Meta’s lavish AI hiring fuels internal resentment, pay wars and high-profile departures
Wall Street Journal reporting says Meta’s multimillion-dollar offers and a closed-off ‘TBD Lab’ have prompted defections, internal pay fights and questions about talent retention
Meta’s effort to build a top-tier artificial intelligence team by offering massive compensation packages has prompted resentment among longtime employees, a spate of high-profile defections and an internal scramble over resources, according to a Wall Street Journal report.
The Journal reported that Meta has offered some AI recruits packages ranging as high as $250 million to $300 million over four years, with select hires receiving awards the outlet described as reaching roughly $100 million in the first year through combinations of cash, stock and other incentives. The hires have been concentrated into a small, badge-restricted unit near CEO Mark Zuckerberg’s office called the "TBD Lab," the Journal said, and its roster is not visible on the company’s internal directory.
The secrecy and reported pay levels have fueled grumbling across Meta’s Menlo Park campus, where employees said the outsized offers came during a period of tight hiring controls and limited computing resources. Longtime engineers and managers have used competing offers to seek raises and promotions, and some teams told the Journal they felt starved of infrastructure while the new unit secured privileged access.
Several hires left shortly after joining, the Journal reported. Among those who returned to rivals were Avi Verma and Ethan Knight, who left for OpenAI. Researcher Shengjia Zhao, a co‑creator of ChatGPT, nearly returned to OpenAI within a week of joining Meta before the company formalized his role as chief scientist; the Journal reported that move was accompanied by a substantial pay increase, a claim Meta disputes. Toronto-based researcher Rishabh Agarwal resigned after being told he would have to work in person and instead joined Periodic Labs, a startup founded by a former OpenAI executive. Product manager Ruben Mayer, recruited from Scale AI, also left, the Journal said, citing personal reasons.
Meta told The New York Post that characterization of the situation was "false, exaggerated or mischaracterized," and the company disputed aspects of the Journal’s reporting, including the extent of compensation changes tied to individual hires. In a statement cited by the Post, Meta said it formalized Zhao’s role once the team structure was defined and described him as a scientific lead since the group’s inception.
The Journal said more than 50 AI experts were recruited during the summer hiring push, including 21 from OpenAI, more than a dozen from Google and others from Apple and Elon Musk’s xAI. That influx, and the perceived preferential treatment of some new hires, prompted internal moves: employees who brought outside offers to management sometimes saw their compensation and team assignments adjusted, generating further questions about equity and process.
Experts and former industry HR executives said such concentrated spending can backfire without clear cultural and managerial foundations. Laszlo Bock, former head of human resources at Google, told the Journal that failing to prepare the workplace for an elite cohort risks burning out top talent and wasting the investment.
The situation at Meta reflects broader industry dynamics as AI talent becomes increasingly mobile and well compensated. Companies from established Big Tech firms to early-stage startups have engaged in aggressive recruiting tactics. The Journal and other outlets reported that OpenAI handed out one-time retention bonuses this year, and that offers from startups founded by ex-OpenAI executives, including Mira Murati’s Thinking Machines Lab, have prompted additional movement and bargaining leverage across the sector.
Meta’s AI leadership has exercised tight control over hiring and resource allocation during the internal push, managers told the Journal, with approvals for new roles routed to senior leaders. Some employees said that constrained hiring and opaque decision-making added to frustration as the company sought to scale its AI efforts rapidly.
The departures and public reports have raised questions about how sustainable the current recruitment model will be. While large offers can attract top researchers, retention depends on team integration, access to computing and research support, and workplace culture, according to former executives and hiring experts who commented to the Journal.
Meta declined to provide additional comment beyond statements in the Post and Journal coverage. The company has publicly emphasized its long-term investments in AI research and infrastructure and continues to recruit across a wide range of technical roles as it expands its lab and product efforts.
Industry observers say the competition for AI talent is likely to remain intense, with firms adjusting compensation, workplace policies and strategic structures to keep researchers and engineers amid a fast-moving technology landscape. The short-term influx of top hires has already reshaped internal dynamics at Meta and underscored the broader market pressures shaping where and how AI research is conducted.