Mathematics Professor/Researcher (PhD)

Mathematics Professor/Researcher (PhD) – $60 - $90/hour pay

Role Type: Contractor

Location: Remote

About micro1

micro1 is a leading AI data lab focused on training frontier models and evaluating AI agents. Our experts bring diverse subject matter knowledge from finance, healthcare, STEM engineering, and more, converting real‑world expertise into high‑quality training data, evaluations, and feedback loops that enhance how AI systems learn, reason, and perform.

Scope of Work

• Review, analyze, and evaluate complex mathematical content to generate detailed feedback and domain‑specific insights for AI model training.
• Develop and contribute original mathematical problems, proofs, and teaching materials across a range of undergraduate and graduate topics.
• Annotate, critique, and refine mathematical datasets for accuracy, depth, and pedagogical value.
• Collaborate with other subject matter experts and project stakeholders to define quality standards and subject coverage.
• Draft and edit clear written explanations, solutions, and instructional content tailored for AI learning and reasoning tasks.
• Participate in iterative review cycles to enhance the robustness and diversity of mathematical data.

Required Skills

• Advanced mathematics expertise.
• Research experience.
• Teaching experience.
• PhD in Mathematics or related field.

Preferred Qualifications

• PhD in Mathematics or a closely related quantitative field.
• Demonstrated experience in university‑level teaching or advanced mathematical research.
• Proven ability to communicate intricate mathematical concepts with precision and clarity, both in writing and verbally.
• Strong analytical skills and attention to detail in reviewing mathematical work and educational content.
• Familiarity with contemporary mathematical literature and ongoing research trends.
• Experience developing learning materials or problem sets for mathematics education is a plus.
• Intellectual curiosity about artificial intelligence and its implications for mathematical discovery and instruction.