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GleanGleanUnited States

Machine Learning Engineer - LLM Evals + Observability

Build evaluation pipelines, LLM judges, and observability tools to measure and improve AI assistant quality. Requires 2+ years software engineering with strong Python/Go skills and LLM eval experience.

200k – 300k/yr
Hybrid2+ YOEML Engineering

About the role

You will:

  • 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.

About 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.

Compensation & Benefits

The standard base salary range for this position is $200,000 - $300,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.

Skills

PythonGoLlm EvaluationNatural Language ProcessingDistributed Data PipelinesMachine LearningEvaluation DatasetsLlm-Powered JudgesObservability Infrastructure

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