OpenAI Is Offering You $445,000 To Solve Problems That Don’t Exist

If the job works, someone will be paid $445,000 a year to prevent problems that do not exist, caused by systems that are not finished, inside a future that has not arrived yet. If it fails, it will still have achieved something remarkable: proving that even in the age of artificial intelligence, humans remain fully capable of inventing extremely expensive ways to worry about things in advance. Either way, it may be the first job description where success and failure both depend on whether reality eventually decides to cooperate with the job listing.

OpenAI is offering up to $445,000 for a research role focused on anticipating artificial intelligence risks that may not currently exist, underscoring how leading AI labs are increasingly investing in “pre-emergent” safety work.

The position, part of OpenAI’s Preparedness team, is designed to examine speculative but high-impact scenarios, including what happens if AI systems become capable of improving themselves without human oversight.

“This work relies on reasoning about problems that might exist in the future, but might not exist now,” the job listing says, according to Business Insider. “So it’s especially important that people in this role are tasteful and strategic.”

The role is a senior machine learning engineer position and sits at the intersection of safety research and long-term systems design, reflecting growing concern inside the company about recursive self-improvement, where AI systems could potentially train more capable versions of themselves.

Rather than focusing only on existing technical failures, the Preparedness team is tasked with identifying risks before they emerge at scale, including model misuse, system autonomy, and unexpected behavioral shifts in advanced systems.

The job description suggests the researcher may also evaluate how much of OpenAI’s internal research work could already be automated by AI systems, effectively assessing whether the company’s own technical workforce could be partially replaced by its models.

“This is urgent, fast-paced work that has far-reaching implications for the company and for society,” the Preparedness postings say, according to Business Insider.

The framing of the role highlights a central tension in frontier AI development: building systems capable of accelerating scientific discovery while simultaneously trying to predict and contain risks those same systems may create.

OpenAI chief executive Sam Altman has previously described ambitions for increasingly autonomous AI researchers, including an “automated AI research intern” operating at large scale in the near term, followed by more capable systems later this decade.

In October, Altman said the company aimed to run such systems on large compute clusters within months and eventually build a “true automated AI researcher” by 2028, while acknowledging uncertainty about whether those targets are achievable.

Industry leaders have echoed similar concerns about accelerating capabilities. Google DeepMind chief executive Demis Hassabis has described current progress as the “foothills of the singularity,” while researchers across the field increasingly debate how to manage systems that may outpace human-designed safety frameworks.

The Preparedness team’s mandate reflects a broader shift in the industry toward trying to solve future failure modes before they are fully understood, effectively building safeguards for systems that do not yet exist but are considered increasingly plausible.

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