As AI becomes more ubiquitous, the need for the top-tier talent at tech firms becomes even more important—and it’s starting a war among Big Tech, which is simultaneously churning through layoffs and poaching people from each other with eye-popping pay packages. Meta, for example, is dishing out $100 million signing bonuses to woo top OpenAI researchers. Others are scrambling to retain staff with massive bonuses and noncompete agreements.
With such a seemingly small pool of researchers with the savvy to usher in new waves of AI developments, it’s no wonder salaries have gotten so high. That’s why one tech executive said companies will need to stop “recycling” candidates from the same old Silicon Valley and Big Tech talent pools to make innovation happen.
“There’s different biases and filters about people’s pedigree or where they came from. But if you could truly map all of that and just give credit for some people that maybe went through alternate pathways [then you can] truly stack rank,” Alex Bates, founder and CEO of AI executive recruiting platform HelloSky, told Fortune.
(In April, HelloSky announced the close of a $5.5 million oversubscribed seed round from investors like Caldwell Partners, Karmel Capital, True, Hunt Scanlon Ventures as well as prominent angel investors from Google and Cisco Systems).
That’s why Bates developed HelloSky, which consolidates candidate, company, talent, investor, and assessment data into a single GenAI-powered platform to help companies find candidates they might not have otherwise.
Many tech companies pull from previous job descriptions and resume submissions to poach top talent, explained Bates, who also authored Augmented Mind about the relationship between humans and AI. Meta CEO Mark Zuckerberg even reportedly maintains a literal list of all the top talent he wants to poach for his Superintelligence Labs and has been heavily involved in his own company’s recruiting strategies.
But the AI talent wars will make it more difficult than ever to fill seats with experienced candidates.
Even OpenAI CEO Sam Altman recently lamented about how few candidates AI-focused companies have to pull from.
“The bet, the hope is they know how to discover the remaining ideas to get to superintelligence—that there are going to be a handful of algorithmic ideas and, you know, medium-sized handful of people who can figure them out,” Altman recently told CNBC.
The ‘moneyball’ for finding top talent
Bates refers to his platform as “moneyball” for unearthing top talent—essentially a “complete map” of real domain experts who may not be well-networked in Silicon Valley.
Using AI, HelloSky can tag different candidates, map connections, and find people who may not have as much of a social media or job board presence, but have the necessary experience to succeed in high-level jobs.
The platform scours not just resumes, but actual code contributions, peer-reviewed research, and even trending open-source projects, prioritizing measurable impact over flashy degrees. That way, companies can find candidates who have demonstrated outsized results in small, scrappy teams or other niche communities, similar to how the Oakland A’s Billy Beane joined forces with Ivy League grad Peter Brand to reinvent traditional baseball scouting, which was depicted in the book and movie Moneyball.
It’s a “big unlock for everything from hiring people, partnering, acquiring whatever, just everyone interested in this space,” Bates said. “There’s a lot of hidden talent globally.”
HelloSky can also sense when certain candidates “embellish” their experience on job platforms or fill in the gaps for people whose online presence is sparse.
“Maybe they said they had a billion-dollar IPO, but [really] they left two years before the IPO. We can surface that,” Bates said. “But also we can give credit to people that maybe didn’t brag sufficiently.” This helps companies find their “diamond in the rough,” he added.
Bates also predicts search firms and internal recruiters will start forcing assessments more on candidates to ensure they’re the right fit for the job.
“If you can really target well and not waste so much time talking to the wrong people, then you can go much deeper into these next-gen behavioral assessment frameworks,” he said. “I think that’ll be the wave of the future.”
