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Mercor is seeking a research-oriented role focused on constructing realistic frontier AI evaluation tasks in drug research. You will craft problems that require genuine reasoning, build data sets anchored to real sources, and author robust grading criteria.
Role demands deep expertise in enzymology or related fields and the ability to defend complex conclusions. Flexible hours and browser-based tooling support this position.
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.
Three things per task: the prompt, the data room, and the grading document.
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.