Mathematics Expert — Computational Problem Author

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect experts with projects that teach and shape how AI systems behave, offering flexible remote work that helps contributors grow careers in a fast-moving industry.

About AI training work

AI training (data labeling/annotation) is the human side of machine intelligence: people create, verify, and curate examples that modern models learn from. This role focuses on producing high-quality, research-like problem content and verified solutions that can be used for model fine-tuning, evaluation, and text generation tasks.

The role

You will design original, computationally intensive mathematics problems and provide fully reproducible verifications implemented in Python. Problems should require non-trivial reasoning chains and reflect realistic mathematical research workflows across topics such as number theory, combinatorics, graph theory, and numerical analysis.

• Create clear, self-contained problem statements suitable for training and evaluation datasets.
• Provide complete, verified answers with reproducible Python code using standard mathematical libraries.
• Deliver problems that exercise multi-step reasoning and realistic research-style workflows.

What you'll do day-to-day

Work independently to author problem sets and verification code, iterate on edge cases, and ensure reproducibility. Tasks will include both content generation and evaluation-style activities tied to model training and fine-tuning workflows.

• Draft original research-style problems in number theory, combinatorics, graph theory, and numerical analysis.
• Implement and verify solutions in Python using NumPy, SciPy, SymPy, and other standard libraries.
• Write clear, reproducible verification scripts and documentation so answers can be automatically validated.
• Provide evaluation ratings or annotations of problem difficulty, solution correctness, and reasoning clarity when requested.
• Collaborate with project leads to meet dataset quality standards and follow submission guidelines.

Requirements

The project requires solid academic credentials, proven experience, and hands-on technical ability. Preserve all requested submission details when applying.

• Bachelor’s degree or higher in Mathematics or a closely related field (required).
• 2+ years relevant professional, research, or teaching experience in mathematics or computational mathematics.
• Strong Python skills and experience with NumPy, SciPy, SymPy or equivalent mathematical libraries.
• Experience with computational and numerical methods and familiarity with computational complexity concepts.
• Hands-on text annotation or review experience (experience in producing or reviewing dataset content preferred).
• CV in English that indicates your level of English proficiency and includes an email address and phone number.

Restricted locations

Due to acquisition restrictions, applicants located in the following places cannot be hired for this project. Please do not apply from these locations.

• Iran, Cuba, North Korea, Syria, Sudan, Venezuela, Myanmar, Russia, Belarus, Palestine
• Switzerland
• China, Taiwan
• Kenya
• States of the USA: Alaska, Arkansas, California, Connecticut, Delaware, Georgia, Hawaii, Illinois, Indiana, Kansas, Louisiana, Maine, Maryland, Massachusetts, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, Ohio, Oregon, Tennessee, Utah, Vermont, Washington, West Virginia
• Antarctica, Aruba, Åland Islands, Saint Barthélemy, Bonaire, Sint Eustatius and Saba, Bouvet Island, Cocos (Keeling) Islands, Democratic Republic of the Congo, Cook Islands, Christmas Island, Western Sahara, Falkland Islands (Malvinas), French Guiana, Guadeloupe, South Georgia and the South Sandwich

Compensation, time commitment, and contract

This is a part-time contractor role with a minimum time expectation and hourly pay range set by the project.

• Time requirement: 20+ hours per week.
• Pay: hourly range $15–$60 USD per hour (projects may list top-of-range rates; final rate depends on experience and scope).
• Employment types: Contractor, Part-time.

How to apply

To be considered, submit your CV in English and include your level of English proficiency plus contact email and phone number. Applications should highlight relevant mathematics experience, sample problems or links to previous work if available, and examples of reproducible Python verifications.

• Provide a CV in English including email address and phone number.
• List degrees, research or teaching roles, and 2+ years of relevant experience.
• Include sample problems or verification scripts (if available) demonstrating use of NumPy/SciPy/SymPy and reproducible results.