Machine Learning Engineer - Agentic Retrieval

Zoom • Seattle, WA

6d • Hybrid

About The Position

Zoom is looking for a Machine Learning Engineer to join our Agentic Retrieval team. You will design and build the core retrieval and reasoning systems that power Zoom’s AI Companion — enabling AI agents to search, reason over, and act on enterprise knowledge to deliver high-quality, trustworthy, and actionable answers at scale. The Agentic Retrieval team sits within Zoom’s GenAI Engineering organization and is responsible for building a multi-tenant, permission-aware retrieval platform. We operate at the intersection of distributed systems, machine learning, and large language models — powering search and answer generation across meetings, chat, docs, and third-party enterprise applications through a layered API architecture (keyword search, natural language search, and agentic RAG-based answer generation).

Requirements

• Master’s degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Distributed Systems, or a 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 environments.
• 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++.
• Solid understanding of information retrieval fundamentals (inverted index, ranking, embeddings, hybrid retrieval).
• Strong system design skills with the ability to reason about scale, reliability, latency, and cost trade-off.

Responsibilities

• Designing and implementing scalable retrieval systems including vector search, hybrid search (keyword + embedding + reranking), and structured query planning.
• Designing and optimize Retrieval-Augmented Generation (RAG) pipelines for multi-step, tool-using AI agents.
• Developing ranking, relevance modeling, and evaluation frameworks to improve search quality and answer grounding.
• Building indexing pipelines that transform heterogeneous enterprise data into unified, retrieval-ready representation.
• Building entity extraction and NLP pipelines that support agentic reasoning over enterprise content.
• Partnering with product, infrastructure, and applied research teams to ship production-grade AI capabilities.

Benefits

• award-winning workplace culture
• commitment to delivering happiness
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior