Zoom is looking for a Machine Learning Engineer to join the Agentic Retrieval team, designing and building core retrieval and reasoning systems for Zoom's AI Companion. The role involves developing scalable retrieval systems, RAG pipelines, and ranking models to power AI agents across enterprise knowledge.
Responsibilities
Designing and implementing scalable retrieval systems including vector search, hybrid search, and structured query planning.
Designing and optimizing RAG pipelines for multi-step, tool-using AI agents.
Developing ranking, relevance modeling, and evaluation frameworks to improve search quality.
Building indexing pipelines that transform heterogeneous enterprise data into unified representations.
Building entity extraction and NLP pipelines for agentic reasoning over enterprise content.
Partnering with product, infrastructure, and applied research teams to ship production-grade AI capabilities.
Requirements
Master's degree or higher in Computer Science, AI, Machine Learning, or related field.
5+ years of experience in machine learning, search infrastructure, information retrieval, or distributed systems.
Strong hands-on experience building and operating large-scale search or data platforms in production.
Experience building or integrating RAG systems and LLM-based applications in production.
Zoom is an American communications technology company known for its video conferencing platform. It provides tools for online meetings, webinars, chat, and business telephone systems.