Candidate Quality
Why do AI engineers not respond to job adverts?
Co-founder and CEO
The short answer
Experienced AI engineers do not respond to job adverts because they are almost never looking: they are employed on interesting work, well paid, holding unvested equity, and receiving approaches every week already. An advert asks them to enter a process and compete for something they have not decided they want, which is a poor offer compared with a specific conversation about a specific problem.
The people you want are not ignoring your advert because it is badly written. They are not reading it at all.
The market conditions behind it
- Demand ran ahead of supply. Nearly every technology business now has an AI initiative, and the pool of people who have taken one to production is small.
- They are already approached constantly, so the marginal value of one more message is close to zero unless it is specific.
- Compensation and equity are usually good, which raises the bar for any move.
- The work itself is often the retention factor. Interesting problems are harder to replace than salary.
- Adverts select for availability rather than capability, so the response you do get skews towards the visible minority of the market.
What reaches them instead
Three channels do most of the work. Referral from engineers they respect, which arrives with credibility attached. Community, including open-source contribution, research circles and technical meet-ups, where their work is already visible. Direct approach from somebody who can hold a real technical conversation about the problem, rather than recite a job description back at them.
The common factor is specificity. A message that names the system, the data, the constraint and the reason this person in particular was approached gets replies. A message that names a salary band and a list of technologies does not.
When adverts are still worth running
Advertise for early-career roles, for well-defined engineering positions in deep talent pools, and to support employer brand for people who already know you. Adverts are cheap and occasionally productive. They are simply the wrong primary channel for a small, passive and highly contested market.
Explored in depth
This topic is explored in more depth within How do you hire AI and machine learning engineers?.
See this in practice
Move from the concept to the way Saiyō delivers it.
Related questions
What should you assess in a machine learning engineer?
Assess four things: what the candidate has personally built and put into production, how they evaluate whether a model is working, how they handle data quality and failure, and whether their judgement fits the stage your initiative is at. Everything else, including the job title and the framework list, is a poor predictor.
Read the answerAnswerWhat is the difference between an ML engineer and an applied AI engineer?
A machine learning engineer builds, trains, deploys and maintains models, and is judged on whether the model performs reliably in production. An applied AI engineer builds product features on top of models, usually models somebody else trained or a third party provides, and is judged on whether the feature works well for users at acceptable latency and cost.
Read the answer