The research teams behind the best-known AI models come to Mercor for materials science judgment they can't generate on their own. Your standards and expertise become the rubric that frontier AI is graded against.
This is a standing listing for materials scientists who want AI training and evaluation work, not a specific job opening. It stays open whether or not a matching project is running this week.
New projects start on short notice, so instead of posting and pulling a listing each time, we keep one open per field and draw from it when one begins.
We match materials scientists in the network to projects like:
Writing a materials problem from work you have done, with the system, the processing history, and the property target, plus the reference answer a model's attempt gets graded against
Grading model-written structure-property reasoning: whether the microstructure explains the property, whether the characterization supports the claim, whether the processing window is realistic
Flagging where a model's proposed material meets the spec on paper and fails in service, given fatigue, corrosion, thermal cycling, or what can actually be manufactured
Past rates have run $60 to $120 an hour, set per project by scope and depth.
A graduate degree in materials science or a related field, with research or industrial experience
Clear written communication, since most of the work involves explaining your reasoning
Comfort with ambiguous tasks, and willingness to flag unclear instructions
Where you trained matters less than whether you processed and characterized the material yourself, recently enough to explain the calls you made.
This listing does not accept or reject candidates, so you will not get a decision on it. We reach out when a project matches your background. Depending on what our clients are running, that can be within a week or several months.
Finishing the domain expert interview and joining every network you qualify for both improve your odds of being matched. You only need to sign up once to be eligible across all of them.
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