Remote AI Physics Question Architect (PhD)

Mercor; San Francisco (CA); On-site; USD 55,000 - 103,000; Part time

Job summary

Mercor is seeking expert physicists to author and review rigorous academic assessment content for an AI research initiative. You will craft original physics questions across semiconductor physics, nanoelectronics, quantum optics, and more, rate difficulty levels, and provide a correct answer with 9 challenging distractors.

Remote, asynchronous work with 10+ hours per week. Ideal candidates hold a PhD or are doctoral candidates and can deliver step-by-step Chain-of-Thought solutions in markdown,

Qualifications

• PhD or doctoral candidate in Physics, Applied Physics, or closely related field.
• Master's degree considered for exceptional depth in a subdomain.
• Strong command of graduate-level physics concepts and mathematical formalism.

Responsibilities

• Author original physics questions that test deep conceptual understanding and measure problem-solving.
• Ensure questions are unambiguous, self-contained, and precisely defined with all necessary data in the prompt.
• Rate each question's difficulty: Medium, Hard, or Expert.
• Provide 1 correct answer and 9 plausible distractors.
• Write step-by-step Chain-of-Thought solutions in markdown format and supply 1–5 references per question.
• For verification tasks: flag clarity, completeness, precision, solvability and justify edits.

Skills

Problem design

Academic writing

Graduate physics

Education

PhD in Physics

Master's degree considered

Tools

LaTeX

Markdown

Job description

Mercor is seeking expert physicists to author and review rigorous academic assessment content for an AI research initiative. You will craft original physics questions across semiconductor physics, nanoelectronics, quantum optics, and more, rate difficulty levels, and provide a correct answer with 9 challenging distractors.

Remote, asynchronous work with 10+ hours per week. Ideal candidates hold a PhD or are doctoral candidates and can deliver step-by-step Chain-of-Thought solutions in markdown,