AI Trainer (Mathematics & Statistics)

micro1 Inc.; United States; A distancia; USD 83.000 - 165.000; A tiempo parcial

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Python

Mathematical specialization

Numerical analysis

Optimization

Educación

Master's degree

PhD

Herramientas

NumPy

SciPy

SymPy

pandas

Pyomo

OR-Tools

Lean

Coq

Descripción del empleo

Pay: $60–$120/hour equivalent, paid per accepted task

Location: Global, fully remote

Job Type: Contractor

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.

What You’ll Work On

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

Required Qualifications

1. Prior paid experience training, evaluating, benchmarking, or improving AI systems on mathematical or technical tasks.
2. Strong practical proficiency with Python.
3. Deep expertise in at least one relevant mathematical specialization.
4. 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.

Public Proof of Skill

Strong applicants should provide evidence such as:

1. Peer-reviewed publications or preprints
2. Public mathematical, statistical, or optimization code
3. Google Scholar, ORCID, arXiv, or equivalent research profiles
4. Open-source numerical or mathematical software contributions
5. Competition, theorem-proving, or optimization results
6. Reproducible notebooks, models, proofs, benchmarks, or technical projects

Preferred Qualifications

1. Experience creating AI-training tasks, reference answers, rubrics, graders, or benchmark problems.
2. Experience reviewing other AI trainers’ technical submissions.
3. A master’s degree, PhD, or equivalent record of substantial computational work.
4. Experience with NumPy, SciPy, SymPy, pandas, Pyomo, OR-Tools, Lean, Coq, or comparable tools.
5. Experience validating numerical solutions, statistical results, optimization outputs, or formal proofs.
6. Availability to begin immediately.

Compensation

1. Compensation is output-based. Experts are paid for tasks that meet project specifications and quality requirements. Task availability and completion time may vary.