and multimodal LLMs, involving research, algorithm development, and translating research into practice for consumer products. Requires PhD, 10+ years of ML experience, and expertise in computer vision, VLM, and deep learning. The role involves defining research directions, developing long-term strategies, and mentoring junior scientists. | Post-trainAgent | 9 |
| Sr Mgr, Applied Science, AWS Supply Chain Senior Manager of Applied Science to lead science and data teams working on innovative AI-powered supply chain solutions, focusing on GenAI/Agentic AI for enterprise applications. The role involves driving technical vision, fostering innovation, leading researchers, and delivering solutions to production. | AgentShip | 9 |
| Sr. Principal Scientist, Secure Work Enablement Senior Principal Scientist role focused on pioneering AI technologies for secure enterprise collaboration, including novel AI architectures, human-AI interaction, AI agent orchestration, and privacy-preserving ML. The role involves translating business requirements into AI deliverables, inventing new product experiences, and bringing state-of-the-art LLM/GenAI models to production, while defining long-term science vision and collaborating with academic partners. | Agent | 9 |
| 2026 Applied Science Internship - United States, Undergrad Student Science Recruiting, Frontier AI & Robotics Internship role focused on developing novel algorithms and modeling techniques at the intersection of LLMs and generative AI for robotics, tackling research problems in robotic perception, manipulation, and control. Involves collaboration with cross-functional teams and leveraging expertise in deep learning, reinforcement learning, computer vision, and motion planning. | ShipAgent | 9 |
| Applied Scientist, AGI Information Research scientist role focused on cutting-edge LLM technologies, integrating multimodal information using techniques like RAG, and applying results to Amazon products. Requires independence and a strong research background with publications. | AgentData | 9 |
| Member of Technical Staff, Applied Science - People Leader, AGI Autonomy Lead a research team focused on advancing foundational capabilities for useful AI agents by combining LLMs with RL. The role involves managing research, aligning roadmaps, mentoring, and hiring, with a focus on evolving agents for reasoning, planning, and world modeling. Experience with training large models, scaling foundational models, and applying post-training techniques is required. | AgentPost-train | 9 |
| Applied Scientist, AGI Information Research scientist role focused on state-of-the-art LLM technologies, integrating structured and unstructured information (e.g., RAG) for applications across Amazon businesses, with a focus on delivering innovations from research to production. | AgentPost-train | 9 |
| Principal Applied Scientist, FAR (Frontier AI & Robotics) Lead the development of breakthrough foundation models for robotics, focusing on perception, manipulation, and interaction with the world. This role involves hands-on research, algorithm design, and scaling models for real-world deployment at Amazon scale, with a focus on multi-modal and efficient architectures. | PretrainServe | 9 |
| Manager Research Science, Last Mile Science and Analytics Manager Research Science role focused on optimizing Amazon's delivery network using advanced ML models, AI systems, and AI agents. The role involves developing algorithms for forecasting, resource allocation, and decision-making, with a focus on building and deploying AI-driven solutions for logistics. | AgentData | 8 |
| Applied Scientist, Ring AI Applied Scientist role focused on computer vision and machine learning for consumer products (Ring devices). The role involves research, development, evaluation, and deployment of models, with a specific emphasis on Multi-modal LLMs and Vision Language Models. Collaboration with product and engineering teams is key. | Post-trainAgent | 8 |
| 2027 Applied Science Intern (Computer Vision), Amazon International Machine Learning Internship role focused on Computer Vision and Machine Learning research, developing novel solutions and prototypes with potential impact on customer-facing products. Involves collaboration with researchers and publication in top-tier conferences. | Post-train | 8 |
| Applied Scientist, Conversational AI ModEling and Learning Research and develop novel algorithms and modeling techniques for conversational AI using LLMs, focusing on prompt engineering, fine-tuning, and learning from human feedback to improve user experience and enable natural conversations. | Post-trainAgent | 8 |
| Applied Scientist, AICE - AI Center of Excellence Research Scientist role focused on building and hardening AI primitives for enterprise-wide consumption at Amazon, translating research into production-ready solutions and driving scientific direction. | ShipData | 8 |
| Applied Scientist - LLM, Alexa Applied Scientist role focused on training and deploying LLMs for conversational AI systems like Alexa. The role involves end-to-end ownership from research and algorithm development to production deployment and inference infrastructure. | Post-trainServe | 8 |
| 2027 Applied Science Intern (Machine Learning, Recommender Systems), Amazon International Machine Learning Internship role focused on developing novel solutions and prototypes in Deep Learning and Generative AI, with potential to deliver to production. Collaborates with R&D scientists and aims to publish research in top ML conferences. | Ship | 8 |
| Applied Scientist, Traffic Quality Applied Scientist role focused on detecting sophisticated invalid traffic (IVT) in advertising using deep learning, self-supervised techniques, representation learning, and advanced clustering. The role involves working with massive datasets, developing novel algorithms, and deploying production-quality ML components. Emphasis on research, innovation, and contributing to the scientific community through publications. | Agent | 8 |
| Data Scientist, Traffic Quality The Data Scientist II in Traffic Quality at Amazon Ads will focus on applying advanced statistical techniques and machine learning to detect sophisticated invalid traffic (IVT) in advertising. This role involves defining new research problems, applying ML models to detect fraud, performing data analysis, working with massive datasets, and producing research reports. The team leverages deep learning, generative modeling, user behavior analysis, anomaly detection, and time-series analysis to protect advertiser spend and maintain marketplace integrity. The role also involves mentoring junior scientists and has a strong publication record. | AgentData | 8 |