Mathematics Professor/Researcher (PhD) | $60-$90/hr Remote
Overview
A remote contractor role for a Mathematics Professor or Researcher with a PhD. You’ll leverage deep mathematical expertise to train and refine AI systems by providing high quality input, problems, and explanations that enhance model reasoning. This position values domain knowledge over AI experience and invites seasoned academics to shape the future of AI through rigorous math work.
What You'll Do6
- 1Review complex mathematical material to supply precise feedback and domain insights for AI training
- 2Create original problems, proofs, and instructional content across undergraduate and graduate topics
- 3Annotate and improve mathematical datasets to ensure accuracy and pedagogical value
- 4Collaborate with subject matter experts and stakeholders to set quality standards and coverage goals
- 5Draft clear written solutions and explanations tailored for AI learning and reasoning
- 6Participate in iterative review cycles to strengthen data robustness and diversity
Requirements6
- 1PhD in Mathematics or a closely related quantitative field
- 2Experience teaching at the university level or conducting advanced mathematical research
- 3Ability to communicate complex ideas clearly in writing and speech
- 4Strong analytical skills with meticulous attention to detail in mathematical work
- 5Familiarity with current mathematical literature and ongoing research trends
- 6Experience creating learning materials or problem sets for math education is a plus
Who Should Apply
Ideal candidates are seasoned mathematicians who enjoy teaching and research, want to influence AI development through rigorous math input, and excel at explaining complex concepts clearly. You should be comfortable working independently in a remote setup and collaborating with cross disciplinary teams.
Salary Insight
Compensation is available on an hourly basis in the range of $60 to $90 per hour.
Location
Required Skills
Application Tip
Prepare a brief portfolio snippet showing your approach to translating a math concept into AI training material and include a short example of a published problem or proof you authored.
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