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Mercor is seeking a science-focused role to design evaluation challenges for frontier AI models in drug research. You will build data rooms grounded in real sources and write graders to assess reasoning quality, with 20–40 hours weekly commitment.
Tools include Claude Code and Claude Max, in-browser studio work. The role requires deep expertise in mechanistic enzymology or related areas, and the ability to defend non-obvious conclusions.
This is an evaluation framework for frontier AI models in drug research and development. Domain experts write realistic research problems wrapped around messy evidence worlds. The model works offline in a sandbox with open-source scientific tooling, receiving incomplete, indirect and sometimes misleading data, and must reach a defensible conclusion. The answer is present in the evidence but never stated.
Your job is to build a research problem so realistic and well-constructed that the model has to genuinely reason to solve it — it can't pattern-match or look the answer up.
You are the final authority on every scientific and difficulty question in your task.
Minimum 20 hours per week, up to 40.
Work happens in a browser-based studio plus Claude Code. A Claude Max subscription is required and is fully reimbursed.