AI Trainer: Computational Physical Sciences (Remote)

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

Job summary

micro1 Inc. seeks Computational Physical Scientists with AI-training or model-evaluation experience to develop challenging tasks that probe advanced AI systems.

You will craft realistic problems, establish evaluation criteria, and build reproducible environments to test model outputs and claims. The role emphasizes identifying errors, invalid assumptions, and reproducibility issues, requiring strong Python skills and deep domain knowledge in physics, chemistry, or related fields.

Qualifications

• Paid experience training, evaluating, benchmarking, or improving AI systems on scientific or technical tasks.
• Strong practical proficiency with Python.
• Deep expertise in at least one relevant physical-science specialization.
• Hands-on experience using computational methods for modeling, simulation, numerical analysis, data analysis, or reproducible research.

Responsibilities

• Create realistic computational physical-science tasks that challenge advanced AI models.
• Develop task instructions, reproducible environments, reference solutions, and evaluation criteria.
• Evaluate model-generated calculations, code, simulations, models, and technical deliverables.
• Identify invalid assumptions, numerical errors, physically impossible results, incorrect methods, or reproducibility failures.

Skills

Python

AI systems experience

Numerical analysis

Tools

NumPy

SciPy

SymPy

Astropy

PyTorch

JAX

Job description

micro1 Inc. seeks Computational Physical Scientists with AI-training or model-evaluation experience to develop challenging tasks that probe advanced AI systems.

You will craft realistic problems, establish evaluation criteria, and build reproducible environments to test model outputs and claims. The role emphasizes identifying errors, invalid assumptions, and reproducibility issues, requiring strong Python skills and deep domain knowledge in physics, chemistry, or related fields.