Machine Learning Engineer, Llm Evals & Observability

Glean

Mountain View, CA, United States
Base: $200,000 - $300,000 annually; bonus/equity: ...
Hybrid (3-4 days in the office)
2+ years software engineering experience
Strong backend fundamentals in go and python
Experience with llm evaluation and nlp
Glean is seeking a Machine Learning Engineer for their LLM Evals & Observability team in Mountain View, CA. The ideal candidate will have experience in software engineering, particularly in backend development, and a strong focus on quality measurement for AI systems

Job Summary

  • The role focuses on building the measurement and quality layer that ensures Glean's AI Assistant and Agents reliably improve over time.
  • Candidates will design evaluation datasets, build LLM-powered judges, and create observability infrastructure to inspect agent behavior.
  • Glean offers a comprehensive benefits package including medical, vision, dental coverage, generous time-off, and 401k contributions.

Matching Summary

Match Score: 85

Glean is seeking a Machine Learning Engineer for their LLM Evals & Observability team in Mountain View, CA. The ideal candidate will have experience in software engineering, particularly in backend development, and a strong focus on quality measurement for AI systems.

Salary

Base: $200,000 - $300,000 annually; Bonus/Equity: Variable compensation and equity may be eligible; Benefits: Medical, Vision, Dental, 401k, generous time-off

Skills & Requirements

Must-have

  • 2+ years software engineering experience
  • Strong backend fundamentals in Go and Python
  • Experience with LLM evaluation and NLP
  • Designing large-scale evaluation datasets
  • Building distributed data pipelines

Nice-to-have

  • Analytically rigorous mindset
  • Customer-focused team player
  • Deep care for product quality
  • Experience with RLHF techniques
  • Cross-functional collaboration skills

Key Requirements

  • 2+ years of software engineering experience
  • Strong coding skills in Go and Python
  • Experience with machine learning systems

Work Rights

Not specified

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