This is not a traditional job — you'll draw on your hands-on experience in numerical simulation, scientific computing, or your physics subfield to evaluate AI-generated content and provide feedback that helps AI reason like a practicing physicist.

This is an ongoing, project-based opportunity you can take on alongside your current role.

Complete tasks at your own pace with no set schedule or minimum hour requirement.

• Use your domain expertise to create expert-level physics problems and scenarios grounded in real simulation, modeling, and computational workflows.
• Review and evaluate AI-generated responses for technical accuracy, numerical rigor, and alignment with how the work is actually done.
• Provide structured written feedback to help improve AI model performance.

Ideal candidates meet all three of the following:

• Industry/research experience — first-author publications in a computational subfield or 2+ years of hands-on industry experience.
• Degree — PhD in Physics, with a computational or theoretical focus.
• Sub-domain depth — demonstrated expertise in one of the following areas:
  • Numerical simulation, PDE/ODE solvers, and Monte Carlo methods.
  • HPC and scientific computing (NumPy/SciPy, C++/Fortran).
  • A core subfield such as condensed matter, astrophysics, high-energy physics, or fluid dynamics.

Candidates who meet at least 2 of the 3 qualifications above are also encouraged to apply.

Additional qualifications (not required, but strengthen your application)

• Proficiency running large-scale simulations on HPC clusters across multiple scientific computing environments.
• Experience with lattice methods or other specialized techniques within your subfield.

Required for all applicants

• Must have US work authorization.
• Strong written communication and attention to detail.
• Ability to explain complex physics concepts clearly.
• Ability to work independently in a remote, asynchronous environment.

Work arrangement: Fully remote

Eligible countries: United States