Remote AI Math & Statistics Trainer — Contract

micro1 Inc.; United States; Remote; USD 83,000 - 165,000; Part time

Job summary

micro1 Inc. is seeking Computational Mathematicians, Statisticians, and Optimization Experts with AI-training experience to create challenging tasks for evaluating advanced AI systems. This contractor role offers flexible scheduling, roughly 15+ hours per week, and pay per accepted task.

You will design realistic problems, write instructions and reference solutions, and assess model proofs, code, and benchmarks to establish objective evaluation criteria for progress across global projects.

Qualifications

• Prior paid experience training, evaluating, benchmarking, or improving AI systems on mathematical or technical tasks.
• Strong practical proficiency with Python.
• Deep expertise in at least one relevant mathematical specialization.
• Hands-on experience using computational methods for numerical analysis, optimization, statistics, theorem proving, modeling, or scientific computing.

Responsibilities

• Create realistic computational mathematics and statistics tasks that challenge advanced AI models.
• Develop task instructions, reproducible environments, reference solutions, and evaluation criteria.
• Evaluate model-generated proofs, calculations, code, models, optimizations, and technical deliverables.
• Identify logical errors, invalid assumptions, numerical instability, incorrect statistical methods, or reproducibility failures.

Skills

Python

Mathematical specialization

Numerical analysis

Optimization

Education

Master's degree

PhD

Tools

NumPy

SciPy

SymPy

pandas

Pyomo

OR-Tools

Lean

Coq

Job description

micro1 Inc. is seeking Computational Mathematicians, Statisticians, and Optimization Experts with AI-training experience to create challenging tasks for evaluating advanced AI systems. This contractor role offers flexible scheduling, roughly 15+ hours per week, and pay per accepted task.

You will design realistic problems, write instructions and reference solutions, and assess model proofs, code, and benchmarks to establish objective evaluation criteria for progress across global projects.