Machine Learning Engineer - LLM Evals + Observability

Glean
San Francisco Bay Area$200k – $300kPosted 5 March 2026

Job Description

<div class="content-intro"><p><span style="font-family: helvetica, arial, sans-serif; color: rgb(0, 0, 0); font-size: 12pt;"><strong>About Glean:</strong></span></p> <p>Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.</p> <p>At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.</p> <p>Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.</p> <p>If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.</p></div><div> </div> <div><span style="font-size: 12pt; font-family: helvetica, arial, sans-serif;"><strong>About the Role:</strong></span></div> <div> </div> <div><span style="font-size: 12pt; font-family: helvetica, arial, sans-serif;">Building a great AI assistant is only half the battle – knowing whether it's actually great is the other half. Our team owns the measurement and quality layer that make Glean's Assistant and Agents reliably better over time: evaluation pipelines, quality evalsets, LLM-powered judges, agent observability, and the tooling engineers use to understand what changed and why. It's a rare combination of infrastructure engineering, applied ML, and direct product impact. If you care deeply about quality and want to build the systems that make it measurable, this role is for you.</span></div> <div> </div> <div><span style="font-size: 12pt; font-family: helvetica, arial, sans-serif;"><strong>You will: </strong></span></div> <div> <ul> <li style="font-size: 12pt; font-family: helvetica, arial, sans-serif;"><span style="font-size: 12pt; font-family: helvetica, arial, sans-serif;">Design and curate evaluation datasets – sampling strategies, query diversity, and golden sets that give reliable, representative coverage of real assistant behavior.</span></li> <li style="font-size: 12pt; font-family: helvetica, arial, sans-serif;"><span style="font-size: 12pt; font-family: helvetica, arial, sans-serif;">Build and maintain large-scale evaluation pipelines that measure assistant quality across thousands of real user queries.</span></li> <li style="font-size: 12pt; font-family: helvetica, arial, sans-serif;"><span style="font-size: 12pt; font-family: helvetica, arial, sans-serif;">Build LLM-powered judges that ... (truncated, view full listing at source)
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