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 |
| Applied Scientist - LLM, Alexa Conversational Modelling Intelligence Applied Scientist II in Alexa Conversational Modelling Intelligence team focused on LLM post-training (SFT, RLHF, preference optimization) for Alexa+. Drives model development from data curation through training, evaluation, and deployment. Builds evaluation frameworks, diagnoses defects, and iterates on recipes. Collaborates with scientists and engineers, contributes to tooling, and publishes research. Aims to improve customer experience for millions. |
| Post-trainServe |
| 9 |
| 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 |
| Senior Applied Scientist, Alexa AI Senior Applied Scientist role focused on defining and driving the science roadmap for conversational AI systems using LLMs, impacting millions of customers. Responsibilities include designing LLM fine-tuning, alignment, and agentic architectures, owning end-to-end delivery from research to production, developing evaluation frameworks, and collaborating with cross-functional teams. The role involves publishing at top-tier conferences and generating intellectual property. | AgentPost-train | 9 |
| Member of Technical Staff, Artificial General Intelligence The AGI team is looking for a Member of Technical Staff to build industry-leading Generative AI (GenAI) technology with LLMs and multimodal systems. This role involves leading foundational model development in an applied research capacity, including model training, dataset design, and pre- and post-training optimization, leveraging Amazon's resources to advance LLMs and impact customer-facing products and services. | PretrainPost-train | 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 II Applied Scientist II at Amazon focusing on Speech and Language technology, including ASR, NLU, MT, TTS, Dialog Management, and CV. The role involves developing novel algorithms and modeling techniques to advance the state-of-the-art and impact millions of customers through large-scale systems. | Post-train | 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 |
| Sr. Applied Scientist, Trust CX Innovations&AI Policy Senior Applied Scientist role focused on Generative AI, LLMs, and multimodal models for Alexa+, emphasizing AI trust, privacy, safety, and alignment. The role involves leading research, developing optimization techniques, pioneering responsible AI methods, and collaborating with product and engineering teams to deliver production-ready AI solutions. | Post-trainAgent | 9 |
| Applied Scientist, Alexa International Tech Applied Scientist role focused on developing Generative AI (GenAI) technology with LLMs and multimodal systems, specifically for speech generation to make Alexa more natural, expressive, and culturally relevant across multiple languages. The role involves research, algorithm development, experimentation, publishing findings, and collaborating with engineering teams to productionize models. | Post-trainServe | 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, Alexa Edge AI Applied Scientist role focused on designing, developing, and deploying multimodal ML models (CV, audio, speech) for edge and cloud deployment. The role involves full ML lifecycle ownership, research, and contributing to publications. It's a founding member position in a new Bangalore site, requiring collaboration with engineers and scientists to productionize algorithms. | Post-trainServe | 9 |
| Applied Scientist, Alexa Edge AI Seeking an Applied Scientist to design, develop, and deploy state-of-the-art ML models for computer vision, audio, and multimodal understanding for edge and cloud deployment. This role involves full ML lifecycle ownership, research, and contributing to publications, with an opportunity to be a founding member of a new site. | Post-trainServe | 9 |
| Applied Scientist, Alexa Edge AI This role focuses on researching and developing next-generation machine learning models for computer vision, audio processing, and multimodal semantic understanding, with a strong emphasis on defining the science roadmap, delivering scalable solutions, and publishing research. The role involves technical leadership, end-to-end ownership of ML programs, and mentorship. | Post-trainServe | 9 |
| Applied scientist, Agentic AI, AWS Agentic AI Research scientist role focused on building next-generation models for intelligent automation using autonomous agents, API orchestration, large multimodal models (especially vision-language), and reinforcement learning within AWS. | Agent | 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 |
| 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 leveraging RL/IL, integrating with hardware, using simulation and real-world testing, and leading projects from conception to deployment within Amazon's Fauna Robotics team. | ShipData | 9 |
| Applied Scientist II, Foundation Model, Robotics This role focuses on developing and improving machine learning systems for advanced robotics, leveraging and adapting state-of-the-art foundation models, and inventing new algorithms. The primary output is agentic robotic systems, with a secondary focus on data and training workflows. | AgentData | 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 |
| Member of Technical Staff, 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 responsibilities include driving research initiatives across the robotics stack, designing novel deep learning architectures, guiding technical direction for full-stack robotics projects, and collaborating with platform and hardware teams. The role emphasizes developing breakthrough foundation models and full-stack robotics systems that enable robots to perceive, understand, and interact with the world. | AgentPost-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 |
| Senior Applied scientist, Agentic AI, AWS Agentic AI Research scientist role focused on building next-generation models for intelligent automation using autonomous agents, API orchestration, multimodal models, and reinforcement learning within AWS. | Agent | 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 |
| Applied Scientist Gen AI - Amazon Advertising, CreativeX Applied Scientist role focused on developing novel AI Agent architectures and multi-modal Generative AI models (audio, images, videos) for advertisers within Amazon Advertising's CreativeX team. The role involves research, development, and productionization of these models, with an emphasis on agent evaluation, LLM/VLM fine-tuning, and reinforcement learning. | 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 |
| Sr. Applied Scientist, Enterprise Security Products Senior Applied Scientist role focused on building AI-first security products. The role involves defining the science vision, inventing and building novel ML solutions (including agentic architectures and RAG systems), tackling ambiguous security challenges, and shipping end-to-end solutions. It requires staying ahead of advancements in foundation models and agentic AI, and influencing across the organization. The role emphasizes research rigor, rapid prototyping, and influencing the team's culture and scientific practices. | AgentPost-train | 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 |
| Applied Scientist, Trust CX Innovations&AI Policy Research-focused Applied Scientist role at Amazon working on generative AI for Alexa, focusing on LLMs, multimodal models, AI safety, alignment, and responsible AI. The role involves developing innovative solutions, optimizing models, evaluating performance, and leading the development of production-ready AI solutions, with a strong emphasis on research publications and patents. | Post-trainAgent | 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 II, Alexa International Applied Scientist II at Amazon Alexa International focusing on developing and applying LLMs and multimodal systems for multi-lingual applications. The role involves research, fine-tuning/post-training LLMs, building evaluation metrics, and driving scientific strategy from research to production, impacting global customers. | Post-trainShip | 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 |
| Principal Applied Scientist , Personalized Autonomy and Proactive Intelligence (PAPI) This role focuses on leading research and development for next-generation proactive and autonomous agentic experiences within Alexa AI. The Principal Applied Scientist will guide a team in leveraging state-of-the-art ML, NLP, LLM training, and agentic AI systems to advance autonomous intelligence and proactive user assistance. Key responsibilities include identifying research directions, developing novel agent solutions, translating research into production, and influencing partner teams to launch AI-powered autonomous agents. The role aims to transform user interaction with Alexa by enabling proactive anticipation of needs, autonomous task execution, intelligent reasoning, continuous learning, and seamless coordination across domains. | Agent | 9 |
| Applied Scientist II, Alexa Sensitive Content Intelligence (ASCI) This role focuses on building AI safety systems for conversational AI, specifically for Alexa. It involves pioneering solutions in Responsible AI, training models for safety standards, designing automated testing for vulnerabilities, creating intelligent evaluation systems, building models to understand human values, and crafting feedback mechanisms. A key aspect is building AI agents for real-time detection and fixing of production issues. The role emphasizes frontier research with real-world impact, focusing on training truthful and grounded models, building reward models for human values, and creating automated systems to discover and address issues. Collaboration with scientists, PMs, and engineers is expected to transform ideas into production systems. The role also involves leading certification processes, advancing optimization techniques, building human-like evaluation systems, and mentoring others. | Post-trainEval Gate | 9 |
