Type:
Temp (6–9 months) • Location: Remote US TZsTarget 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 TargetFDE: 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 Engagement30–40 hrs/week
