The war for AI talent has turned the tech industry into a real-life game of The Price is Right, and let’s just say most companies aren’t making it to the Showcase Showdown.
High salary expectations are the biggest challenge companies of all sizes face when hiring AI talent, with small to mid-size companies feeling the brunt of the sticker shock.
That’s according to a recent CloudZero survey querying 500 US software engineers, senior managers, and other higher ups at companies with between 250 and 10,000 employees earlier this year. Other challenges the survey referenced include a shortage of qualified candidates, a too-lengthy hiring process, and unclear role requirements.
Houston, we have a problem. Aaron Sines, director of AI recruiting at tech recruitment agency Edison & Black, told IT Brew that he has seen salary expectation problems time and time again, largely because of a salary expectations “mismatch” between companies and candidates.
“Companies think they can hire AI talent like they can hire software engineers, and it’s like trying to hire Elon Musk with a Toyota salary,” Sines said. CloudZero estimates that most AI professionals earn more than $100,000 with more than one-fourth (26%) earning between $150,000 and $200,000.
Sines explained that the industry is currently undergoing what he calls the “1,000 people problem.” Currently, there are about 1,000 people with the “deep theoretical knowledge” needed to build and train advanced AI models known as frontier models. (Sines noted it’s likely about 2,000 people, but 1,000 sounds catchier). The problem is every company wants to grab the cream of the crop, especially those with experience at top AI companies, leaving many regular tech companies unable to compete.
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“A lot of times we’re kind of giving them the hard news that, ‘Hey, you’re way off, way off. So, unless you’re willing to adjust your expectations, we’re not going to be able to deliver on this,’” Sines said.
Eric Fehr, chief revenue officer at Search Solution Group, recalled once working with a mid-size SaaS company that was seeking an inaugural in-house machine learning engineer with an initial budget in the range of $160,000 to $165,000. Fehr said candidates with the appropriate level of experience for the role were expecting upward of $200,000.
“That’s a pretty significant gap,” Fehr said. “That caused some friction and kind of caused progress to stall for a couple weeks.”
What’s a tech company to do? For companies that may not be able to afford top AI talent, Sines suggests upskilling current talent or hiring and refining entry-level candidates.
“A lot of more sophisticated engineers who’ve been working on machine learning, or something peripheral of machine learning, can definitely be upskilled,” Sines said. “And a lot of them, I think, are really eager to be.”