AI Trainer – Mathematics & Statistics

AI Trainer – Mathematics & Statistics

Compensation: $60–$120/hour equivalent (Paid per accepted task)

Location: Global | Fully Remote

Employment Type: Contract

Time Commitment: 15+ hours per week

Work Schedule: Flexible

About the Role

We are looking for Computational Mathematicians, Statisticians, and Optimization Experts with prior professional experience in AI training, model evaluation, or benchmarking to contribute to a project focused on improving advanced AI systems.

In this role, you will leverage your mathematical expertise and programming skills to design challenging technical tasks, evaluate AI-generated mathematical reasoning and computational solutions, identify errors, and establish objective standards for accuracy and correctness.

This opportunity is ideal for professionals with strong mathematical foundations, hands-on computational experience, and a proven background in AI training or model evaluation.

Key Responsibilities

• Design challenging computational mathematics, statistics, and optimization tasks to evaluate advanced AI models.
• Develop detailed task instructions, reproducible environments, reference solutions, and evaluation criteria.
• Evaluate AI-generated mathematical proofs, calculations, statistical models, optimization solutions, and code.
• Identify logical errors, incorrect assumptions, numerical instability, and methodological weaknesses.
• Validate mathematical reasoning, computational accuracy, and reproducibility of technical solutions.
• Establish objective grading standards and quality benchmarks for AI-generated outputs.

Required Qualifications

• Prior paid professional experience in AI training, model evaluation, benchmarking, or improving AI systems, particularly involving mathematical or technical tasks.
• Strong hands-on proficiency in Python.
• Deep expertise in at least one relevant mathematical specialization.
• Practical experience applying computational methods in numerical analysis, optimization, statistics, theorem proving, mathematical modeling, or scientific computing.
• Strong analytical and problem-solving abilities with the ability to evaluate complex mathematical reasoning.

Relevant Specializations Include:

• Applied Mathematics
• Computational Mathematics
• Probability and Statistics
• Scientific Computing
• Operations Research
• Mathematical Optimization
• Numerical Methods and Analysis
• Formal Mathematics and Theorem Proving
• Mathematical Modeling

Public Proof of Technical Expertise

Applicants should be able to demonstrate their expertise through publicly accessible evidence, such as:

• Peer-reviewed research publications or preprints.
• Google Scholar, ORCID, arXiv, or equivalent research profiles.
• Public mathematical, statistical, or optimization projects.
• Open-source contributions to numerical or mathematical software.
• Competition, theorem-proving, or optimization achievements.
• Reproducible research notebooks, computational models, proofs, or technical benchmarks.

Preferred Qualifications

• Experience creating AI-training tasks, reference solutions, evaluation rubrics, graders, or benchmark problems.
• Experience reviewing and evaluating technical submissions from other AI trainers.
• Master's degree, PhD, or equivalent demonstrated computational research experience.
• Familiarity with tools and libraries such as NumPy, SciPy, SymPy, pandas, Pyomo, OR-Tools, Lean, or Coq.
• Experience validating numerical solutions, statistical results, optimization outputs, or formal mathematical proofs.
• Availability to start immediately.