Machine Learning Engineer, Glean
Assistant Quality
$180-205k
More information about location
4 days a week in office
AI-based search engine connecting enterprise data
Posted today
AI-based search engine connecting enterprise data
1001+ employees
Posted today
$180-205k
More information about location
4 days a week in office
1001+ employees
Company mission
To expand human potential to do extraordinary work.
Role
Who you are
- 2+ years of industry experience in machine learning, applied AI, or software engineering with significant ML ownership
- Strong hands-on coding ability and a track record of shipping production systems, not just prototypes or research projects
- Experience in one or more of the following areas: LLM applications, NLP, search, retrieval, recommendations, evaluation frameworks, agent systems, or personalization
- Comfort working across both modeling and product engineering details, including experimentation, quality measurement, and production iteration
- Proficiency in common ML tooling and strong software engineering fundamentals in languages such as Python, Go, Java, or C++
- A pragmatic, product-minded approach. You know when to use sophisticated ML techniques and when simple, reliable systems are the better answer
- A proactive, low-ego working style and excitement about learning quickly in a high-velocity environment
What the job involves
- Glean is seeking a Machine Learning Engineer to improve the quality of our AI Assistant and autonomous agents
- This role sits at the intersection of production machine learning, LLM-powered systems, and product engineering, with a focus on building, evaluating, and iterating on assistant experiences that are useful, reliable, and grounded in real enterprise workflows
- You will work on applied problems across agent quality, evaluation, personalization, retrieval, and orchestration
- The ideal person is excited by shipping production systems, not pure research, and wants to help shape how Glean’s assistant gets better over time through stronger signals, tighter feedback loops, and better end-to-end execution quality
- Build and improve ML and LLM-powered systems that raise the quality of Glean’s AI Assistant and autonomous agents across real user workflows
- Design evaluation, benchmarking, and monitoring loops to measure assistant quality, model quality, and end-to-end system performance
- Develop and iterate on signals, prompts, workflows, and model-driven logic that improve reasoning, planning, personalization, and task completion quality
- Work across areas such as RAG, semantic search, recommendation-style systems, post-training or reinforcement learning, and agent orchestration where they materially improve product outcomes
- Partner closely with product, design, and engineering teammates to understand customer pain points and ship high-quality production systems quickly
- Contribute to the data and ML infrastructure needed to support robust experimentation, offline and online evaluation, and continuous model improvement
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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