Meta loses 4 AI researchers months after $1B recruitment push

Mark Zuckerberg’s billion-dollar recruitment spree to lure top AI researchers to Meta’s Superintelligence initiative is already backfiring, with at least four key hires departing within months of joining. The exodus includes researchers who returned to OpenAI after experiencing Zuckerberg’s management style, highlighting potential internal dysfunction at Meta’s AI division despite massive financial investments.

The big picture: Meta’s aggressive talent acquisition strategy, featuring payments reportedly reaching up to $1 billion, has failed to retain several high-profile AI researchers who are now jumping ship.

Key departures: At least four notable researchers have already left Meta’s AI team after being recruited with substantial financial packages.

• Avi Verma and Ethan Knight, both poached from OpenAI, have returned to their former employer
• Rishabh Agarwal departed after just a few months at Meta
• Chaya Nayak, a longtime Meta product manager, also left for OpenAI

What they’re saying: The departing researchers are keeping their reasons deliberately vague, though some have offered pointed commentary.

• “It was a tough decision not to continue with the new Superintelligence TBD lab, especially given the talent and compute density,” Agarwal wrote on X
• He added a subtle dig at Zuckerberg: “I ultimately choose to follow Mark’s own advice: ‘In a world that’s changing so fast, the biggest risk you can take is not taking any risk'”

Meta’s response: A company spokesperson attempted to downplay the departures as normal industry behavior.

• “During an intense recruiting process, some people will decide to stay in their current job rather than starting a new one,” the spokesperson told Wired. “That’s normal”

Why this matters: The talent drain comes amid reports that Zuckerberg’s micromanaging has created internal chaos within Meta’s AI efforts, suggesting deeper organizational issues beyond compensation.

Industry context: While researcher mobility is common in the competitive AI landscape, the rapid departure of expensive recruits specifically from Meta points to potential management and culture problems rather than typical industry churn.