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Meta's High-Stakes AI Talent Grab: Poaching Andrew Tulloch with a Rumored $1.5 Billion Package

  • Writer: Marketing Admin
    Marketing Admin
  • Nov 4
  • 4 min read
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Meta Platforms has secured Andrew Tulloch, a key figure in AI development and co-founder of Thinking Machines Lab, alongside former OpenAI CTO Mira Murati. Tulloch, who spent over a decade at Meta contributing to projects like PyTorch, left his startup role for personal reasons, according to Thinking Machines. The hire follows Meta's unsuccessful attempt to acquire the startup, after which CEO Mark Zuckerberg personally courted its engineers.

Meta Platforms' recent recruitment of Andrew Tulloch stands out as a symbolic move, blending aggressive corporate strategy with the allure of astronomical compensation. Tulloch, a co-founder of the promising AI startup Thinking Machines Lab, has returned to Meta after initially rebuffing a reported $1.5 billion offer, a move that not only bolsters Meta's technical prowess but also underscores the fierce, high-stakes competition for top-tier AI talent with behemoths like OpenAI and Google DeepMind. This development, in October 2025, comes amid Meta's broader push to accelerate its AI initiatives, including substantial infrastructure investments and partial acquisitions to secure key personnel.


To understand the significance, it's crucial to delve into Tulloch's professional trajectory. A graduate with Bachelor's and Master's degrees from the University of Sydney and the University of Cambridge, respectively, Tulloch spent 11.5 years at Meta before his brief stint at OpenAI and the subsequent co-founding of Thinking Machines Lab in early 2025. Often dubbed the "PyTorch King" for his pivotal contributions to the open-source machine learning framework, Tulloch's expertise in AI systems architecture made him a prime target for Meta's recruitment efforts. His work has garnered over 2,334 citations across approximately 10 publications on ResearchGate, underscoring his influence in the field. Thinking Machines Lab, valued at around $12 billion and backed by a $2 billion funding round, focuses on advanced AI research, and Tulloch's departure—for "personal reasons," as per a lab spokesperson—represents a notable setback for the fledgling company.

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Date

Event

Details

Early 2025

Founding of Thinking Machines Lab

Tulloch co-founds with Mira Murati after brief OpenAI role; startup raises $2B, valued at $12B.

August 2025

Initial Offer Declined

Meta offers Tulloch ~$1.5B; he and over 50 employees reject, following failed acquisition bid.

October 2025

Hire Confirmed

Tulloch departs for Meta with rumored $1.5B package over 6 years; announced internally on Friday.

The broader implications ripple through global AI supply chains and debates over tech dominance. Meta's strategy aligns with its massive capital expenditures—projected at over $75 billion annually—treating elite researchers like "hedge-fund managers" of compute resources to maximize ROI. Comparable moves include Meta's $14.3 billion investment in Scale AI, which enabled hiring 11 senior engineers and the appointment of founder Alexandr Wang to lead a new division. However, such tactics risk alienating startups and concentrating power, potentially hindering diverse innovation. On X, reactions vary: some praise Meta's decisiveness, while others question whether the deepest pockets or collaborative efforts should drive AGI.

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Economically, the AI talent war has driven up compensation, with OpenAI's Sam Altman noting that Meta has offered up to $100 million in bonuses to his staff. Globally, this could fragment supply chains as startups like Thinking Machines, despite ample funding, struggle to retain talent against tech giants' resources. For U.S. tech dominance, it reinforces Meta's position but prompts scrutiny over whether such expenditures—amid Llama 4's mixed reception—will yield proportional breakthroughs.


Aspect

Pros

Cons

Talent Acquisition

Access to top expertise accelerates AI development, e.g., enhancing Llama models.

High costs may not guarantee loyalty; risks overpaying if AI bubble bursts.

Competitive Edge

Positions Meta against OpenAI/Google; leverages Tulloch's PyTorch knowledge.

Could stifle startup ecosystem, reducing innovation diversity.

Economic Impact

Boosts U.S. AI leadership through domestic hires.

Escalates wage inflation, making AI inaccessible for smaller entities.

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Forward-looking experts recommend balanced regulations to prevent monopolization while fostering collaboration. For Meta, integrating Tulloch could catalyze advancements in superintelligence pursuits, but sustaining such talent wars demands innovation beyond checkbooks. As AI evolves, this hire may redefine talent valuation, profoundly influencing global tech dynamics.



 
 
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