Machine Learning Engineer, Platform at Brain Co.
San Francisco, CA
—
Aug 2, 2026
San Francisco, CA
Sep 24, 2026
What this job asks for AI summary
A platform-focused ML engineering role at an applied AI startup building agent-native operating systems for regulated industries such as government, insurance, and construction. The engineer will design and own shared ML capabilities — including document extraction agents, a construction-domain foundation model, model routing, a unified evaluation system, and continuous improvement loops — that underpin every product the company ships. The role suits a hands-on ML practitioner comfortable working at the research frontier while maintaining production-grade reliability.
Senior level · Full-time
Quick apply — this platform usually takes a CV and a few fields.
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
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
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)
No location is specified in the posting — CBSA and state fields are left blank. The role may be remote or in-person; the posting does not clarify.
The posting names no specific frameworks, languages, or cloud platforms anywhere — all skills are derived from the described work (e.g., LLMs, fine-tuning, VLMs, agentic systems, document extraction, eval systems). Several of these appear in the narrative description of the role's core responsibilities rather than a formal requirements section, so the must-have/preferred distinction reflects the centrality of each to the described work.
SOC classification is Medium confidence: the role is titled 'Machine Learning Engineer' and centers on ML modeling, fine-tuning, and evaluation (pointing to 15-2051 Data Scientists), but also involves substantial platform software engineering and end-to-end production ownership (pointing to 15-1252 Software Developers).
No compensation, experience-year minimums, or degree requirements are stated anywhere in the posting.
'RL fine-tuning' is mentioned once in a narrative context; listed as preferred given the limited emphasis relative to the core LLM/agent/extraction work.
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): foundation model development, ML pipeline engineering.
Read the full posting
The employer publishes the full description on their own site — read it there ↗. Or sign in to read it here — it's free, and it also lets you track this application.