WFH.teamOpen app$125k-$250k
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Decision details from the source listing
Master’s degree, PhD, or equivalent record of substantial computational work (preferred)
flexible
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What this posting tells you
Fully remote contractor role creating and evaluating computational mathematics and statistics tasks for AI systems. The listing states $60–$120/hour equivalent, paid per accepted task, with output-based compensation and variable task availability; no annual salary is stated. Time commitment is 15+ hours per week, with a flexible schedule. Specific country eligibility is not provided.
Backend, Customer success, Marketing, Operations, Product, Software, Customer support
Global; specific eligible countries not stated
Global
Expert · Contractor
Backend hiring on WFH.team
This role's listed pay is near the median among 200 comparable roles shown here. Category counts come from WFH.team's latest published remote job market snapshot.
Explore the remote job marketAI Trainer (Mathematics & Statistics) at micro1
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
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.
Required 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.
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
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
Preferred qualifications
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.
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.
Working remotely at micro1
micro1 builds human-expertise data and evaluation infrastructure for AI models and agents. It recruits core-team employees and domain experts for AI training projects.
- Headquarters
- San Francisco Bay Area, California, United States
- Founded
- 2022
Expert opportunities are remote and can be flexible. International applicants are considered, subject to country exclusions and each project's requirements. Core-team work arrangements vary by opening; check the individual posting.
Apply through the official posting. Expert applicants complete an AI interview and skills certification, followed by project selection and onboarding. Certification does not guarantee a project or immediate work.