Data & AI practice
Hire data and AI people who ship.
Data scientists and ML engineers who get models into production, not just notebooks. Screened for engineering rigor as much as research depth.
Roles we place
Data ScientistsML EngineersAI EngineersAnalytics EngineersData Platform
How the search runs
01
JD co-writing
We co-write the JD until it describes the person you actually need.
02
Sourcing
We reach out directly to proven people in our network and beyond, instead of waiting for applications.
03
Psychometric screen
Tests and culture mapping, included free. Fit is measured, not guessed.
04
Panels
Technical and cultural rounds with your stakeholders. High signal only.
05
Signed offer
We handle the offer and the close. You get a signed acceptance and a start date.
Why FPT
Production over papers
We screen for shipped ML systems and data products, not citation counts.
Rare-skill sourcing
The best data and AI people are never on job boards. Our network search finds the ones quietly shipping.
Stage-fit screening
A seed-stage data hire and an enterprise one are different jobs. We scope which one you actually need.
−29% time-to-hire on mid to senior roles
82% of placed candidates still in seat at 12 months
9 days median from first call to first founder interview
Questions founders ask
The three we hear most, answered straight.
Can you hire for applied AI product roles?
Yes, including AI engineers building on foundation models, retrieval systems, and agentic products, where engineering judgment matters more than research pedigree.
Do candidates get technical screening?
Every shortlist has passed structured technical rounds plus psychometric screening before you meet them.
We are not sure if we need a data scientist or an ML engineer. Can you help?
That is exactly what the discovery call and JD co-writing step solve. We scope the role from your actual problems before searching.
Further reading
Let's build your data team.
A short call is enough to scope the search.