Machine learning Engineer - Agentic Retrieval

What you can expect

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.

About the Team

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).

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.

What we’re looking for

• 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

Salary Range or On Target Earnings:

Minimum:

$151,800.00

Maximum:

$332,200.00

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 fast pace to design solutions with our customers and users in mind. Find room to grow with opportunities to stretch your skills and advance your career in a collaborative, growth-focused environment.

Our Commitment​

At Zoom, we believe great work happens when people feel supported and empowered. We’re committed to fair hiring practices that ensure every candidate is evaluated based on skills, experience, and potential. If you require an accommodation during the hiring process, let us know—we’re here to support you at every step.

We welcome people of different backgrounds