Forward Deployed AI Engineer

Recruits Lab exists to place the right life sciences and technology talent faster than the market thinks possible. We win searches by mapping passive talent, verifying relationships, and running calibrated shortlists—not by waiting on inbound. You will sit with our recruiters and clients, ship working AI into live searches, and turn messy hiring data into placements that actually close.

Performance Objectives

• Embed with 2–3 active life sciences or tech searches in the first 90 days and deliver a production workflow (sourcing, screening, or matching) that recruiters actually use every week.
• Cut time-to-calibrated-shortlist by 30% on assigned searches within six months by automating mapping, signal extraction, and named-account verification.
• Ship one client-facing AI capability per quarter (e.g., territory talent maps, quota-signal scoring, or pathology/biotech buyer matching) that a hiring manager will reference in a live debrief.
• Own model quality on production data: define success metrics with recruiters, instrument outcomes, and iterate until false positives drop and placement conversion rises.
• Translate recruiter and client language into working systems—no slide decks that never leave the lab.
• Document and hand off each deployment so the next search starts from a working playbook, not a prototype.

Environment & Resources

You report to the founding team in a 11–50 person, early-stage firm based in Fort Lauderdale, with remote-friendly client work across U.S. life sciences and tech corridors. You partner daily with specialist recruiters who already know the territory maps. You get production data from live searches, access to modern LLM/tooling stacks, and the mandate to ship—not a research backlog. Budget follows outcomes: tools and compute that improve placements get funded.

Essential Qualifications

• Shipped AI or ML systems used by non-engineers in a production workflow (search, matching, ranking, or extraction), not only notebooks.
• Comfort embedding with domain experts—recruiters, sales, or scientists—and turning their process into code they will keep using.
• Strong Python plus practical LLM/RAG or classical ML experience; you debug data and prompts as readily as models.
• Evidence you can move from ambiguous client problem to working system in weeks, with measurable uptake.
• Enough life sciences, biotech, or B2B talent-market fluency to ask the right questions of pathologists, PIs, and commercial leaders—or the humility to learn it fast on the job.

Role Selling Points

• Real searches, real clients, real placements—your work shows up in closed deals, not internal demos.
• Direct line to founders and recruiters who already run the hardest life sciences field and R&D searches in the country.
• Early-stage ownership: you define how AI becomes Recruits Lab’s unfair advantage in a relationship-driven market.
• Specialty mix of life sciences, SaaS, and AI/ML talent—you will not be stuck on generic HR use cases.

If you want to deploy AI where it changes who gets hired and how fast, apply now. Send work that proves you ship with users, not just models.