Currently tracking 995 active AI roles, up 64% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $196k).
| Title | Stage | AI score |
|---|---|---|
| Applied Scientist II, Amazon Business, Amazon Business - GTMO Science Applied Scientist II role at Amazon Business focused on revolutionizing sales productivity using AI-powered solutions. The role involves developing tools for Account Executives (AEs) to prioritize accounts, recommend products, and engage customers more effectively. It leverages machine learning and Generative AI to outreach customers based on their behavior and purchase history, and performs text mining on customer conversations to recommend solutions. The scientist will partner with product, tech, and sales teams to launch and scale global AI products, with a focus on improving customer experience and sales efficiency. | AgentData | 8 |
| Applied Scientist II, Amazon Business, Amazon Business - GTMO Science Applied Scientist II role at Amazon Business focused on revolutionizing sales productivity using AI-powered solutions. The role involves developing tools for Account Executives (AEs) to prioritize accounts, recommend products, and engage customers more effectively. It leverages machine learning and Generative AI to outreach customers based on their behavior and purchase history, and performs text mining on customer conversations to recommend solutions. The scientist will partner with product, tech, and sales teams to launch and scale global AI products, with a focus on improving customer experience and sales efficiency. |
| AgentData |
| 8 |
| Machine Learning Scientist / Applied Scientist, EU Prime and Marketing Analytics & Science (PRIMAS) This role focuses on developing and deploying 1P audience segments for Amazon's EU marketing campaigns, using causal inference and machine learning to measure incremental lift and optimize marketing spend. The goal is to move beyond platform-led optimization to more personalized customer experiences, building reusable frameworks for scalable experimentation and informing future marketing strategies. | Agent | 7 |
| Process Analyst, EU Central Operations Analytics This role focuses on designing and implementing AI-powered automation solutions and machine learning models for logistics operations, aiming to enhance route planning, scheduling, and delivery execution. The analyst will leverage advanced SQL, Python/R, and AI technologies to create intelligent dashboards, predictive models, and automated reporting systems, working at the intersection of operations, analytics, and automation to drive efficiency and scale across the network. | Agent | 7 |
| Data Engineer, Ring Agent Platforms Data Engineer role focused on building and operating data pipelines, models, and platform infrastructure for Ring's analytics, science, and AI initiatives. The role involves owning the data lifecycle and building multi-agent solutions to automate data engineering tasks, with contributions to the shared data platform. | AgentData | 7 |
| Senior Business Intelligence Engineer, EU Stores CX Analytics & Automation Senior Business Intelligence Engineer focused on building and scaling personalized recommendations for millions of customers in EU marketplaces. The role involves developing custom models (embeddings, persona matching) using Python and Spark, building production-grade Python services, serverless infrastructure (AWS Lambda, CDK), and APIs (FastAPI) for marketing teams. It also includes owning reporting, measurement, and deep-dive analytics for personalized marketing campaigns. | AgentData | 7 |
| Applied Scientist, EU INTech Consumer Selection Discovery, Tamale Applied Scientist role focused on building GenAI-powered data solutions, agentic systems for quality issue detection, and ranking/recommendation models for e-commerce. The role involves designing, developing, testing, and deploying scalable ML solutions, working with state-of-the-art models like LLMs and image-to-text. | AgentServe | 7 |
| Sr. Applied Scientist, Amazon Books This role focuses on developing and implementing novel algorithms and agentic systems at the intersection of AI, LLMs, NLP, search, and deep learning for the Amazon Books team. The goal is to advance the state-of-the-art and build technologies that enhance customer discovery experiences for millions of users. | Agent | 7 |
