If offered a job worth up to $1.5 billion, most people would find it impossible to say no. Yet Andrew Tulloch, a 37-year-old Australian computer scientist, did just that—turning down a staggering six-year compensation package from Meta CEO Mark Zuckerberg, reportedly valued at up to $15 billion. His decision has made headlines across Silicon Valley, highlighting a growing shift in how top AI talent evaluates career moves. According to The Wall Street Journal, Zuckerberg had been pursuing the acquisition of Thinking Machines Lab (TML), the AI startup co-founded by former OpenAI Chief Technology Officer Mira Murati. When Murati declined the acquisition, Meta launched an aggressive talent raid, extending offers to over a dozen employees at TML. Tulloch, one of the company’s co-founders, was the primary target. Zuckerberg and Meta’s new superintelligence lab head, Alexandr Wang, personally reached out multiple times, offering a package that combined base salary, bonuses, and stock options—totaling up to $15 billion over six years, contingent on performance. Despite the astronomical offer, Tulloch declined. The move underscores a deeper trend: for elite AI researchers, money alone is no longer the deciding factor. Tulloch’s credentials are exceptional. He graduated from the University of Sydney with the highest GPA in the faculty of science. He then earned a master’s degree in mathematical statistics from Cambridge’s Trinity College, graduating with distinction. His career began at Goldman Sachs in 2010, where he worked on statistical arbitrage and financial modeling. In 2012, he joined what was then Facebook—now Meta—where he spent 11 years advancing machine learning systems, particularly in PyTorch development. He rose to become a Distinguished Engineer, one of the highest technical titles at Meta. Former Meta executive Mike Vernal described him as “a recognized extreme genius.” In October 2023, Tulloch left Meta for OpenAI, where he contributed to the development of GPT-4o and GPT-4.5, focusing on pre-training and system architecture. Less than a year later, when Murati left OpenAI to launch TML in February 2025, Tulloch joined her as a co-founder. Interestingly, OpenAI had tried to recruit Tulloch as early as 2016. At the time, he was earning $800,000 at Facebook, while OpenAI offered only $175,000 in salary and $125,000 in bonuses. OpenAI’s Greg Brockman noted in an internal email that Tulloch was “very close to accepting” but hesitated due to the significant pay cut. This time, the tables had turned—yet Tulloch still chose independence over a massive payday. TML, though still productless, has already attracted a $1.2 billion valuation in its seed round. Murati, known for her emotional intelligence and collaborative leadership, has drawn over 20 former OpenAI colleagues to the startup. TML operates with a flat, peer-driven structure—reminiscent of Bell Labs—where even senior researchers are labeled “technical team members,” reflecting a culture built on equality and innovation. Meta’s recruiting efforts extended beyond Tulloch. Other TML employees received offers ranging from $200 million to $500 million over four years, with first-year salaries of up to $100 million. Yet not a single one accepted. This unprecedented resistance reveals a new reality: top AI researchers are no longer swayed solely by financial incentives. Why? First, many of these individuals already hold significant equity in high-valued startups. Second, they remain skeptical of Meta’s ad-driven business model, fearing their work will ultimately serve targeted advertising rather than scientific progress. Third, they believe OpenAI and its spin-offs are farther along in the pursuit of artificial general intelligence (AGI). As one insider put it: “They believe OpenAI is closest to AGI, and they want to work in a smaller, more agile environment—not one where their work fuels ads.” For Zuckerberg, the challenge is no longer about outbidding competitors. It’s about proving Meta can offer not just capital, but a compelling technical vision and a culture that attracts the world’s best minds. In the race for AI dominance, the most valuable currency may no longer be money—but purpose.