Computational Mathematics AI Problem Designer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI is recruiting and contracting for this role, giving specialists a way to apply their expertise to advanced AI development while building a durable professional profile.

Creating an OpenTrain account is free, and candidates can build a profile and apply in minutes.

About AI Training Work

AI training is the human side of building artificial intelligence. People with deep subject-matter expertise create examples, evaluate model outputs, and improve the quality of the data used to train modern language models.

This work places specialists close to cutting-edge AI development. It can also provide flexible, fully remote opportunities that fit around other professional or academic commitments.

The Role

OpenTrain is seeking a Computational Mathematics AI Problem Designer to create and solve challenging scientific problems for training and evaluating advanced language models. You will work with research-grade and graduate-level computational mathematics content, develop Python-based solutions, and apply rigorous standards for accuracy, reliability, and logical coherence.

The assignment combines original problem creation with structured quality review and collaborative refinement. It is a fully remote freelance contractor engagement lasting three months.

• Work remotely as a part-time freelance contractor
• Commit to at least 20 hours per week
• Choose a schedule of 20, 30, or 40 hours weekly
• Maintain four hours of overlap with PST
• Work primarily in English

What You'll Do

You will produce rigorous computational mathematics content that can test advanced reasoning and scientific coding capabilities. Each problem and solution should be mathematically accurate, logically consistent, and appropriately documented.

• Design original research-grade or graduate-level computational mathematics problems
• Use scientific coding and Python to develop elegant computational solutions
• Verify solutions for mathematical accuracy and logical consistency
• Define categories, secondary tags, and suitable difficulty levels for each item
• Conduct two-tier reviews of problem statements and solutions
• Identify accuracy and quality issues during review
• Incorporate feedback from reviewers and team leads
• Refine problems, solutions, and supporting documentation

Requirements

This role requires advanced academic expertise in computational mathematics and the ability to reason carefully about quantitative problems. You should be comfortable creating graduate-level content, checking solution reliability, and communicating clearly during collaborative review.

• PhD or current PhD candidacy in Computational Mathematics
• At least one published peer-reviewed paper
• Ability to design graduate-level quantitative problems
• Ability to assign appropriate categories and difficulty levels
• Strong mathematical rigor when verifying accuracy, logic, and reliability
• Clear written and verbal communication
• Ability to incorporate review feedback
• Advanced Python programming for scientific coding is preferred

Who Should Apply

This opportunity is designed for a computational mathematics researcher or doctoral candidate who wants to apply rigorous mathematical and programming expertise to AI training. It is especially relevant to candidates who enjoy creating challenging problems, developing precise solutions, and improving technical content through structured review.

• Computational mathematics PhD holders
• Current Computational Mathematics PhD candidates
• Researchers with peer-reviewed publication experience
• Scientific programmers with strong Python skills
• Quantitative problem solvers who value precision and logical coherence

Engagement Details

This is a three-month, fully remote freelance contractor assignment. The expected commitment is 20 or more hours per week, with available options of 20, 30, or 40 hours weekly. The schedule must include four hours of overlap with PST.

• Engagement type: Freelance contractor
• Work arrangement: Fully remote
• Duration: Three months
• Weekly commitment: 20, 30, or 40 hours
• Minimum availability: 20 hours per week
• Required overlap: Four hours with PST

Apply Through OpenTrain

AI training and data-labeling work helps shape how advanced AI systems solve problems, communicate, and perform technical tasks. If you meet the academic and publication requirements, create a free OpenTrain account, build your profile, and apply for this opportunity in minutes.

• Create a free OpenTrain account
• Showcase your computational mathematics background
• Highlight your publication and Python experience
• Apply to the role through OpenTrain