Machine Learning Engineer, Assistant Quality at Glean
San Francisco, CA
$180,000–$205,000from the description
Aug 3, 2026
San Francisco, CA
Sep 24, 2026
What this job asks for AI summary
A Machine Learning Engineer role at an enterprise AI platform company, focused on improving the quality of an AI Assistant and autonomous agents in production. The work spans LLM-powered systems, RAG and semantic search, evaluation and benchmarking frameworks, agent orchestration, and personalization — all oriented toward shipping reliable, measurable improvements to real enterprise workflows rather than research. Suits an applied ML practitioner comfortable bridging modeling and product engineering.
Mid level · 2+ years · San Francisco-Oakland-Berkeley, CA · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 470 people in the San Francisco-Oakland-Berkeley, CA area plausibly meet what this posting asks for (data scientists). range 350–610
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $173,851 (middle half $133,298–$217,653). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 4, 2026. It is a model, not a headcount.
Why we read it this way (6)
The role is genuinely ambiguous between 15-2051 (Data Scientists — ML modeling, evaluation, experimentation) and 15-1252 (Software Developers — production systems, product engineering, shipping code). The posting emphasizes production shipping and software fundamentals as much as ML, so 15-1252 is a credible runner-up.
The title carries no seniority level, but the 2+ years minimum and scope of responsibilities (independent ownership of production ML systems, cross-functional collaboration) support a Mid-level classification.
Python is listed alongside Go, Java, and C++ as acceptable languages; Go, Java, and C++ are captured as alternatives since any one satisfies the requirement.
LLM applications, NLP, search/retrieval, recommendations, evaluation frameworks, agent systems, and personalization are listed as 'one or more of the following areas' — meaning none individually is a hard gate, so all are marked preferred.
RAG, semantic search, agent orchestration, and reinforcement learning appear in the responsibilities narrative ('You will work on…') rather than a requirements section, so they are marked preferred.
The role is hybrid (4 days/week in San Francisco), not fully remote.
Read the full posting
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