AI Trainer (Mathematics & Statistics)

About the Role

Pay: $60–$120/hour equivalent, paid per accepted task Time Commitment: 15+ hours per week Schedule: Flexible micro1 is looking for Computational Mathematicians, Statisticians, and Optimization Experts with prior professional AI-training or model-evaluation experience to support a project focused on improving advanced AI systems. You will use your mathematical expertise and programming skills to create challenging technical tasks, evaluate model-generated code and reasoning, identify failures, and establish objective standards for correct solutions. This role is intended for candidates who have completed substantive AI-training work involving mathematical, statistical, or optimization content. Public Proof of Skill Strong applicants should provide evidence such as • Peer-reviewed publications or preprints • Public mathematical, statistical, or optimization code • Google Scholar, ORCID, arXiv, or equivalent research profiles • Open-source numerical or mathematical software contributions • Competition, theorem-proving, or optimization results • Reproducible notebooks, models, proofs, benchmarks, or technical projects Application Process • Submit your application, AI-training experience, specialization, and public technical evidence. • Complete an AI interview containing technical and integrity checks. • Complete a hiring-manager review. • If selected, complete project onboarding and begin your first assigned task. Compensation • Compensation is output-based. Experts are paid for tasks that meet project specifications and quality requirements. Task availability and completion time may vary.

Responsibilities & Tasks

• 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.

Qualifications & Requirements

• 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.
• Relevant specializations may include applied mathematics, scientific computing, operations research, optimization, formal mathematics, theorem proving, probability, statistics, numerical methods, and mathematical modeling.
• Experience creating AI-training tasks, reference answers, rubrics, graders, or benchmark problems.
• Experience reviewing other AI trainers’ technical submissions.
• A master’s degree, PhD, or equivalent record of substantial computational work.
• Experience with NumPy, SciPy, SymPy, pandas, Pyomo, OR-Tools, Lean, Coq, or comparable tools.
• Experience validating numerical solutions, statistical results, optimization outputs, or formal proofs.
• Availability to begin immediately.

Eligibility