AI hiring, evaluated by people who ship AI.
Generalist engineers can't reliably assess production ML judgment. Recruitor matches every AI evaluation to a practitioner who works in AI today — MLEs, applied scientists, AI infra engineers — scored against a rubric built for the specifics of the role.
"AI experience" hides four very different jobs.
Notebook vs. Production
A candidate who can fine-tune a model in a notebook isn't the same as one who's shipped it to production traffic.
LLM Hype vs. LLM Engineering
Prompting a chatbot well is not the same skill as building reliable, evaluable LLM systems.
Whoever's Free Evaluates It
A highly specialized skill gets assessed by whichever engineer's calendar happened to be open.
No Shared Bar for "AI-Ready"
Without a common rubric, every interviewer's definition of a strong AI hire is different.
A practitioner and a framework built for AI specifically.
AI Practitioner Match
Your evaluation is matched to a working ML engineer, applied scientist, or AI infra practitioner — not a generalist.
AI-Specific Rubric
Evaluation covers production ML judgment, LLM systems engineering, and MLOps — not just algorithms trivia.
Decision-Ready Report
A scored, evidence-backed report your hiring manager can act on the same day.
"I stopped pulling my best ML engineers into interview loops. Recruitor gives every hiring manager that same judgment, on demand."