Founding AI Recruiter

About Calibratr

Calibratr is an AI-native embedded recruiting firm. We embed full recruiting pods inside fast-scaling seed to Series B AI startups, with a focus on AI in healthcare, and run hiring end to end: sourcing, screening, calibration, and close. We hire on proof of work, not resumes, and calibrate to a founder's real bar instead of a keyword list.

Our stack pairs experienced recruiters with an AI-native sourcing and evaluation workflows, so a small team moves at the speed our client's need.

Who we're looking for
A strong Recruiter with deep fluency in the AI/ML and data talent markets. You own full-cycle hiring for the hardest technical roles our clients open: MLEs, applied AI and agents engineers, research engineers, forward-deployed engineers, and data scientists.

• You've recruited AI/ML, data, or research engineering roles and closed senior or staff-level hires.
• You can hold a technical conversation about ML systems, applied AI, or data infra well enough to calibrate and screen.
• You know the difference between "used a model" and "trained and shipped one," and you can spot an inflated profile.
• You're plugged into the AI talent market, or you can map it fast: labs, feeder companies, research communities.
• Clear writer, high agency, organized end to end.

What you'll own

• Everything a Founding Recruiter owns (full-cycle ownership, the screening gate, process velocity, weekly reporting) for AI/ML, data, and forward-deployed roles.
• Deep technical calibration: read a research or engineering profile and know whether they've actually built and shipped models, agents, or data systems, versus adjacent exposure.
• Real proof-of-work evaluation: papers, repos, models, benchmarks, launches, not titles.
• Turning a highly specific spec (a stack component, an eval method, a research area, a stage) into a search that finds the ten people who fit and skips the thousand who don't.
• Partnering with technical founders as a credible thought partner on the AI talent market: who's strong, where they are, what they cost.
• Bringing market intel back: comp, competitor hiring, and where the talent is flowing.

Bonus

• Experience in AI healthcare specifically (HIPAA/FHIR, clinical eval, health data).
• Comfortable with AI-native sourcing tools and evaluating candidates with LLM-assisted workflows.

How we work: Remote-first, US hours. Small team, direct access to founders, fast feedback.

We don't care about years of experience, we care about mindset, drive and no ego.