Mathematics Expert, Python Computational Problem Designer

About OpenTrain AI

OpenTrain AI is the hiring and contracting organization for this role. OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect experienced contributors with projects that shape how state-of-the-art AI systems behave.

About AI training and this work

AI training (data labeling/annotation) is the human work that teaches models to reason, compute, and produce reliable outputs. Contributors create examples and verified answers that models learn from—this role focuses on research-style computational mathematics problems that help train and fine-tune advanced generative models.

This position blends mathematical creativity with reproducible coding: you will author non-trivial problems, produce clear prompts and statements, then verify solutions with Python and standard math libraries so results can be used for text generation, evaluation, and fine-tuning.

The role

We are hiring a Mathematics Expert to design original, computationally intensive, research-style math problems and provide fully verified answers with reproducible Python verification. OpenTrain AI hires contractors who produce content used for text generation, evaluation rating, and fine-tuning.

• Employment type: Contractor, part-time.
• Time commitment: 20+ hours per week.
• Work product: problem statements, annotated solutions, Python verification scripts and notes.

What you'll do

Create high-quality, original math problems that require multi-step reasoning and reflect realistic research workflows across topics such as number theory, combinatorics, graph theory, and numerical analysis. Each problem must include a clear statement, worked solution, and reproducible verification code.

• Design non-trivial problems that test multi-step reasoning and computational thinking.
• Write concise, unambiguous problem statements suitable for use as model prompts and evaluation items.
• Provide complete solutions and verification scripts in Python using standard libraries.
• Use NumPy, SciPy, SymPy and other standard packages to reproduce answers numerically or symbolically.
• Document verification steps so reviewers can reproduce results deterministically.

Requirements

You must meet the stated qualifications exactly as provided. We will verify credentials and evaluate sample problems and verification code during review.

• Bachelor’s degree or higher in Mathematics or a closely related field (required).
• 2+ years of relevant professional, research, or teaching experience in mathematics or computational math.
• Strong Python skills and hands-on experience with NumPy, SciPy, SymPy.
• Experience with computational and numerical methods and awareness of numerical stability.
• Knowledge of computational complexity concepts and ability to craft problems that require non-trivial reasoning chains.
• Hands-on text annotation or review experience (experience creating or reviewing prompts, answers, or annotated examples).
• Familiarity with research-style computational mathematics problems and workflows.

Pay, labeling use, and logistics

Pay structure: pay-per-hour. Hourly range shown in the posting: $15–$60 USD per hour (structured as PAY_PER_HOUR). Work will be used for TEXT_GENERATION, EVALUATION_RATING, and FINE_TUNING datasets. This is a contractor, part-time engagement.

• Data type: TEXT; label types: TEXT_GENERATION, EVALUATION_RATING, FINE_TUNING.
• Expected output: problem statements, final answers, and reproducible Python verification code.
• Work is remote; you will deliver artifacts and reproducible code for review.

Location restrictions and application details

This project has restricted locations for acquisition and cannot accept contributors located in or acquiring data from the following places: Iran, Cuba, North Korea, Syria, Sudan, Venezuela, Myanmar, Russia, Belarus, Palestine, Switzerland, China, Taiwan, Kenya, Alaska (USA), Arkansas (USA), California (USA), Connecticut (USA), Delaware (USA), Georgia (USA), Hawaii (USA), Illinois (USA), Indiana (USA), Kansas (USA), Louisiana (USA), Maine (USA), Maryland (USA), Massachusetts (USA), Nebraska (USA), Nevada (USA), New Hampshire (USA), New Jersey (USA), New Mexico (USA), Ohio (USA), Oregon (USA), Tennessee (USA), Utah (USA), Vermont (USA), Washington (USA), West Virginia (USA), 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 Islands, Heard Island and McDonald Islands, British Indian Ocean Territory, Northern Mariana Islands, Martinique, New Caledonia, Norfolk Island, Niue, French Polynesia, Saint Pierre and Miquelon, Pitcairn, Réunion, Saint Helena, Ascension and Tristan da Cunha, Svalbard and Jan Mayen, Sint Maarten (Dutch part), French Southern Territories, Tokelau, United States Minor Outlying Islands, Holy See, Virgin Islands (British), Wallis and Futuna, Mayotte.

To apply, submit a CV in English that states your level of English proficiency and includes an email address and phone number. You will be asked to provide sample problems and Python verification notebooks during the evaluation process.

• CV must be in English and include your English proficiency level, email, and phone number.
• Applicants will be evaluated on qualifications and sample problem submissions with reproducible code.