If your LinkedIn inbox is a flood of hopeful recruiters, you have a PhD in Machine Learning and a PhD among six-digit jobs. congratulations. You are probably an AI research engineer and one of the most qualified job seekers in America.
Machine learning knowledge is the hottest ticket in today's recruitment market, and there is data to show it. Along with an analysis of job list data by the University of Maryland and link-up and outrigger groups on the Job List Platform, we found that one in four of the US high-tech jobs featured so far this year are looking for employees with AI skills.
LinkedIn data shows AI engineering is the fastest growing job in the last three years, with AI consultants intimately lagging behind. Companies in almost every industry are rushing to add key jobs that will bring technology to collapse.
“The top talent has gained a lot of looks and has really interesting offers before them,” said Atli Thorkelsson, vice president of Red Point Ventures' Talent Network.
This week, Meta spent roughly $15 billion to buy a 49% stake in high-profile data company Scale AI as part of a deal powered by founder Alexandre Wang.
Bloomberg reported this week that Zuckerberg is personally recruiting a new group led by a king dedicated to the pursuit of “super intelligence.”
Recruitment scramble is on and the pool of eligible candidates is small, said Matthew Clark, founder of Lunch, a search company that helps tech companies expand with major recruitment. He looks at a list of positions where he has completed his PhD in search of candidates with years of practical experience, but says the field has not been popular for long enough to generate talent enough to meet the demand.
It's a nightmare for an employer to lock this unusual talent in, but it's a dream for those who own a product.
Data scientists have moved from fringe characters in many organizations to major roles. Researchers are scooped out of university labs. Clark said some designers with technical and coding skills are now closing the pay gap with their engineering siblings.
Mark Zuckerberg, Recruit in Chief. Andrej Sokolow/Picture Alliance via Getty Images
Of the things six recruiters and headhunter business insiders talked about, they all worked on searches related to AI. They said some of the most popular roles are trendy and hybrid roles of AI engineers, machine learning engineers, agent software engineers, infrastructure engineers, research scientists and research engineers.
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Recruiters are intentionally using the modest “technical staff” by Openai, Anthropic and Canadian rivals, but they are intentionally using Mark Bai and Shawn Thorne from True Search to obscure what their team is working on and protecting them from poaching, but they see very different titles in the same work.
Researchers are still the hardest to find. The ideal candidate will be advanced in machine learning, statistics, or mathematics from top-ranked computer science programs such as Massachusetts Institute of Technology, Carnegie Mellon University, Stanford University, or the University of California, Berkeley. Several years of experience with high-tech companies make candidates more desirable as they show that they can handle long hours and high interests.
Regarding roles aimed at applying AI and effectively equipping stacks, employers care more about the products they have built than where candidates have studied, says Natan Fisher, founder of SinglesProut, a search company that uses algorithms tailored to technology clients for software engineers, data scientists and product managers.
Headhunters and recruiters are increasingly highlighting the importance of soft skills when evaluating top candidates. With the rush of vibe coding tools, some advanced leaders have realized that many hard skills could ultimately be automated, Bai and Thorne write in a blog post. Their clients are currently looking for executives who can adapt to the changing landscape of the field.
Fisher said his clients value intellectual intelligence and emotional intelligence on an equal footing. They are looking for experts who have the ability to weigh trade-offs, build consensus and communicate effectively between technical and business teams, as well as technical know-how.
His advice to candidates is to listen more.
“You have two ears and one mouth,” Fisher said. “Use them in that ratio.”
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