Machine Learning Engineer, Assistant Quality

Details

Glean is seeking a Machine Learning Engineer to improve the quality of its AI Assistant and autonomous agents. The 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.

The work covers applied problems across agent quality, evaluation, personalization, retrieval, and orchestration. The ideal candidate is excited by shipping production systems rather than pure research and wants to improve the assistant through stronger signals, tighter feedback loops, and better end-to-end execution quality.

Responsibilities

• 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 retrieval-augmented generation (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.

Requirements

• 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, including the ability to choose between sophisticated ML techniques and simple, reliable systems.
• A proactive, low-ego working style and excitement about learning quickly in a high-velocity environment.
• Candidates will complete a brief AI-focused exercise or discussion during the interview process.

Location

• Hybrid schedule with 4 days per week in the San Francisco office.

Compensation And Benefits

• Standard base salary range of $180,000–$205,000 annually.
• Certain roles may be eligible for variable compensation, equity, and benefits.
• Medical, vision, and dental coverage.
• Generous time-off policy.
• 401(k) contribution plan.
• Home office improvement stipend.
• Annual education and wellness stipends.
• Regular company events and healthy lunches daily.

Glean is committed to building and sustaining a diverse, inclusive workplace. The company does not discriminate on the basis of gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.