OpenAI researcher calls job-hopping “test drives”

Gabriel Petersson, an OpenAI researcher, says early-career tech workers should treat early moves between teams and employers as “test drives” rather than fearing the “job-hopper” label. Petersson argues young engineers need real data on research projects, cult

On Sunday, Gabriel Petersson posted a message aimed directly at the anxiety young tech workers feel when recruiters warn them about becoming “job-hoppers.”

In several X posts, the OpenAI researcher argued that early-career engineers should do the opposite of what many mentors advise. Instead of locking themselves into one company too quickly. Petersson said they should test out different teams—collecting real information before they “anchor themselves” to a single place.

“Young tech workers should test out different teams before anchoring themselves to one company,” Petersson wrote in posts on Sunday, framing the early years as research, not commitment.

His reasoning was blunt. Early engineers, he said, need data points—about research projects, about culture, and about their own market value—before making a long-term bet. Petersson called the traditional advice to stay at one company for a long time and avoid moving around “braindead.”

“Please don’t take the advice that you should stay at a company long and ‘not hop around’ for your first jobs. ” he wrote. “please don’t take the advice that you should stay at a company long and ‘not hop around’ for your first jobs it’s absolutely braindead to decide on a long term bet with zero datapoints on what a good team looks like and long before you have priced yourself into the market.”.

Petersson also pushed back on the idea that frequent moves automatically reflect a lack of commitment. He suggested young engineers instead use a fast approach to building their careers. “Just tell people you are looking for internship or you want to ‘try working together for a month’ or say you’re a contractor. ” he wrote.

He argued that this approach can benefit everyone because both sides get information they can use to “price yourself in.” In his view, moving early isn’t a gamble—it’s a way to reduce uncertainty.

There is history behind Petersson’s perspective. He himself hopped around before landing an AI research position at OpenAI in 2024. when he was 23. according to his GitHub profile. Before that. his LinkedIn profile shows he worked as a software engineer at Dataland and Midourney for less than two years each.

Petersson also described a nontraditional path into tech. He dropped out of high school in Sweden at 17 to focus on building AI start-ups.

The “job-hopper” debate isn’t confined to one engineer’s opinion. Petersson isn’t the only tech personality to make the case for job-hopping. In April, when asked to grade some common career advice, Ryan Roslansky, LinkedIn’s former CEO, gave job-hopping for more money an “A.”

But for many young workers, the stakes feel higher than they did in the middle of easier hiring cycles. Tech companies including Meta, Oracle, Microsoft, and Block have announced major layoffs in recent months. Challenger. Gray & Christmas. a layoff-tracking firm. said that while fewer employers are cutting jobs overall this year. layoffs in the tech sector are up 40%.

Entry-level and engineering jobs have also been hit hard by AI, making the post-college job hunt harder for many young Americans—and raising the stakes for those who do land a role.

Petersson, though, said the warning against early movement can miss the reality of how careers actually form. He pointed to what he described as the best engineers he knows—people who, he said, spent years at early jobs that were not valuable stepping stones once viewed with hindsight.

He gave an example: an engineer who spent “2.5 years at a startup,” making $80,000, before later landing a multimillion-dollar deal.

In his posts, Petersson acknowledged that the story doesn’t always end with a correction. He wrote that some workers strike it rich by joining the right company early—early engineers at fast-growing startups. or those landing at a frontier AI lab. He said those outcomes can make life-changing money, but he also drew a line around how common they are.

“These are extremely rare,” he wrote. “Ask any great engineer and you’ll realize how many years they wasted with bad companies.”

Petersson and OpenAI did not immediately respond to requests for comment.

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