Machine Learning Engineer, Glean
LLM Evals + Observability
$200-300k
3-4 days a week in office
AI-based search engine connecting enterprise data
Be an early applicant
AI-based search engine connecting enterprise data
1001+ employees
Be an early applicant
$200-300k
3-4 days a week in office
1001+ employees
Company mission
To expand human potential to do extraordinary work.
Role
Who you are
- If you care deeply about quality and want to build the systems that make it measurable, this role is for you
- 2+ years of software engineering experience with strong coding skills
- Strong backend fundamentals in Go and Python; comfortable with distributed data pipelines
- Experience working with LLM evaluation, reinforcement learning from human feedback, natural language processing, or other large systems involving machine learning
- Analytically rigorous – you think carefully about what offline metrics actually predict about real user experience
- Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company
- You care about quality – not just in the systems you build, but in the product you're helping measure and improve
What the job involves
- 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
- 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
- Design and curate evaluation datasets – sampling strategies, query diversity, and golden sets that give reliable, representative coverage of real assistant behavior
- Build and maintain large-scale evaluation pipelines that measure assistant quality across thousands of real user queries
- Build LLM-powered judges that score metrics like correctness, completeness, and response quality, and align them against human judgment
- Evaluate new models and product changes before they ship – providing the quality signal that gates launches and prevents regressions
- Build observability infrastructure for AI agents: trace enrichment, data pipelines, and dashboards that make assistant behavior inspectable
- Close the loop between quality measurement and improvement using eval results, customer feedback, and techniques like automated prompt iteration to help drive concrete gains in assistant behavior
- Collaborate with engineers across the company to make evals a first-class part of how we ship
Our take
Glean is an intuitive digital assistant which allows employees to search across all their apps and find the information and tools that they need more quickly.
With so many SaaS apps being used by modern day companies, overwhelm and inefficiency inevitably enter the equation. Glean’s search engine is proving popular for how it unifies and centralizes all these distributed tools and data.
It’s been quite a start to life at Glean, having emerged from stealth in 2021, it received a $1B valuation in early 2022, thus achieving unicorn status. Since then, the company has gone on to raise substantial funding and bring its valuation up to $7.2B in 2025. With this impressive growth, its secured some big name customers like Grammarly, databricks, and Rubrik.
That Glean was co-founded by a quartet with senior experience at Google, Microsoft, Uber, and Facebook stands the company in good stead. However, it’s the fact that its search engine is solving a new, but very real problem in the workplace that’s seen its popularity surge so quickly, which it’s likely to continue to do in the future. And its adaptability to include new AI capabilities to its platform, such as generative AI, has Glean well set to see further growth.
Steph
Company Specialist at Welcome to the Jungle
Insights
44% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
Jun 2025
$150m
SERIES F
Sep 2024
$260m
SERIES E
Total funding: $805m
Company HQ
Evergreen Park, Palo Alto, CA
Leadership
Arvind Jain
(Co-Founder & CEO)Former Engineer at Google and Microsoft. Arvind is also the co-founder of high growth startup Rubrik, which delivers data security and operational resilience for enterprises.
TR Vishwanath
(Co-Founder & CTO)Before co-founding Glean, TR was a Principal Software Engineer at Facebook after spending eight years at Microsoft as a Software Design Engineer, then Principal Development Lead.
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