Contract Talent Sourcer (AI/ML + Product)

Type: Temp (6–9 months) • Location: Remote US TZs Target Roles: Forward Deployed Engineer, Senior ML Engineer, Research Engineer/Scientist (Alignment), AI Product Manager Own the top of funnel : map the market, generate calibrated pipelines fast, and hand off HM-ready prospects with crisp notes. No “post & pray.” What You’ll Do (Sourcing-First) Market mapping: Build company/lab/OSS target lists; track movers (arXiv, OpenReview, Google Scholar, Hugging Face, GitHub). Outbound at scale: Tailored outreaches; iterate subject/copy; test 3–5 variants; maintain reply metrics. Profile calibration: Validate signals (repos, papers, shipped features, MLOps stack, product outcomes). Light pre-screen (10–15 min): Confirm level, comp ballpark, work auth, location, timeline, and role fit; capture structured notes. Handoff: Package candidates with scorecard snapshot + links; book with recruiter/HM. Role Signals You’ll Target FDE: Customer-facing build/ship, Python + data wrangling, rapid proto, consultative comms. Senior ML Eng: Prod LLM/ML (inference, RAG, fine-tune, evals), MLOps (deploy/observability). Research/Alignment: Strong math/ML fundamentals; safety/evals/interpretability/RLHF artifacts. AI PM: Shipped AI features, experiment cadence, metric/latency/trade-off literacy. Must-Haves 2+ years sourcing for deep eng/ML/AI roles Tools: ATS, LinkedIn Recruiter, GitHub search, arXiv/Scholar, Notion/Airtable, Gem/Fetcher. Clean pipeline habits Engagement 30–40 hrs/week