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, AWS Applied AI Solutions This role focuses on leading technical innovation in visual reasoning foundation models, specifically building a next-generation visual reasoning engine powered by frontier Large Video Models (LVMs). The goal is to create a system that rivals human understanding of the physical world, capable of interpreting natural language, navigating environments, and executing complex tasks. It sits at the intersection of LVMs, LLMs, and Agentic AI, requiring end-to-end ownership from research to production deployment, with a focus on advancing state-of-the-art and solving real-world business problems. | AgentPost-train | 10 |
| Postdoctoral Scholar - SAF Lab, Compass Research role focused on developing and validating safe autonomy for highly dynamic robots, integrating control barrier functions (CBFs) with perception and learning, and deploying methods on physical robotic hardware. The work involves pushing the frontiers of safety theory, developing simulation and evaluation pipelines, and enabling robots to operate safely around humans. |
| ShipData |
| 9 |
| Principal Applied Scientist Perception, Compass Seeking a Principal Applied Scientist to lead safety-critical perception for robots, developing novel real-time predictive models of dynamic environments and human motion. This role involves architecting generalizable perception pipelines across sensor modalities, investigating foundation models, and quantifying perception uncertainty to ensure safe robot autonomy. | AgentData | 9 |
| Applied Scientist, Conversational Assistant Modeling and Learning Applied Scientist role at Amazon focusing on building Alexa+, an LLM-powered conversational assistant. Responsibilities include LLM fine-tuning, alignment, agentic reasoning, and evaluation pipelines. The role involves designing and implementing end-to-end systems, translating research into production, and publishing results. It operates at massive scale across multiple languages and device types. | AgentPost-train | 9 |
| 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 |
| Member of Technical Staff, FAR (Frontier AI & Robotics) Research role focused on developing foundation models for robotics, involving multi-modal understanding, sim2real transfer, and efficient inference, with a goal of large-scale deployment. | PretrainServe | 9 |
| Applied Scientist, Selling Partner Support Engagement Research scientist role focused on building and improving AI agents for customer support, involving RL-based systems, preference learning, reward modeling, and policy optimization. The role emphasizes end-to-end ownership from research to production deployment, collaboration with engineering teams, and publishing research. It operates within an enterprise AI domain focused on scaling AI solutions for customer interactions. | AgentPost-train | 9 |
| Senior Applied Scientist, Amazon AWS Agentic AI, AWS AI Fundamental Research This role focuses on leading the design and development of agentic evaluation frameworks and training evaluation/critic models to assess the quality and effectiveness of AI agents. The scientist will define methodologies, create benchmarks, build automated systems, and conduct research to advance agent and evaluation science. The role involves end-to-end ownership from research to production deployment, collaborating with engineering to deliver these capabilities as managed AWS services. It also includes mentoring junior scientists and contributing to the research community. | Eval GatePost-train | 9 |
| Member of Technical Staff - Science, Frontier AI & Robotics (FAR) Research role focused on developing foundation models for robotics, involving perception, manipulation, and multi-modal learning, with a goal of real-world deployment. | Post-trainAgent | 9 |
| Human-Robot Interaction Applied Scientist , Fauna Seeking an HRI Applied Scientist to develop cutting-edge interactions for robots, focusing on verbal/non-verbal systems, social dynamics, memory, and long-term relationships. The role involves developing interactive systems using LLMs, multimodal inputs/outputs, and RLHF, designing conversational systems, integrating sensor streams, and developing memory/personalization systems. The scientist will stay updated on HRI/ML/AI/HCI advancements, lead technical projects, mentor junior staff, and bridge research with engineering. | AgentPost-train | 9 |
| Applied Scientist II, Amazon AWS Agentic AI, AWS AI Fundamental Research Research scientist role focused on building industry-leading generative AI and foundational models, with a specific emphasis on Agentic AI, impacting millions of customers through speech, vision, and language technologies. The role involves developing novel algorithms and modeling techniques, working with large-scale data and computing resources. | AgentPost-train | 9 |
| Applied Scientist, Prime Video - Generative AI Applied Scientist role focused on Generative AI for Prime Video, involving research and development of generative models for synthesis (images, video, multimedia), advancing diffusion and flow-based methods, and designing multimodal GenAI workflows including agentic pipelines. The role aims to deliver production-ready systems at Amazon scale. | Post-trainAgent | 9 |
| Applied Scientist, Amazon Robotics Applied Scientist role focused on developing and training foundation models for robotics, integrating multi-modal learning, imitation learning, and reinforcement learning. The role involves model development, data management, experimentation, and research to enhance robotic perception and skill acquisition. | Post-trainAgent | 9 |
| Senior Applied Scientist, AWS Quick Senior Applied Scientist role focused on building next-generation models for intelligent automation within AWS. The role involves designing and implementing neuro-symbolic systems that integrate formal reasoning with GenAI for reliable outcomes, enhancing formal reasoning capabilities for agentic applications, and driving adoption of these solutions across AWS services. It requires end-to-end ownership of the science lifecycle, including research, experimentation, production deployment, and defining performance metrics. The position also involves mentoring junior scientists and contributing to state-of-the-art through publications and patents. | AgentEval Gate | 9 |
| Member of Technical Staff - Science, Frontier AI & Robotics (FAR) This role focuses on foundational research and building intelligent robotic systems, operating at the intersection of AI research and robotics. The individual will conduct original research, publish findings, and deploy innovations into production systems at Amazon scale. Key areas include developing foundation models, full-stack robotics systems, locomotion, manipulation, perception, sim2real transfer, multi-modal and multi-task robot learning, and designing frameworks that bridge research and deployment. | AgentPost-train | 9 |
| Member of Technical Staff - Hardware Science, Frontier AI & Robotics (FAR) This role focuses on foundational research and building intelligent robotic systems by developing foundation models for perception and manipulation, integrating them with hardware systems, and deploying them at Amazon scale. It involves independent research initiatives, full-stack robotics projects from conceptualization to hardware deployment, and collaboration with hardware engineering teams. | ShipData | 9 |
| Robotics/AI Motor Control Scientist, Fauna Robotics/AI Motor Control Scientist role focused on developing and optimizing ML algorithms, particularly reinforcement and imitation learning, for robot motor control. The role involves research, simulation, sim-to-real transfer, and integration with hardware, aiming to enable complex whole-body tasks and safe human-robot interaction. It bridges research with practical engineering and has a strong publication requirement. | ShipData | 9 |
| Applied Scientist, RL post-training, AWS Research scientist role focused on Reinforcement Learning (RL) post-training of frontier Large Language Models (LLMs) to improve capabilities like instruction following, reasoning over long context, and tool use for customer service applications within AWS. | Post-train | 9 |
| Senior Applied Scientist, Alexa International Senior Applied Scientist role focused on developing novel algorithms and modeling techniques for Large Language Models (LLMs) and multimodal systems, with an emphasis on multi-lingual applications across text, speech, and vision domains. The role involves driving scientific strategy, influencing partner teams, and delivering solutions impacting global customers. | Post-trainAgent | 9 |
| Applied Scientist, Agentic Automated Reasoning Group Pioneering next-generation neuro-symbolic tools by fusing AI breakthroughs with cloud scale and automated reasoning expertise. This role involves building scalable formal reasoning solutions, integrating GenAI and Agentic AI, and applying software engineering best practices to production systems. Responsibilities include defining and implementing automated reasoning features, designing and running RL pipelines, experimenting with model tradeoffs, and collaborating cross-functionally. The role also focuses on enhancing formal reasoning systems for GenAI applications, owning the science lifecycle, and advancing the state of the art through publications and patents. | AgentPost-train | 9 |
| Senior Applied Scientist, Shopping Core Foundations - BuyForMe This role focuses on building and researching autonomous AI agents for online shopping, operating on the open web. It involves LLMs, reinforcement learning, multimodal reasoning, and large-scale systems, with a focus on production-grade reliability, scalability, and safety. The scientist will design evaluation systems, develop agent planning and adaptation techniques, build multimodal reasoning systems, and lead scientific direction for agent reliability and customer trust. | AgentEval Gate | 9 |
| Applied Scientist - Agentic AI, Amazon Fulfillment Technology This role focuses on developing and researching agentic AI systems for operational decision-making and orchestration within Amazon's fulfillment network. It involves building full agentic systems using multi-agent orchestration, tool use, memory, and action execution, training LLMs through various methods including RL, and conducting rigorous evaluations. The role also includes leading research projects, mentoring, and publishing academic papers. | AgentPost-train | 9 |
| Member of Technical Staff, Artificial General Intelligence Research role focused on developing foundational Generative AI (GenAI) technology using Large Language Models (LLMs) and multimodal systems, involving model training, dataset design, and pre/post-training optimization. | Post-trainPretrain | 9 |
| Member of Technical Staff - Science, Frontier AI & Robotics (FAR) Research role focused on developing foundation models for robotics, involving perception, manipulation, and multi-modal learning, with a goal of real-world deployment. | Post-trainAgent | 9 |
| Senior Applied Scientist Senior Applied Scientist at Amazon focused on using Generative AI, VLMs, and multimodal reasoning to understand product identity and relationships within Amazon's catalog. The role involves formulating research problems, designing and implementing models for product relationship inference and catalog understanding, pioneering explainable AI, owning ML pipelines from research to production, defining research roadmaps, and mentoring peers. It emphasizes tackling ambiguous problems at scale, reasoning across text and images, and deploying solutions that impact millions of customers. | AgentServe | 9 |
| Principal Applied Scientist, Neuro-Symbolic AI Labs Research scientist role focused on building neuro-symbolic AI systems using proof assistants for complex problem-solving across various domains within Amazon. The role involves defining and implementing new applications, delivering scientific artifacts, and working in an agile environment. Requires a PhD or Master's with significant applied research experience, and experience leading scientists. | Agent | 9 |
| Applied Scientist, Alexa Connections Applied Scientist role focused on developing novel algorithms and modeling techniques for LLMs and multimodal systems within Alexa Connections. Responsibilities include analyzing customer behavior, building evaluation metrics, fine-tuning/post-training LLMs, setting up experimentation frameworks, and contributing to end-to-end delivery from research to production, with potential for publications. | Post-trainAgent | 9 |
| 2026 Fall Applied Science Internship - Gen AI & Large Language Models - United States, PhD Student Science Recruiting PhD internship focused on applied science in Gen AI and LLMs, involving fine-tuning models, developing novel algorithms for NER, recommendation systems, and question answering, and exploring generative AI applications. | Post-trainAgent | 9 |
| 2026 Fall Applied Science Internship - Natural Language Processing and Speech Technologies - United States, PhD Student Science Recruiting PhD internship focused on research in Natural Language Processing (NLP), Natural Language Understanding (NLU), and Speech Technologies, including large language models (LLMs) and reinforcement learning with human feedback (RLHF). The role involves developing and implementing novel algorithms on production-scale data to advance the state-of-the-art. | Post-trainPretrain | 9 |
| Postdoctoral Scientist, Amazon Robotics Research and AI Development Postdoctoral Scientist role focused on research in multi-agent path planning, dynamic optimal transport, and explainable AI for foundation models applied to a large fleet of mobile robots. The role involves developing novel techniques, publishing in top-tier venues, and potentially extending research into a second year. | AgentPost-train | 9 |
| 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 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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, Regulatory, Intelligence, Safety and Compliance (RISC) Applied Scientist role focused on agentic AI, GenAI, and Machine Learning for regulatory compliance at Amazon. The role involves designing and evaluating state-of-the-art algorithms for content generation, multi-modal classification, intent detection, information retrieval, anomaly detection, and agentic systems. It requires developing and deploying ML models at scale, with an emphasis on scientific innovation and publication. | AgentPost-train | 8 |
| Postdoctoral Researcher – Visual Localization & Navigation | Amazon Last Mile Research scientist role focused on visual localization and navigation for robotics and logistics platforms, involving metric-semantic mapping, relocalization, and monocular localization using geometric and learning-based approaches. | Agent | 8 |
| Sr. Applied Scientist, C360 Senior Applied Scientist role focused on advancing Information Retrieval, NLP, and Large Language Models for e-commerce personalization. The role involves post-training LLMs (instruction tuning, reward modeling, RL, multi-modal alignment), designing large-scale experiments, analyzing model behavior, and developing training recipes to improve capabilities like reasoning and personalization. It also includes owning the scientific roadmap, leading end-to-end systems, driving technical decisions, mentoring, and publishing research. | Post-trainAgent | 8 |