Currently tracking 1110 active AI roles, down 16% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).
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.
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 |
|---|---|---|
| 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 |
| 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 |
| 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 |
| Applied Scientist, Prime Video Commerce Insights Applied Scientist role focused on Reinforcement Learning and ML for personalization in Prime Video Commerce, involving research, design, implementation, and deployment of recommendation systems at scale with low latency. The role aims to improve customer experience and business metrics by applying advanced ML techniques and contributing to the science roadmap. | AgentServe | 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 |
| Senior Applied Scientist, C360 Senior Applied Scientist role focused on improving shopping experiences using LLMs. The role involves post-training activities like instruction tuning, reward modeling, reinforcement learning, and aligning LLMs with embedding modalities. Responsibilities include designing and running large-scale experiments, analyzing model behavior, and developing new training recipes to enhance reasoning and personalization. | Post-trainPretrain | 8 |
| Applied Scientist, Personalization, Personalization Strategic Initiatives Science Research scientist role focused on developing and launching new AI technologies for personalization, including recommendation systems and large language models, leveraging large datasets and computational resources to impact millions of customers. | Ship | 8 |
| Applied Scientist, Personalization, Personalization Strategic Initiatives Science Research scientist role focused on developing and launching large-scale machine learning solutions for personalization and recommendation systems, impacting millions of customers. | Ship | 8 |
| Applied Scientist , Personalization & Ranking Research Scientist focused on developing and launching new AI technologies for personalization and recommendation systems, utilizing deep learning, LLMs, and reinforcement learning, with a strong emphasis on experimentation and A/B testing. | ShipPost-train | 8 |
| Applied Scientist , Personalization & Ranking Research Scientist focused on developing and launching new AI technologies for personalization and recommendation systems, utilizing deep learning, LLMs, and reinforcement learning, with a strong emphasis on experimentation and A/B testing. | ShipPost-train | 8 |
| 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 across images, video, and multimedia. The role will innovate in diffusion and flow-based methods, advance visual grounding and 3D estimation, and design multimodal GenAI workflows including agentic pipelines. | Post-trainAgent | 8 |
| Robotics/AI Motor Control Scientist, Fauna Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots, focusing on creating and optimizing intelligent motor control strategies for complex, whole-body tasks. The role involves using RL/IL, integrating with hardware, simulation/testing, and bridging research with practical implementation. | ShipData | 8 |
| Postdoctoral Scientist, Amazon Robotics Research and AI Development Postdoctoral Scientist role focused on AI-driven optimization for robotic fulfillment operations, involving automated optimization formulation, intelligent solver configuration, and fleet-level AI for dynamic task allocation. The role emphasizes research, publication in top-tier venues, and developing scalable solutions for robotic warehouses. | Agent | 8 |
| Sr. Applied Scientist, Alexa International The Senior Applied Scientist will focus on developing novel algorithms and modeling techniques for multilingual speech generation, text-to-speech synthesis, and speech-to-speech models within the Alexa International team. This role involves driving scientific strategy, influencing partner teams, and delivering solutions that enhance voice experiences across multiple languages, leveraging large-scale computing resources and addressing challenges in low-resource language settings. | Post-trainServe | 8 |
| Sr. Applied Scientist, Alexa International Senior Applied Scientist role focused on developing and advancing multilingual speech models (understanding and generation), text-to-speech synthesis, and speech-to-speech models for Alexa International. The role involves driving scientific strategy, leveraging large-scale computing resources, and optimizing model performance for production deployment in low-resource language settings. | Post-trainServe | 8 |
| Senior Applied Scientist, Amazon Shopping Personalization Senior Applied Scientist role focused on researching, designing, and developing new AI technologies for Amazon's Personalization and recommendation systems. The role involves inventing, experimenting with, and launching new features and products using large-scale datasets and computational resources. Key responsibilities include building state-of-the-art models, conducting experiments, and collaborating with engineers and product managers to implement solutions end-to-end. | ShipPost-train | 8 |
| Sr. Applied Scientist, Amazon Robotics This role focuses on applying AI reasoning systems, specifically combining classical AI reasoning with Large Language Models (LLMs), to solve problems in robotics, automation, and fulfillment. The scientist will innovate on techniques for plan generation, correctness verification, learning reasoning strategies, and self-improving models, with an emphasis on publishing research and applying findings to business problems. | Agent | 8 |
| Applied Scientist, Observability and Triage, Prime Video Applied Scientist role focused on building generative AI and large model systems for automated incident triage, root cause analysis, and resolution recommendation within Prime Video's observability and operational systems. The role involves prototyping, evaluating hypotheses, building evaluation frameworks, and collaborating with engineering teams to integrate ML models into production. | AgentEval Gate | 8 |
| Applied Scientist II, Search Ranking Applied Scientist II role at Amazon focused on improving search ranking by inventing and implementing ML solutions. This involves data analysis, model design, training, A/B testing, and deploying production-level components for Amazon's product search service. | Ship | 8 |
| Agentic Evaluation Scientist, Amazon Customer Service This role focuses on developing evaluation techniques and ML models for agentic AI systems within Amazon's Customer Service to identify and prevent customer defects. The scientist will create methods for efficient human annotation, improve agentic system performance, and build standalone ML models to support automated investigations. The goal is to ensure rigorous quality and continuous improvement of AI-driven customer experience solutions at scale. | Eval GateAgent | 8 |
| Senior Applied Scientist, Fauna This role focuses on developing evaluation frameworks and data collection protocols for robotic capabilities, operating at the intersection of robotics, machine learning, and human-in-the-loop systems. The scientist will design how to measure, stress-test, and improve robot behavior, build infrastructure connecting teleoperation, evaluation, and learning, and lead technical projects. | Eval GateAgent | 8 |
| Applied Scientist, Agentic Automated Reasoning Applied Scientist role focused on building next-generation software verification tools by combining AI, cloud computing, and formal methods. The role involves understanding customer needs, identifying tools and methods, exploring generative AI for formalization and testing, and developing agentic systems for safety and security. | Agent | 8 |
| 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 integrated with GenAI and agentic AI for AWS customers, focusing on areas like hallucination detection and policy verification. The scientist will define and implement features, ensure software quality, and drive adoption of these advanced systems, with a potential to publish research. | AgentEval Gate | 8 |
| Senior Applied Scientist, Agentic Automated Reasoning Group Senior Applied Scientist role focused on pioneering neuro-symbolic tools by fusing AI breakthroughs with automated reasoning and cloud scale. The role involves defining and implementing automated reasoning features, applying software engineering best practices, and delivering high-quality scientific artifacts. Key responsibilities include designing and implementing production-grade neuro-symbolic systems, enhancing formal reasoning capabilities for GenAI and agentic applications (like hallucination detection and guardrails), and owning the end-to-end science lifecycle from research to production deployment. The role also involves mentoring junior scientists and advancing the state of the art through publications. | AgentEval Gate | 8 |
| Applied Scientist, RL post-training, AWS This role focuses on Reinforcement Learning (RL) post-training of frontier LLMs to improve capabilities like instruction following, reasoning, and tool use, primarily for customer service applications within AWS. The role involves developing innovative solutions, publishing findings, and working with researchers and engineers. | Post-train | 8 |
| Sr Applied Scientist III, Supply Chain Optimization Technologies - SCAIL This role focuses on designing, implementing, and evaluating innovative models and agents using Reinforcement Learning (RL) for supply chain optimization. It involves both advancing theoretical knowledge in ML/AI and applying these insights to real-world business problems, with an emphasis on research and publication. | Post-trainAgent | 8 |
| Applied Scientist, RBS Tech Applied Scientist role focused on designing and deploying GenAI, NLP, and Computer Vision solutions for customer experience and operations automation. Involves developing novel LLM, deep learning, and statistical techniques for various ML problems, with a focus on multi-modal LLM Agents and task automation. The role also includes defining research strategies, partnering with business/engineering teams, and potentially publishing research or filing patents. | AgentPost-train | 8 |
| Data Scientist II, RBS Tech The Data Scientist II, RBS Tech role focuses on foundational ML research and developing scalable ML solutions for customer experience and selling partner experience. The role involves designing and deploying GenAI, NLP, and Computer Vision solutions, developing novel LLM, deep learning, and statistical techniques, and defining research strategies. Key areas include multi-modal understanding, task automation with LLM Agents, and improving product search results. The role also involves mentoring and potentially patent/publication contributions. | AgentPost-train | 8 |
| Applied Scientist, AWS Quick This role is for an Applied Scientist on the AWS Agentic AI team, focusing on building next-generation models for intelligent automation. The role involves defining and implementing automated reasoning features, applying software engineering best practices, and delivering high-quality scientific artifacts. The ideal candidate has experience in autonomous agents, API orchestration, planning, large multimodal models, reinforcement learning, and sequential decision making, with a strong publication record. | AgentPost-train | 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 |
| Applied Scientist, AWS Quick The AWS Agentic AI science team is looking for world-class researchers to build the next generation of intelligent automation models. The role involves developing innovative solutions for complex problems using autonomous agents, API orchestration, planning, large multimodal models (especially vision-language), reinforcement learning, and sequential decision making. Researchers are expected to publish their findings at peer-reviewed conferences and workshops, and apply software engineering best practices to ensure high-quality deliverables in an agile, startup-like environment. | Agent | 8 |
| Member of Technical Staff - Simulation, Frontier AI Robotics The role focuses on developing 3D physics-based and photorealistic simulations for training large-scale machine learning models in robotics. This involves creating simulations for reinforcement learning, generating synthetic data, implementing robotics features, and building real-to-sim workflows to minimize sim-to-real gaps. The goal is to support the training of foundation models for robotics. | DataPost-train | 8 |
| Applied Scientist II, Alexa Edge AI Applied Scientist II on the Alexa Edge AI team, focusing on deep learning and speech processing to develop novel ML algorithms for speech and audio. This role involves applied research, model design, training, and optimization for consumer products. | Post-train | 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 the potential for production impact. Collaboration with researchers and publication in top-tier conferences are key aspects. | Post-trainServe | 8 |
| Senior Applied Scientist , Prime Video Ads Senior Applied Scientist role focused on building and deploying ML models for personalizing advertising experiences on Prime Video. The role involves research and development across the ML lifecycle, from exploratory research to production deployment, with a focus on understanding heterogeneous customer responses, inferring preferences from indirect signals, and optimizing for competing objectives like revenue and customer engagement at massive scale. | ShipAgent | 8 |
| Postdoctoral Scientist, Amazon Robotics R&D Postdoctoral Scientist role in Amazon Robotics R&D focusing on computer vision and robotic manipulation for automating picking operations in fulfillment centers. The role involves developing ML solutions for robots to identify and interact with items in cluttered 3D scenes in real-time, with a focus on pushing research boundaries and deploying innovations to real warehouses. | ShipData | 8 |
| Senior Applied Scientist, Fauna This role focuses on developing evaluation frameworks and data collection protocols for robotic capabilities, operating at the intersection of robotics, machine learning, and human-in-the-loop systems. The scientist will design how to measure, stress-test, and improve robot behavior, build infrastructure connecting teleoperation, evaluation, and learning, and lead technical projects. | Eval GateAgent | 8 |
| Applied Scientist II, Amazon Quick This role focuses on developing innovative solutions for complex problems using autonomous agents, API orchestration, planning, large multimodal models (especially vision-language models), reinforcement learning, and sequential decision making. The candidate will define and implement new automated reasoning features, apply software engineering best practices, and publish findings at peer-reviewed conferences. The role is part of AWS and aims to solve real-world problems with access to significant data and computational resources. | Agent | 8 |
| Applied Scientist I Applied Scientist role focused on developing novel algorithms and modeling techniques for speech and language technologies (ASR, NLU, TTS, Dialog Management) impacting millions of customers. Requires ML background and programming experience, with preferred qualifications in AI/ML technologies, large-scale systems, and publications in top-tier conferences. | Post-train | 8 |
| Applied Scientist II, RBS Tech The Applied Scientist II, RBS Tech role focuses on foundational ML research and developing scalable ML solutions for customer experience (CX) and Selling Partner experience (SPX). The role involves designing and deploying GenAI, NLP, and Computer Vision solutions, developing novel LLM, deep learning, and statistical techniques for task automation, text and image processing, pattern recognition, and anomaly detection. It also includes defining research strategies, partnering with business and engineering teams, and potentially filing patents or publishing research. | AgentPost-train | 8 |
| Applied Scientist II, Alexa International Team Applied Scientist II role focused on developing and evaluating LLMs and multimodal systems for Alexa's international products. Responsibilities include analyzing customer behavior, building evaluation metrics, fine-tuning/post-training LLMs (SFT, DPO, RLHF, RLAIF), setting up experimentation, and contributing to research and production delivery. Requires strong ML, NLU, LLM architecture, and evaluation knowledge, with a focus on international customer nuances and diverse data sources. | Post-trainAgent | 8 |
| Applied Scientist II, Alexa International Team Applied Scientist II on the Alexa International Team at Amazon, focusing on developing novel algorithms and modeling techniques for Large Language Models (LLMs) and multimodal systems. The role involves fine-tuning/post-training LLMs, building evaluation metrics, and contributing to end-to-end delivery from research to production, impacting international customers with digital assistant technology. | Post-trainAgent | 8 |
| Applied Scientist II, Alexa International Team Applied Scientist II on the Alexa International Team at Amazon, focusing on developing novel algorithms and modeling techniques for Large Language Models (LLMs) and multimodal systems. The role involves fine-tuning/post-training LLMs, building evaluation metrics, and contributing to end-to-end delivery from research to production, impacting international customers with digital assistant technology. | Post-trainAgent | 8 |
| Senior Applied Scientist, Neuro-Symbolic AI Labs Research scientist role focused on developing neuro-symbolic AI systems that integrate proof assistants for enhanced learning and reasoning, applied across various Amazon domains. The role involves defining and implementing new applications, delivering scientific artifacts, and working in an agile environment. | Post-train | 8 |
| 2027 Applied Science Intern (Machine Learning, Recommender Systems), Amazon International Machine Learning Internship role focused on applying state-of-the-art Deep Learning, Recommender Systems, Information Retrieval, and NLP algorithms to large datasets for customer-facing products at Amazon. Involves developing novel solutions, building prototypes, contributing to research, and potentially delivering solutions to production. Collaboration with experienced scientists and opportunities for publication in top conferences. | Ship | 8 |
| Applied Scientist, Amazon Compliance and Safety Services Applied Scientist role focused on researching and developing NLP, multi-modal, and LLM-based ML solutions for product compliance and safety within Amazon. The role involves evaluating existing algorithms, designing new ones, generating synthetic data, and potentially using active learning and grounding LLMs for business use cases. Collaboration with engineers and product managers is key, with an emphasis on publishing research. | Post-trainData | 8 |
| Applied Scientist II, Prime Video - Personalization and Discovery Science This role focuses on developing and applying ML models, including foundation models, for recommendation and search systems within Prime Video's personalization and discovery science team. The goal is to enhance customer experience by recommending titles effectively and enabling discovery of niche interests. The role involves end-to-end ownership, experimentation, and collaboration with scientists, engineers, and product managers, with an emphasis on publishing research findings. | Ship | 8 |
| Applied Scientist II, RBS Tech The Applied Scientist II, RBS Tech role focuses on foundational ML research and developing scalable ML solutions for customer experience (CX) and Selling Partner experience (SPX). The role involves designing and deploying GenAI, NLP, and Computer Vision solutions, developing novel LLM, deep learning, and statistical techniques for task automation, text and image processing, pattern recognition, and anomaly detection. It also includes defining research strategies, partnering with business and engineering teams, and potentially filing patents or publishing research. | AgentPost-train | 8 |
| Applied Scientist II, RBS Tech The Applied Scientist II, RBS Tech role focuses on foundational ML research and developing scalable ML solutions for customer experience (CX) and Selling Partner experience (SPX). The role involves designing and deploying GenAI, NLP, and Computer Vision solutions, developing novel LLM, deep learning, and statistical techniques for task automation, text and image processing, pattern recognition, and anomaly detection. It also includes defining research strategies, partnering with business and engineering teams, and potentially filing patents or publishing research. | AgentPost-train | 8 |
| Applied Scientist II, Prime Video Personalization and Discovery Science Applied Scientist II at Amazon Prime Video focusing on personalization and discovery. The role involves developing foundation models for content understanding (video, text) and customer behavior prediction using deep learning and multimodal techniques. Responsibilities include building time sequence models, end-to-end solution implementation with engineers and product managers, designing and conducting A/B experiments, and publishing research findings. The team works on recommendation science for Prime Video surfaces and devices, aiming to solve cold-start problems and discover niche customer interests. | Post-trainAgent | 8 |