Machine Learning Engineer, Assistant Quality

Job summary

Responsibilities

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…

• 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…
• Partner closely with product, design, and engineering teammates to understand customer pain points and ship high-quality production systems quickly.

What they're looking for

• 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++.

Tech stack

• RAG
• Python
• Go
• Java
• C++