If your LinkedIn inbox is a deluge of wishful recruiters, you hold a doctorate in machine learning, and you're swatting away mid-six-figure job offers, congratulations: you're probably an AI research engineer — one of the most eligible job candidates in America.

Knowledge of machine learning is the hottest ticket in today's hiring market, and there's data to show it. An analysis of job-listing data by the University of Maryland, along with job listings platform LinkUp and Outrigger Group, found that one in four US tech jobs posted so far this year are seeking employees with AI skills.

LinkedIn data shows that AI engineering has been the fastest-growing job over the past three years, with AI consultants following closely behind. Companies across nearly every industry are rushing to add key hires who will bring the technology into the fold.

"The top-percentile talent is getting a ton of looks and really interesting offers put in front of them," said Atli Thorkelsson, vice president of talent network at Redpoint Ventures, whose portfolio includes Stripe, Mistral, and Poolside.

This week, Meta spent about $15 billion to buy a 49% stake in Scale AI, a high-profile data company, as part of a deal to bring its founder Alexandr Wang, on board.

Bloomberg reported earlier this week that Zuckerberg is personally recruiting for a new group, headed by Wang, that's dedicated to the pursuit of "superintelligence."

The hiring scramble is on, and the qualified candidate pool is small, said Matthew Clark, founder of Lunch, a search firm that helps tech companies scale with key hires. He's seen Ph.D.-preferred job listings seeking candidates with years of hands-on experience, but says the field hasn't been popular long enough to produce enough talent to meet the demand.

While it's a nightmare for employers to lock in this rare talent, it's a dream come true for those who have the goods.

Data scientists have gone from being fringe characters in many organizations to leading roles. Researchers are getting scooped out of university labs . Clark said some designers with technical and coding skills are now closing the pay gap with their engineering brethren.

Of the six recruiters and headhunters Business Insider spoke with, all had worked on searches related to AI, mostly for tech companies. They said some of the most sought-after roles are AI engineer, machine learning engineer, agent software engineer, infrastructure engineer, research scientist, and the trendy, hybrid role of research engineer.

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Recruiters see wildly different titles for the same work, though OpenAI, Anthropic, and their Canadian rival Cohere deliberately use the low-key "member of technical staff," say True Search's Mark Bai and Shawn Thorne, to obscure what their teams are working on and protect against poaching.

Researchers are still the hardest to find. The ideal candidate, headhunters say, has an advanced degree in machine learning, statistics, or mathematics, preferably from a top-ranked computer science program like the Massachusetts Institute of Technology, Carnegie Mellon University, Stanford University, or the University of California, Berkeley. A few years of experience at a tech company make a candidate more desirable, as it shows they can handle the long hours and high stakes.

For roles geared toward applying AI and wielding the stack effectively, employers care more about what products the candidate has built than where they studied, said Natan Fisher, founder of SingleSprout, a search firm that uses an algorithm to match software engineers, data scientists, and product managers to tech clients.

Headhunters and recruiters are increasingly emphasizing the importance of soft skills when evaluating top candidates. With the rush of vibe coding tools, some forward-thinking leaders are realizing that many hard skills may eventually be automated, Bai and Thorne wrote in a blog post . Their clients are now seeking executives who can adapt to the field's shifting landscape.

Fisher said his clients value emotional intelligence on equal footing with intellectual intelligence. They're looking for professionals who not only have the technical know-how but also the ability to weigh trade-offs, build consensus, and communicate effectively across technical and business teams.

His advice to candidates is to listen more.

"You have two ears and one mouth," Fisher said. "Use them in that ratio."