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, 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, 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 |
| Senior Audio Applied Scientist, Edge Technology Senior Applied Scientist role focused on audio processing for Echo devices, involving research, development, and commercialization of spatial audio and music processing technologies. Requires expertise in signal processing and C/C++, with preferred experience in ML applications for audio. | Post-trainServe | 7 |
| Applied Scientist, Prime Video - Content Localization, Understanding & Enrichment Applied Scientist role at Amazon Prime Video focusing on content localization, understanding, and enrichment. The role involves applying NLP and computer vision research to video content, leading a team of applied scientists, and developing roadmaps for research. Requires experience building models for business applications and implementing deep learning algorithms, particularly in computer vision. | Post-train | 7 |
| Applied Scientist, Prime Video - Content Localization, Understanding & Enrichment Applied Scientist role at Amazon Prime Video focusing on content localization, understanding, and enrichment. The role involves applying NLP and computer vision research to video content, leading a team of applied scientists, and developing roadmaps for research. Requires experience building models for business applications and implementing deep learning algorithms, particularly in computer vision. | Post-train | 7 |
| Language Data Scientist, Alexa International This role focuses on analyzing and evaluating conversational interaction data to support the training and evaluation of LLMs and machine learning models for Alexa's speech interfaces. The Language Data Scientist will own data analysis, research requests, and contribute to developing annotation workflows and evaluation conventions. | Post-trainEval Gate | 7 |
| Applied Scientist, Shopping Convo Foundations - Pre-purchases Science Research and develop novel ML approaches for catalogue expansion and product attribute challenges, translating scientific breakthroughs into production-ready solutions at Amazon scale. | Post-train | 7 |
| Senior Computational Biologist, Special Projects Senior Computational Biologist role focused on developing advanced computational methods and predictive models for complex, multi-modal datasets in the healthcare space. The role involves building interpretable models, integrating diverse data sources, and uncovering actionable insights, operating within an entrepreneurial and rapidly evolving environment. | Post-train | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship focused on research in machine learning, deep learning, generative AI, LLMs, speech, robotics, computer vision, optimization, OR, quantum computing, automated reasoning, or formal methods. The role involves designing and developing end-to-end systems, writing technical papers, creating roadmaps, and driving production-level projects. Experience with publications at top-tier conferences and solving business problems with ML/data mining/statistical algorithms is preferred. | Post-train | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech, robotics, vision, optimization, OR, quantum computing, automated reasoning, or formal methods. Focus on designing and developing end-to-end systems, writing technical white papers, creating roadmaps, and driving production-level projects. Opportunity to design new algorithms and models, deploy solutions into production, and potentially publish work. | Post-train | 7 |