Physicist, PhD

Physicist, PhD (AI Training)

About the Role

What if your years of physics expertise could directly shape how AI reasons through the most complex problems in science? We're looking for PhD-level physicists to evaluate, critique, and help build the training data that teaches frontier AI models to think rigorously — from quantum mechanics to thermodynamics to electromagnetism.

This is a fully remote, flexible contract role. No AI background needed — just deep domain expertise, a sharp analytical mind, and a passion for scientific precision.

• Type: Hourly Contract
• Location: Remote
• Commitment: Minimum 15 hours/week, fully asynchronous

What You'll Do

• Develop and refine advanced physics questions spanning specialized subfields — from classical mechanics to quantum field theory
• Review and evaluate AI-generated solutions to physics problems, identifying errors, logical gaps, and conceptual misunderstandings
• Annotate and categorize physics problems, concepts, diagrams, and experimental data to support model training
• Map relationships between key physics principles and subfields to help AI models grasp the structure of the discipline
• Contribute to building high-quality training datasets that span a full range of topics and difficulty levels
• Provide clear, structured feedback that directly improves how AI models reason through scientific problems

Who You Are

• You hold a PhD in physics or a closely related field, with demonstrated expertise through research, teaching, or advanced problem-solving
• You have experience developing or critically reviewing sophisticated scientific content — such as research publications, curriculum design, problem sets, or technical simulations
• You can communicate complex physical concepts with clarity, and enjoy translating abstract theory into precise, well-reasoned explanations
• You're detail-oriented, methodical, and hold yourself to a high standard of scientific rigor
• You're self-motivated and comfortable working independently in an asynchronous environment

Nice to Have

• Experience with data labeling, RLHF, or other AI training or model evaluation workflows
• Background spanning multiple subfields — e.g., condensed matter, astrophysics, optics, nuclear, or computational physics
• Experience writing or reviewing technical educational content at the graduate level

Why Join Us

• Work on cutting-edge AI projects alongside leading research labs and top AI teams
• Fully remote and asynchronous — work when and where it suits you
• Freelance autonomy with the structure of meaningful, expert-level work
• Make a direct, tangible impact on how AI models understand and reason through science
• High-performing contributors take the lead on new programs and mentor incoming subject matter experts
• Potential for ongoing work and contract extension as new projects launch