OpenAI and Other AI Labs Poach Wall Street Quants with Multimillion-Dollar Offers

In May, OpenAI CEO Sam Altman invited over 20 finance professionals to the company's San Francisco headquarters, hosting what he jokingly referred to as a "party." The purpose was to recruit quant traders—mathematicians, physicists, data scientists, and engineers who typically power top hedge funds and high-frequency trading firms. A follow-up event in New York City attracted more quant talent, with OpenAI extending formal interview invitations to select attendees. Altman’s pitch to these quant traders is compelling: leave the lucrative but potentially stagnant world of Wall Street to join a tech giant valued at $300 billion, where they can contribute to groundbreaking artificial general intelligence (AGI) research. This aggressive recruiting strategy comes as AI labs intensify their efforts to attract top talent, not just from their competitors but from sectors like finance as well. OpenAI, Anthropic, and xAI are among the startups leading this charge. While Silicon Valley has long been poaching talent from Wall Street, the shift in recent months is notable due to the significantly higher compensation packages offered by AI labs. Junior and mid-level traders are now receiving multimillion-dollar offers, a stark increase from the previous year. This has created a wave of fear and frustration among Wall Street recruiters, who often find their top candidates swayed by the allure of AI companies. OpenAI has already made strategic hires from Wall Street, including Julia Villagra, the former Chief People Officer at Hudson River Trading (HRT), one of the industry's leading proprietary trading firms. HRT's AI lab, led by ex-DeepMind researcher Iain Dunning, generated $8 billion in net trading revenue in 2024, highlighting the potential for AI expertise within finance. The economics of these offers are particularly appealing. Less than two years ago, AI labs offered machine-learning researchers with a few years of experience up to $750,000, including equity. Now, offers for similar roles have risen to between $1.5 million and $3 million. One quant trader, who recently left a high-frequency trading firm, is considering a move to an AI lab simply because the financial incentives are too good to ignore. The skill set of quant traders aligns well with the demands of AI research. Both fields require expertise in mining vast data sets and building systems to extract valuable insights. The high-pressure, fast-paced culture of elite trading desks also mirrors the intense environment of leading AI labs. As Jason Droege, Scale AI's interim CEO, explains, "In quantitative trading, you need to be comfortable conducting research on large quantities of data, then you need to build a system that can take advantage of any insights from that research. Sound familiar?" Moreover, quants are often risk-averse, preferring calculated decisions and expected-value math. This makes them ideal recruits for the rapidly evolving and well-funded AI industry, where the stakes are high but the rewards are immense. Noam Brown, a top OpenAI researcher who previously worked in quant trading, emphasizes this point: "Taking a pay cut to pursue AI research was my best life decision. Today, you don't even need to take a pay cut to do it." Perplexity, a $14 billion search engine and web browser company, also entered the fray by hosting a recruiting event in New York during tech week. Cofounder Johnny Ho, a former quantitative trader, sees this as a natural progression, noting that the tables have turned from quants favoring Wall Street to being more open to Silicon Valley. The DeepSeek incident, where a Chinese AI startup briefly topped the US App Store, further underscored the latent AI capabilities within finance. This episode prompted Altman to openly court quant traders on X, challenging them to escape the "existential dread" of trading optimization and join the AGI revolution. The impact of this recruiting drive is evident, with AI startups now setting new benchmarks for compensation and mission-driven work. Industry insiders predict that if this talent war intensifies, Wall Street will not stand idle. Trading firms are known for their competitiveness and might adjust their strategies to retain their top quants. As Paul Carr, a veteran quant recruiter, warns, "Trading firms are run by competitive people with a habit of winning. They’re used to resource constraints, and they've never had the option of hurling SoftBank's money at problems." However, for now, the financial and cultural appeal of AI labs, combined with their lofty missions, seems to be winning over many of Wall Street's brightest minds. The ability to make a significant impact and work on cutting-edge technology is proving irresistible, signaling a potential paradigm shift in the talent landscape of both industries.