Overview
Responsibilities [About the Role]
We are looking for experienced physics professionals to help train and evaluate advanced AI models so they can reason like real-world physicists. In this role, you’ll use your domain expertise to design challenging physics problems, review AI-generated outputs, and establish clear scientific evaluation standards across classical, modern, and computational physics.
This is a flexible, remote freelance role that can be done alongside your research, teaching, or professional commitments.
[What You’ll Do]
As a Physics Expert – AI Trainer, you will:
• Evaluate AI-generated answers to physics questions for correctness, mathematical rigor, clarity, and conceptual depth.
• Design realistic physics scenarios, prompts, and multi-step problems (e.g., mechanics, E&M, thermodynamics, quantum, relativity, optics).
• Create scoring rubrics and structured evaluation guidelines to assess model performance across multiple subfields.
• Provide high-quality written feedback to improve the reasoning, derivations, and scientific explanations of AI models.
• Develop technically rigorous problem sets, conceptual explanations, or experiment-based questions depending on your specialization.
• Collaborate with AI research teams to refine datasets, tasks, difficulty levels, and evaluation methods over time.
Qualifications Bachelor’s, Master’s, or PhD in Physics or a closely related field.
(Experimental, Theoretical, or Computational Physics all welcome.)
At least 2–3 years of research, teaching, applied physics, or industry experience in one or more areas such as:
• Classical Mechanics
• Electromagnetism
• Thermodynamics / Statistical Mechanics
• Quantum Mechanics
• Relativity
• Optics & Photonics
• Condensed Matter Physics
• Astrophysics / Cosmology
• Computational Physics / Numerical Methods
• Engineering Physics or Applied Physics
Strong grasp of core physics concepts such as:
• Mathematical modeling, derivations, and problem solving
• Physical intuition and conceptual reasoning
• Experimental design, data interpretation, and error analysis
• Computational workflows (simulations, numerical solvers, modeling techniques)
Excellent written English, with the ability to explain complex physics concepts step-by-step with precision.
Notes
