Staff Machine Learning Engineer

What you can expect Zoom is building the next generation of AI Companion, powered by Agentic Retrieval — a unified intelligence layer that enables AI agents to securely search, reason over, and act on enterprise knowledge at scale. In this role, you’ll design and develop the core retrieval and reasoning systems driving AI-powered workflows across meetings, chat, docs, and enterprise apps. This is a high-impact opportunity to shape Zoom’s AI foundation and advance how enterprises access and use knowledge. About the Team The Agentic Retrieval team within Zoom’s GenAI Engineering group builds a multi-tenant, permission-aware retrieval platform. It powers large-scale document and data search. The team also focuses on enterprise knowledge graph reasoning and retrieval orchestration for AI agents. We operate at the intersection of distributed systems, machine learning, knowledge representation, and large language models. Our mission is to enable AI agents to access the right information, with the right permissions, at the right time — across enterprise data sources. Responsibilities: Designing and building scalable retrieval systems using vector and semantic search for unstructured data, hybrid keyword-embedding search, enterprise data analytics, and graph-based reasoning. Designing and optimize Retrieval-Augmented Generation (RAG) pipelines for multi-step, tool-using AI agents. Building indexing pipelines that transform heterogeneous enterprise data into unified retrieval-ready representations. Developing ranking, relevance modeling, and evaluation frameworks to improve answer quality and grounding. Working on permission-aware retrieval to ensure secure, multi-tenant isolation and fine-grained access control. Partnering closely with product, infrastructure, and applied research teams to ship production-grade AI capabilities. What we’re looking for: 5+ years of experience in machine learning, search infrastructure, information retrieval, distributed systems, or related areas. Demonstrate hands-on experience building and operating large-scale search, recommendation, or data platforms in production environments. Possess understanding of:Information retrieval, Structured query systems, Knowledge graph or graph database concepts Have experience building or integrating RAG systems and LLM-based applications in production. Possess proficiency in one or more of: Python, Go, Java, C#, or C++. Have experience with modern ML frameworks (e.g., PyTorch, TensorFlow) and vector databases or search engines. Have experience working with enterprise data systems or multi-tenant SaaS environments is a plus. Salary Range or On Target Earnings: Minimum: Maximum: In addition to the base salary and/or OTE listed Zoom has a Total Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value. Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience. We also have a location based compensation structure; there may be a different range for candidates in this and other locations. Ways of Working Our structured hybrid approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting. Benefits As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways. Click Learn for more information. About Us Zoomies help people stay connected so they can get more done together. We set out to build the best collaboration platform for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars. We’re problem-solvers, working at a fas ... (truncated, view full listing at source)