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Specialized recruiting for teams building data platforms, ML systems, and applied AI. From senior ICs to leadership—30 to 60 days on core tiers. Contingency where it fits. No job board. No spray-and-pray.
Typical path to offer: 30 to 60 days. Every placement includes a 90-day replacement guarantee.
Inbound turns hiring into triage. Hundreds of profiles, many mislabeled data science or AI after a short course. Your leads stop building to screen PDFs. Momentum dies in calendar Tetris while the role stays open past sixty days. You need fewer names and more signal.
Keyword-matching PyTorch and LLM without knowing your stack fails everyone. Candidates who cannot own your eval harness, RAG pipeline, or training budget burn your interview panel. You need someone who reads repos and papers, not just titles.
CTOs and leads ship product, not a hundred hours of cold outbound. Internal referrals tap out at senior levels. Boards still want the hire yesterday. You need a dedicated lane that respects your time and only surfaces people who cleared a real technical bar.
how we work
Technical sourcing beyond LinkedIn
We map GitHub, Hugging Face, NeurIPS and ICML authors, data engineering communities, and the corners of ML Twitter and Discord where serious builders live. You get candidates aligned with how you move data, train models, deploy, and evaluate in production.
Depth before your calendar moves
Every shortlist candidate is vetted on technical depth and role fit before you see them. You interview a tight set who can walk your stack, not a volume play that wastes staff engineer time.
Public pricing, no games
Fees and salary bands are on the site. You know the math before the first call. Faster decisions, fewer procurement loops, no request-a-quote theater.
Pay on success for Tiers 1 to 3
Contingency means you pay when the hire starts, under clear terms. Incentives stay aligned. We win when you land someone who stays and ships.
Anonymized for confidentiality
Names withheld under NDA. Roles, stage, and timelines are representative of actual searches.
Senior ML Engineer, ranking and retrieval
Series B vertical AI, legal domain
38 days
Prior FAANG ML infra, shipping RAG at scale in production
Staff Data Engineer, real-time features and lakehouse
Series B fintech, core banking data platform
41 days
Ex-Databricks, owned ingestion, streaming, and governance for petabyte-scale analytics.
Lead ML Engineer, distributed training and GPU orchestration
Series A AI infrastructure, inference platform
44 days
PhD, published systems work, ex-research lab with production handoff
Director of Applied AI, product-facing model team
Series D fintech, AI core for underwriting
61 days
Scaled applied ML org from single digits to double digits
Tier 1
Mid-Senior Data / ML / AI Engineer
$27K – $40K
18% of first-year base
$150K – $220K salary band
Strong ICs who own models and pipelines without staff-level org scope yet.
Schedule Intro CallTier 2
Senior / Staff Data, ML, or AI Engineer
$44K – $64K
20% of first-year base
$220K – $320K salary band
Core hires who set direction for modeling, data, and evaluation with your leads.
Schedule Intro CallTier 3
Principal / Lead ML or Applied AI
$70K – $99K
22% of first-year base
$320K – $450K salary band
Small senior teams that need one person to raise the ceiling on architecture and execution.
Schedule Intro CallDiscovery call, 30 minutes.
Align on role, bar, comp band, and timeline.
We source for 7 to 14 days.
Map communities, repos, and papers that match your stack.
You interview up to five vetted candidates.
Each one pre-qualified on depth and fit.
Placement in 30 to 60 days.
Typical window from kickoff to accepted offer, subject to your process.
If the role and stage fit, we walk through your stack, how we source, and whether contingency or retained makes sense. If not, you still get a straight read on the market.
Schedule Intro Call