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 |
|---|---|---|
| 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 |
| 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-LLM, Buy For Me Seeking an Applied Scientist with expertise in AI, Agentic LLMs, Generative AI, Machine Learning, and NLP to build LLM-powered solutions for Amazon's BuyForMe product. The role involves developing agentic frameworks, LLM fine-tuning, reinforcement learning, prompt engineering, RAG, MCP, and automated benchmarking to improve shopping workflows. | AgentPost-train | 8 |
| Senior Applied Scientist, Last Mile Delivery Senior Applied Scientist role focused on developing computer vision and perception systems for AI agents in last-mile delivery logistics. The role involves designing and implementing deep learning models for visual perception, building algorithms for decision-making, and creating robust systems for AI agents to operate safely in complex environments. It spans from object detection and tracking to path planning and control, including sim-to-real transfer and continuous learning from agent experiences. | AgentServe | 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 |
| Principal Applied Scientist, PXT This role leads the science strategy and technical vision for an intelligence layer using GenAI and predictive modeling, focusing on heterogeneous signals to power talent applications at Amazon scale. The Principal Applied Scientist will guide a team, conduct hands-on research in areas like foundation models and multi-modal LLMs, design novel ML architectures, and mentor scientists while contributing technically to complex problems. | Post-trainAgent | 8 |
| Senior Manager, Research Science, WW Stores Finance, WW Stores Finance This role leads the science function in WW Stores Finance, driving AI/ML innovations in financial analytics. The leader builds and directs a multidisciplinary team to deliver scalable solutions, translating AI capabilities into production systems. The role requires strategic vision and execution excellence to transform finance operations, automate workflows, and improve forecasting and controllership through agentic AI, ML, and generative AI. | AgentShip | 8 |
| Sr. Applied Scientist, Special Projects This role is for a Sr. Applied Scientist on an Amazon Special Projects team focused on creating new products and services. The role involves leading research projects from ideation to production, driving ML/AI strategy, collaborating cross-functionally, publishing findings, and establishing best practices for ML experimentation and deployment. Requires a PhD or Master's with significant applied research experience, strong programming skills, and experience with ML/LLM fundamentals and deploying ML systems at scale. Experience with autonomous AI frameworks and translating research into production systems is preferred. | ShipServe | 8 |
| Principal Applied Scientist, Data Center Design Engineering - BIM & AI Technologies Principal Applied Scientist role focused on AI-powered design automation for AWS data centers. The role involves defining research roadmaps, developing and deploying ML models (including fine-tuning foundation models, GNNs, NLP, RL, CV) for BIM and AECO applications, and publishing research findings. It requires a blend of theoretical ML knowledge and practical application in a domain with high trust requirements. | Post-trainAgent | 8 |
| Applied Scientist, Customer360 This role focuses on researching, designing, and developing new AI technologies for personalization, leveraging LLMs, Information Retrieval, and Recommendation Systems to create unified customer understanding across Amazon's diverse businesses. The goal is to revolutionize customer experiences with AI-powered personalization and set new industry standards. | ShipAgent | 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, Traffic Quality Applied Scientist II role focused on detecting sophisticated invalid traffic (IVT) in advertising using deep learning, self-supervised techniques, representation learning, and advanced clustering. The role involves defining research problems, inventing ML approaches, designing and deploying production-quality ML components, and working with massive datasets. It also requires producing research reports and contributing to the scientific community through publications. | 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 of solutions impacting international customers. | 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 |
| 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 |
| Applied Scientist, Amazon Compliance and Safety Services Research Scientist role focused on applying and extending state-of-the-art research in NLP, multi-modal modeling, domain adaptation, continuous learning, and large language models to improve product compliance and safety at Amazon. The role involves researching and evaluating algorithms, designing new algorithms for business impact (e.g., synthetic data generation, active learning, grounding LLMs), and collaborating with engineering and product teams to implement ML solutions across the product catalog. The team specializes in image and document understanding for compliance capabilities, with a focus on publishing research. | Post-train | 8 |
| Applied Scientist , AWS Healthcare-AI Senior Applied Scientist role at AWS Healthcare AI, focusing on developing and researching AI-driven clinical solutions to transform healthcare delivery. The role involves defining research directions, developing new ML techniques, and ensuring research translates into impactful products for clinicians and patients. Requires a PhD or Master's with significant experience in ML, NLU, deep learning, foundation models, and RL, with a strong publication record. | ShipPost-train | 8 |
| Applied Scientist (Fixed Term Contract), Amazon Music AI and Personalization Research scientist role focused on developing novel machine learning solutions for music and podcast recommendations within Amazon Music. The role involves implementing and validating ideas through A/B testing, producing innovative research for peer-reviewed publications, and building scalable models. It requires a PhD or Master's degree and experience in deep learning, ML, or NLP, with a focus on recommender systems. | ShipPost-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 |
| Sr. Applied Science Manager, AGI Information This role leads teams of applied scientists and ML engineers to develop and deliver AI systems for Amazon businesses, focusing on integrating information into AI systems using techniques like RAG. The role involves defining technical roadmaps, mentoring teams, and driving research from conception to production, with a strong emphasis on building impactful AI-driven products and services. | Ship | 8 |
| Senior Applied Scientist, Personalization, Personalization Strategic Initiatives Science Senior Applied Scientist role focused on research, design, and development of new AI technologies for personalization, including recommendation systems and large language models. The role involves inventing, experimenting with, and launching new features, products, and systems that impact millions of customers. | ShipPost-train | 8 |
| Applied Scientist, Personalization, Personalization Strategic Initiatives Science Research Scientist role focused on developing and launching new AI technologies for personalization, leveraging large datasets and computational resources to build large-scale machine learning solutions for customer recommendations. The role involves inventing, experimenting with, and launching new features, products, and systems, with a strong emphasis on research publications. | ShipPost-train | 8 |
| Applied Scientist Intern, 2026 Shenzhen This internship focuses on bridging cutting-edge AI research with practical application and communication. The intern will translate complex AI concepts into understandable content for business stakeholders and the wider community, document AI capabilities, develop internal AI literacy programs, and contribute to applied research projects in NLP, Computer Vision, or Multimodal AI. The role requires a strong foundation in ML/DL, Python, and ML frameworks, with a passion for science communication and a curious, open mindset. | Post-trainAgent | 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 at Amazon. The role involves evaluating state-of-the-art algorithms, designing new ones, generating synthetic data, and improving grounding of LLMs for business use cases. It requires collaboration with engineers and product managers, and publishing research. | Post-trainData | 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 at Amazon. The role involves evaluating state-of-the-art algorithms, designing new ones, generating synthetic data, and improving grounding of LLMs for business use cases. It requires collaboration with engineers and product managers, and publishing research. | Post-trainData | 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 |
| 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, PRG (Personal Robotics Group) This role focuses on researching and developing advanced navigation systems for intelligent robotic products, utilizing a spectrum of approaches from classical methods to learning-based techniques and foundation models. The primary goal is to enable robots to move reliably and safely in complex, dynamic environments, with a strong emphasis on sim-to-real transfer and evaluation frameworks. | AgentData | 8 |
| Applied Scientist II, Alexa AI Applied Scientist II at Amazon Alexa AI focused on prototyping, optimizing, and deploying ML algorithms in Generative AI. Responsibilities include research, building PoCs, collaborating with teams, technical communication, documentation, and publishing research. | Post-train | 8 |
| Applied Scientist, Sales AI This role focuses on building AI/ML solutions for the Ad Sales business, specifically creating customer-facing recommendations and enhancing end-to-end workflows with Generative AI. The scientist will leverage quantitative modeling techniques like Sequential Recommender Systems, Deep Learning, and Reinforcement Learning, and use NLP and Generative AI for explainability. The role involves research, model development, A/B testing, and collaboration with engineering and product teams to deliver production-ready solutions. | AgentPost-train | 8 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship focused on machine learning, deep learning, generative AI, LLMs, speech, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. The role involves designing and developing end-to-end systems, writing technical white papers, creating roadmaps, and driving production-level projects. Interns will work closely with scientists to develop and deploy solutions, design new algorithms and models, and potentially publish work at top-tier conferences. | Ship | 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 |
| Sr. Applied Scientist, AWS Healthcare-AI Senior Applied Scientist at AWS Healthcare AI focused on developing and researching AI-driven clinical solutions to transform patient-clinician interaction and care documentation. The role involves leading research, developing new ML techniques, and ensuring research translates into impactful products, with a focus on generative AI experiences. | ShipPost-train | 8 |
| Sr Manager Research Science, Last Mile Science and Analytics This role focuses on applying AI and machine learning to optimize Amazon's last-mile delivery network. Responsibilities include developing sophisticated ML models for logistics, forecasting, and resource allocation, architecting AI-powered systems, implementing deep learning for image recognition, and developing reinforcement learning for adaptive scheduling. The role also involves designing AI agents for autonomous decision-making and creating models for customer behavior analysis. A strong emphasis is placed on research, publishing findings, and leveraging big data and cloud platforms. | AgentData | 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 |
| Personal Robotics Group - Applied Scientist II Intern / Co-op - 2026 (Robotics, Manipulation, Locomotion, Controls, Reinforcement Learning, Perception, Manipulation, Planning, HRI and more) PhD intern/co-op role in Amazon's Personal Robotics Group focusing on research and development of intelligent robotic products, including Amazon Astro. The role involves working on the full spectrum of robotics, from hardware design to software and control systems, with a focus on manipulation, locomotion, and human-robot interaction. Requires a PhD in a relevant field and experience in programming languages like Python, C++, or Java. | ShipAgent | 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 |
| Applied Scientist II, Business Data Technologies This role focuses on designing and deploying GenAI, NLP, and Computer Vision solutions for Amazon's retail business services, aiming to enhance customer experience and operational efficiency. The scientist will develop novel ML techniques for task automation, text and image processing, and anomaly detection, with a strong emphasis on LLM Agents and multi-modal understanding. | AgentPost-train | 8 |
| Applied Scientist II, Amazon Smart Vehicles The Amazon Smart Vehicles (ASV) science team is seeking an Applied Scientist with expertise in advanced LLM technologies to create personalized services for drivers and passengers, enhancing their experience on the road. The role involves innovating in AI research, developing novel algorithms, and applying theoretical models in an applied environment, with direct application to Amazon products. The scientist will leverage Amazon's data and computing resources to advance generative AI and work closely with other teams to drive impact. | Agent | 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 |
| Applied Scientist The AWS Neuron Science Team is seeking scientists to enhance their software stack for ML accelerators (Trainium and Inferentia). The role involves working with customers to identify adoption barriers, collaborating with engineering teams on solutions, and advancing ML systems. Key areas include AI for Systems (kernel/code generation), ML Compiler techniques, System Robustness, and Efficient Kernel Development. | Serve | 8 |
| Senior Applied Scientist, 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 |
| Research Scientist, SSG Science Research Scientist role focused on developing and optimizing Generative AI models for edge devices, involving model compression techniques, custom ML hardware, and theoretical understanding of deep learning and information theory. The role involves co-authoring research papers and collaborating with cross-functional teams. | ServePost-train | 8 |
| Robotics - Applied Scientist II Intern / Co-op - 2026 (Robotics, Manipulation, Perception, Motion Planning, Autonomous Mobile Robots, Computer Vision, Machine Learning, Controls, and more) This role is for a PhD student intern/co-op focused on robotics research, specifically in areas like manipulation, perception, motion planning, and autonomous mobile robots. The role involves applying machine learning, computer vision, and potentially LLMs to solve real-world robotics problems, with a focus on developing research prototypes and seeing them through from concept to working prototype. The work touches on data collection/preparation for training and research. | AgentData | 8 |
| Sr. Applied Science , AWS Agentic AI This role focuses on building next-generation models for intelligent automation within AWS Agentic AI. The scientist will develop innovative solutions for complex problems, focusing on areas like autonomous agents, API orchestration, planning, large multimodal models (especially vision-language), reinforcement learning, and sequential decision making. The role involves partnering with technology and business teams, utilizing extensive data and computational resources, and collaborating with engineers. There's an expectation to publish findings at peer-reviewed conferences. | Agent | 8 |