The difference between quant jobs in electronic trading and research jobs in an AI lab
In recent years, a tug of war has developed between prominent electronic trading firms and AI laboratories for talent. Last year, OpenAI was reportedly offering junior quants $3m compensation packages, and other labs like Anthropic were hosting dinners to tempt high-frequency trading quants to make the switch. If you're considering a move, an ex-Citadel Securities quant has revealed just how different AI research jobs are.
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Nimit Sohoni spent two years as a quant at Citadel Securities, joining as a graduate after completing his PhD. He's spent the last two years at Cartesia, a voice AI firm. Appearing on a podcast yesterday, he explained the differences between is current job and his time at Citadel Securities.
For one, he said quants in finance work far fewer hours than researchers in AI. In finance, Sohoni said he had "a pretty great life balance, as funny as that might sound." Sohoni said his finance colleagues were "really clustered working around trading hours and don't take their work home all too much." This was confirmed last year by ex-Jane Street engineer Leila Clark, who said Jane Street staff work nine-hour days on average.
It's not like that in AI. Sohoni said the AI space includes "a lot of people who are working around the clock." Competition for positions is high and "you can gain a comparative advantage just by outworking your competition." Ex-quants in AI have told us that the long hours aren't mandatory, but researchers choose to work late out of passion.
There are advantages, though. Sohoni said AI labs have far more open cultures, to the point that it was "jarring" for him to hear colleagues speak so openly about their projects. In finance, by contrast, "a lot of people are reluctant or even forbidden to talk about any details of what they do." Culture differs between the big and small AI labs, however. Sohoni said that the larger firms like OpenAI have massive compute power, but "can be more averse to out-of-the-box ideas and more susceptible to groupthink."
Both AI and finance pay well. Sohoni said the two offer the potential to earn "NBA salaries." In quant finance, however, pay is "not exactly outlandish" and outperformance is difficult to achieve. "Hard metrics [mean] that it's easier to evaluate how somebody does, especially if you're an alpha quant."
He said finance quant careers can become "U-shaped" as a result. Seniority comes with higher pay, but the quality of your alpha can't always keep up. "Even a good quant can stop being worth it after a while," he said, "whereas early career quants might be very good and also not command as much of a salary." AI labs seem to have much more reverence for their senior staff; according to Levels.fyi, OpenAI is the second-highest paying firm in the world for staff engineers, and fifth-highest for principal engineers.
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