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 |
|---|---|---|
| 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 |
| Delivery Consultant- AI/ML, WWPS ProServe Delivery Team This role focuses on designing, implementing, and scaling AI/ML solutions for enterprise customers on AWS, with a strong emphasis on generative AI. The consultant will work with customers to identify use cases, select, fine-tune, and deploy models, and provide technical guidance throughout the project lifecycle. | Post-train |
| 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, 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 |
| Data Scientist II, Amazon Currency Convertor Data Scientist II at Amazon Payments focused on building analytical solutions for the Amazon Currency Convertor using Gen AI, LLM, and other machine learning techniques for text analytics, segmentation, and prediction. Responsibilities include applying causal inference, developing descriptive and predictive solutions, collaborating with stakeholders, innovating with modeling techniques, performing exploratory data analysis, and building models using standard techniques. Specific tasks involve fine-tuning Amazon LLMs for text summarization, preventing catastrophic forgetting, feature engineering, and implementing data flow solutions. | Post-train | 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 |
| AI Editor, Alexa for Shopping Content and Marketing Experiences This role focuses on improving AI model fluency through human-in-the-loop evaluations and LLM judge audits, developing prompting strategies, creating alignment data for LLMs in shopping use cases, and identifying/mitigating biases through fine-tuning. It involves cross-functional collaboration with Product, Science, and Design teams to enhance customer experience metrics and ensure model improvements for Alexa for Shopping. | Post-trainAgent | 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 |
| Data Scientist II, Long Term Planning and Forecasting This Data Scientist II role focuses on building scientific tooling for how business customers interact with Long-Term Planning and Forecasting (LTPF) forecasts and plans. The role involves developing causal inference models, automated explainability frameworks, and variance bridging methodologies. It also includes building GenAI-powered narrative generation capabilities and automated hypothesis ranking to synthesize quantitative variance outputs into human-readable performance summaries and identify drivers of forecast error. The position emphasizes leading cross-functional programs, defining multi-year strategy, and leveraging insights for strategic decision-making. | Post-trainData | 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 |
| Sr. Design Technologist, Prime Video - AI Content Generation This role bridges generative AI research and visual storytelling for Prime Video, focusing on translating ML capabilities into production workflows and understanding creative needs. The Sr. Design Technologist will assess generative models, build proof-of-concept tools, and identify gaps between model output and production requirements. | Post-train | 7 |
| Sr Applied Scientist, Sponsored Products and Brands Ads Response Prediction This role focuses on developing and deploying machine learning models for Amazon's Sponsored Products and Brands Ads, aiming to improve customer experience and advertiser effectiveness. The scientist will conduct data analysis, build and optimize ML models, run A/B experiments, and collaborate with engineers to productionize solutions. They will also research new ML modeling techniques to enhance business outcomes. | Post-train | 7 |