AI Engineer - Quality and Post-Training

Location: Hybrid, 4 days per week in the Mountain View or San Francisco office

Base salary: $200,000–$280,000 annually

Company

Glean develops an enterprise Work AI platform with intelligent search, AI assistants, autonomous agents, enterprise SaaS connectors, flexible LLM support, and APIs.

What you will do

• Use evaluation results and production traces to improve agent harnesses, model routing, prompts, retrieval, and the broader AI stack while balancing quality, latency, and cost.
• Post-train LLMs using supervised fine-tuning and preference- or reward-based optimization, including generating training data.
• Build reinforcement-learning environments that simulate enterprise workflows, including evaluation sets, harness support, and LLM-based verifiers.
• Improve evaluation sets, LLM judges, and agentic verifiers, calibrating them against human graders for trusted release decisions and model training.
• Work with product, platform, and research teams to ship quality improvements into production.

Requirements

• 5+ years of industry experience in AI or Machine Learning Engineering.
• Hands-on experience post-training LLMs, including adapting open-weight models to specialized tasks.
• Experience building evaluations for AI assistant and agent systems, including generating evaluation sets, building LLM-as-a-judge verifiers, and calibrating offline and online signals.
• Good judgment about when a metric reflects genuine quality improvements.
• Strong coding skills in Python and/or Go, proficiency in an ML framework, and a track record of shipping production ML systems.
• Product-minded approach, ability to turn vague problems into concrete experiments, and ability to work effectively in a tight-knit, cross-functional team.

Nice to have

• TypeScript experience.

Culture & Benefits

• Hybrid work with four days per week in the Mountain View or San Francisco office.
• Medical, vision, and dental coverage, a generous time-off policy, and access to a 401k plan.
• Home office improvement, education, and wellness stipends.
• Regular company events and healthy daily lunches.
• Inclusive workplace committed to diverse backgrounds, experiences, and perspectives.

Hiring process

• Complete a brief AI-focused exercise or discussion during the interview process.