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 |
|---|---|---|
| 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 & 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 |
| 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 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 |
| 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 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, 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 |
| 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 |
| 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 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 |
| 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 |
| Sr. Applied Scientist, Prime Video - Personalization and Discovery Science Senior Applied Scientist role focused on developing and launching foundation models for content understanding and customer behavior prediction within Prime Video. The role involves hands-on machine learning, research leadership, and end-to-end ownership of solutions, with an emphasis on publishing research findings. | Post-trainAgent | 8 |
| Applied Scientist II, Amazon Connect Research and develop generative AI technology for Amazon Connect, focusing on LLM Agents and their evaluation/optimization to disrupt customer service experiences. The role involves building ML models from conception to deployment, prototyping, and iterating on state-of-the-art Agentic AI systems. | AgentPost-train | 8 |
| Applied Scientist II The role focuses on developing and applying cutting-edge simulation methodologies for advanced robotics systems, including physics-based simulation, sim-to-real transfer, and machine learning. The goal is to enable rapid development, testing, and validation of robotic systems in complex environments. The role involves fundamental research and real-world development, translating research into scalable simulation capabilities that impact robot design and building. | DataAgent | 8 |
| Applied Scientist II, Reinforcement Learning Applied Scientist II role focused on developing advanced robotics systems using AI, deep learning, and reinforcement learning for automation at Amazon's scale. The role involves designing and implementing control methods for balance, locomotion, and manipulation, with a focus on bridging theoretical advancements and practical implementation in robotics. | Ship | 8 |
| Applied Scientist, AGI , AGI Information This role focuses on advancing knowledge graphs for the LLM era, specifically for LLM grounding and construction pipelines. It involves web-scale knowledge mining, fact verification, multilingual information retrieval, and agent memory over graphs. The primary responsibility is entity resolution for conflating facts from multiple sources into a single graph entity, requiring scalable, generic, and streaming data solutions. The role also touches upon agent memory, suggesting a secondary stage involvement. | DataAgent | 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 of solutions impacting international customers. | Post-trainAgent | 8 |
| 2026 Fall Applied Science Internship - Information & Knowledge Management (Machine Learning) - United States, PhD Student Science Recruiting This internship focuses on developing systems and frameworks for machine learning asset lifecycle management, leveraging NLP and information retrieval. The role involves research into ML operations and knowledge engineering to enhance Amazon's ML capabilities. | DataPost-train | 8 |
| 2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - United States, PhD Student Science Recruiting This internship focuses on research in Reinforcement Learning and Optimization within Machine Learning, developing and implementing novel algorithms for complex real-world challenges. The role involves working with large-scale data and applying cutting-edge ML techniques. | Post-train | 8 |
| Sr. Applied Scientist, Prime Video - Personalization and Discovery Science This role focuses on developing and launching end-to-end AI solutions for Prime Video's recommendation and personalization systems. It involves deep learning, GenAI, reinforcement learning, and optimization methods, with a strong emphasis on experimental design (A/B testing) and research publication. The scientist will work closely with engineers and product managers to bring these solutions to millions of customers. | Ship | 8 |
| Data Scientist, Demand Forecasting Research Scientist role focused on building and deploying large-scale foundation models for demand forecasting at Amazon. The role involves designing experiments, developing deep learning and statistical models, and analyzing large datasets to improve forecasting accuracy and downstream business impact. Emphasis on research rigor, production deployment, and scientific contribution. | Post-train | 8 |
| Applied Scientist, Last Mile Delivery Automation This role focuses on developing AI and ML solutions for last mile delivery automation, combining expertise in machine learning, computer vision, and robotics to solve complex challenges in perception, navigation, and path planning. The scientist will research, design, and implement algorithms, transforming research concepts into production-ready solutions for autonomous systems. | ShipAgent | 8 |
| Applied Scientist , Amazon Applied Scientist role at Amazon focusing on improving shopping experiences using LLMs. The role involves post-training of LLMs, including instruction tuning, reward modeling, and reinforcement learning. Responsibilities include designing and running large-scale experiments, analyzing model behavior, and developing new training recipes to enhance capabilities like reasoning and user experience. Requires a PhD or Master's with significant experience, practical LLM experience, and a strong publication record. | Post-trainPretrain | 8 |
| Applied Scientist, Console Science The Applied Scientist will work on building industry-leading Conversational AI Systems, focusing on Natural Language Understanding, Dialog Systems, Generative AI with LLMs, and Applied Machine Learning. The role involves developing novel algorithms and modeling techniques to advance human language technology, impacting millions of customers through products and services. The scientist will gain hands-on experience with Amazon's text, structured data, and large-scale computing resources. | Post-trainAgent | 8 |
| Applied Scientist II, Foundation Model, Industrial Robotics Group Applied Scientist II role focused on developing foundation models for industrial robotics, integrating multi-modal learning, skill acquisition, perception, and environmental understanding. The role involves leveraging, adapting, and optimizing state-of-the-art models, conducting rigorous experimentation, building evaluation benchmarks, and contributing to data and training workflows. It requires strong programming skills in Python and experience in deep learning areas like computer vision, multimodal models, or RL for robotics. | Post-trainAgent | 8 |
| Applied Scientist, Last Mile Delivery Automation Applied Scientist role focused on developing AI/ML solutions for Last Mile Delivery Automation, combining expertise in machine learning, computer vision, and robotics for perception, navigation, and path planning. The role involves transforming research into production-ready solutions and collaborating with engineering teams. | AgentServe | 8 |
| 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 |
| 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 |
| 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 |
| 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 |
| Sr. Applied Scientist, Global Hiring Science This role focuses on applying machine learning and AI to reinvent the hiring process at Amazon, aiming for scale, sophistication, and accuracy in talent acquisition. The scientist will work on state-of-the-art research, advanced software tools, new AI systems, and ML algorithms, leveraging Amazon's tech stack to deliver innovative solutions for hiring. | Ship | 7 |
| Applied Scientist, SCOT Forecasting and Labs - CIV Team Applied Scientist role focused on developing and prototyping new statistical, causal, and machine learning techniques for inventory availability and delivery speed estimations in Amazon's retail supply chain. The role involves collaborating with software teams for production implementation and analyzing business metrics. | Post-train | 7 |
| Applied Scientist, Pricing Science Applied Scientist role focused on developing and launching customer-obsessed improvements to pricing algorithms for billions of Amazon products, leveraging large-scale multi-modal datasets and predictive modeling, causal evaluation, and optimization techniques. | Ship | 7 |
| Research Scientist, Safety-Critical Control, Robotics, SAF Lab Research Scientist focused on developing Control Barrier Function (CBF) theory and algorithms for safety-critical control in robotics. The role involves creating algorithms with formal safety guarantees, integrating them with learned control policies, and deploying them on next-generation robots. Key responsibilities include developing novel CBF algorithms, framing safety filtering within layered architectures involving learning-based components, designing multi-layer CBF filters, and formalizing the interplay between models and system dynamics. The role also requires implementing real-time optimization solvers, validating algorithms through simulation and hardware experiments, and contributing to theoretical foundations through publications. Collaboration with various teams and product leaders is essential for setting a science roadmap. | ShipServe | 7 |
| Applied Scientist, Amazon Redshift Research scientist to build deep learning models for predicting query resource consumption in Amazon Redshift, covering the full ML lifecycle from data analysis to production deployment and publication. | Post-trainServe | 7 |
| Applied Scientist, Prime Video - Content Localization, Understanding & Enrichment This role focuses on research and development of speech and audio generation technology, including end-to-end speech-to-speech architecture and audio processing solutions. The scientist will define research roadmaps, publish findings, and develop deep learning algorithms, with a focus on computer vision algorithms. The role involves building models for business applications and potentially mentoring/hiring other scientists. | Post-trainData | 7 |
| Applied Scientist II, Customer360 Research and develop new AI technologies for personalization using recommendations, information retrieval, and large language models. Build large-scale ML solutions for customer experiences. | Ship | 7 |