GenAI hires aren't the same as AI/ML hires. Most JDs miss it.
Three distinct profiles are being confused for one. The mis-hire rate is predictable. The fix is upstream of recruitment.
Draft. Figures marked like this are illustrative and pending verification against Recruise placement data & Sachith sign-off before publication.
Key takeaways
- "AI/ML" hides three distinct profiles: the researcher, the applied-ML engineer, and the GenAI product builder. They are different talent markets.
- Most job descriptions blur all three, which draws the wrong shortlist and makes the mis-hire predictable.
- The fix is upstream of recruitment — decide which profile you're hiring before the req is written, not after the interviews confuse everyone.
Three roles, one title, and a predictable mis-hire.
Under "AI/ML" sit at least three roles that share almost nothing day to day. The researcher advances the model. The applied-ML engineer improves an existing product with established techniques. The GenAI builder wires foundation models into a workflow and owns the messy last mile. Different skills, different markets, different comp — and, in most reqs, the same job description.
When a JD blurs them, the shortlist blurs too. You interview a strong researcher for a role that needed a product builder, everyone leaves the loop vaguely dissatisfied, and the mis-hire rate climbs in a way that looks random but isn't. It was set the moment three roles were priced and pitched as one.
"The mis-hire doesn't happen in the interview. It happens in the job description, where three different people were invited to apply for the same seat."
Sachith Rai · MD & Founder, Recruise
The fix is a decision made before the req exists.
You can't interview your way out of an ambiguous brief. The teams that hire GenAI talent well make one decision first: which of the three profiles this seat actually needs, tied to the outcome it owns. That single choice sharpens the JD, the screen, the comp benchmark, and the assessment all at once.
It sounds obvious and is routinely skipped, because "AI/ML" is a comfortable label that lets everyone avoid the harder specificity. The centres with low mis-hire rates simply refuse the comfort. They name the profile, then hire against it — and the shortlist stops being a mix of people who could never have been right for the same role.
One pattern worth knowing, every week.
The Signal is our weekly read on the senior GCC talent market — one chart, one pattern, no noise. Written from live placement data.
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