Accelerate: filling a senior AI/ML engineering role at a digital health company

A digital health company with more than 800 employees needed to hire a Principal-level AI/ML engineer. The role required a specific combination: deep machine learning expertise and working familiarity with healthcare domain constraints. By the time the engagement began, the position had been open for an extended period with no viable candidates in pipeline.

Standard sourcing channels had not produced qualified applicants. The candidate market for senior AI/ML engineers with healthcare experience is narrow. Most people with the required ML depth work in adjacent sectors; most people with healthcare backgrounds hold clinical or product roles rather than engineering ones. The combination was rare enough that broad-reach sourcing was not finding it.

The role staying open had real cost. The company was building AI infrastructure with a team headcount gap at the senior level.

The Talent Foundation ran a targeted direct search. The first step was market mapping: identifying the actual population of candidates who held both qualifications, rather than sourcing against a job description. This meant going beyond standard job boards and recruiter networks to map passive candidates working at the intersection of ML engineering and digital health.

From that mapped population, The Talent Foundation built a structured outreach sequence. Outreach was targeted and role-specific, not templated. Candidates received context on the role's scope and why their specific background was relevant. The Talent Foundation managed candidate communication through initial qualification, coordinated assessment logistics, and supported the offer process.

The role was filled. The Talent Foundation placed the role after a direct search engagement during a period when the position had been open for an extended time with the company's own sourcing efforts returning nothing usable. The placement was a Principal-level hire in a candidate market where the qualification combination was genuinely scarce.

No exact time-to-fill figure is cited here because that data is not confirmed. The directional outcome is accurate: The Talent Foundation succeeded where prior sourcing had not.