Senior AI Forward Deployed Engineer at Handshake
San Francisco, CA
$257,000–$300,000
Jul 1, 2026
San Francisco, CA
Jul 21, 2026
What this job asks for AI summary
A forward-deployed engineering role focused on building and delivering AI data infrastructure for frontier AI lab partners. Day-to-day work involves translating research requirements into evaluation frameworks, annotation pipelines, and benchmarking systems, then iterating rapidly with lab researchers. Suited to someone with a strong applied ML background who can operate independently across both technical and client-facing dimensions while mentoring other engineers.
Senior level · 6+ years · Remote · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 3 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
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
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 Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (6)
The caller has overridden the posting's stated San Francisco hybrid location and directed that this be treated as fully remote with no metro assigned.
SOC classification is a genuine judgment call: the role blends applied ML research (data scientists, 15-2051) with forward-deployed software engineering (15-1252). The primary day-to-day work — designing evaluation frameworks, annotation pipelines, and benchmark infrastructure for frontier AI labs — leans toward data science and ML research engineering, so 15-2051 is the primary code, with 15-1252 as a close runner-up.
The 'Tinker' reference under fine-tuning experience appears to be a casual usage ('tinker with models') rather than a specific named tool; it is captured under the broader 'model fine-tuning' skill rather than as a standalone named technology.
No compensation figures are stated in the posting.
Extra Credit items (LLM eval design, annotation platform tooling, benchmarking contributions, forward-deployed consulting experience) are listed under a clearly secondary 'Extra Credit' heading and are marked as preferred.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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