Mathematical Content Review Specialist

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect expert contributors with projects that teach and refine AI systems, helping people build durable freelance careers in a fast-growing part of tech.

OpenTrain is the hiring and contracting organization for this role; you will work directly with our project teams to create high-quality mathematical data that trains next-generation models.

Why AI training matters (quick overview)

AI training—also called data labeling or human feedback work—is the human side of building intelligent systems. People prepare and evaluate examples that models learn from, and contributors directly influence model behavior, accuracy, and safety.

This project focuses on mathematical content: your work will improve model reasoning, problem solving, and instructional capability in advanced math topics.

The role

You will review and evaluate advanced mathematical content, author original problems and proofs, refine datasets for depth and pedagogical quality, and produce clear explanations and instructional material that help AI systems learn mathematical reasoning.

This is a remote, contract, part-time role at 20+ hours/week. Compensation is hourly, $60–$90 USD per hour, paid per OpenTrain terms.

• Commitment: 20+ hours/week (part-time, contractor)
• Pay: Hourly, USD $60–$90/hr
• Data type: Text; label types include evaluation/rating and text generation

What you'll do day to day

Your core work combines careful review with original content creation. Tasks are iterative and quality-driven: annotate, critique, and elevate mathematical examples so models learn correct reasoning and clear explanations.

• Evaluate and rate advanced mathematical content for accuracy, rigor, and pedagogy
• Write original problems, solutions, proofs, and worked examples across advanced topics
• Draft clear explanations and instructional materials suitable for model training
• Annotate datasets to improve coverage, clarity, and difficulty calibration
• Participate in review cycles with subject-matter experts to refine quality standards

Requirements

You must meet the essential qualifications below; we will assess submissions and sample work during selection. The role emphasizes precision, clarity, and deep subject expertise.

• PhD in Mathematics or a closely related quantitative field (required)
• Experience teaching mathematics at the university level or conducting advanced mathematical research
• Strong written and verbal communication skills for explaining intricate mathematical concepts clearly
• Proven ability to create original problems, proofs, solutions, and instructional materials
• Analytical rigor and attention to detail when reviewing mathematical content

Helpful background (not required)

These experiences will strengthen an application but are not mandatory. If you have them, highlight them in your submission.

• Experience creating curricula, problem sets, or other learning materials for mathematics education
• Interest or prior exposure to AI and how models learn from annotated data

How selection and work flow

OpenTrain will review qualifications and sample tasks. Selected contributors will receive onboarding materials, dataset guidelines, and iterative feedback from the project team to align work with quality standards.

Work is delivered remotely through OpenTrain workflows. Tasks include evaluation ratings and text-generation-style contributions; expect collaborative review cycles to improve dataset robustness and diversity.

• Onboarding includes style guides, annotation instructions, and example annotations
• You will participate in iterative review and quality checks with project stakeholders
• Work assignments vary by project phase and may emphasize evaluation, creation, or both

How to apply

Apply through OpenTrain with your CV, a brief summary of relevant teaching or research experience, and samples of mathematical writing or problem sets if available. Highlight any prior instructional materials you authored.

Because this role requires a PhD, please include degree details and a short statement describing the topics you are most prepared to review or create (examples: algebraic topology, real analysis, PDEs, etc.).

• Provide CV, degree information, and 1–3 samples of mathematical work or teaching materials
• Indicate availability for 20+ hours/week and your preferred hourly rate within the posted range