Job Description
Rigorous physics reasoning at the research level is one of the hardest problems for AI systems to get right. Chegg is seeking physics professionals to evaluate AI-generated derivations and advanced problem-solving, write publication-quality reference solutions, and expose precisely where AI physical reasoning breaks down. This is frontier-adjacent work spanning theoretical and computational physics — fully remote, asynchronous, and highly specialized.
Core Responsibilities
- Evaluate AI-generated derivations and solutions across advanced physics — quantum mechanics, electrodynamics, statistical mechanics, and general relativity — for rigor, correctness, and logical completeness
- Write publication-quality reference derivations and solutions with correct notation, complete mathematical steps, and airtight physical reasoning that AI models learn from
- Identify derivation errors, misapplied physical laws, dimensional inconsistencies, or hidden unstated assumptions in AI-generated content, tagging the specific error category
- Compare and rank multiple AI-generated derivations or solutions to the same problem, explaining which reflects superior rigor, correctness, and physical insight
- Where relevant, verify AI-generated numerical or symbolic solutions using computational tools, confirming physical consistency and correct boundary conditions
- Construct advanced problem sets and research-level challenges that probe the limits of current AI reasoning about the physical world
- Contribute to rubric design — defining scoring criteria such as rigor, correctness, logical completeness, and physical insight — used to benchmark AI physics reasoning at scale
- Complete asynchronous task batches independently — no scheduled calls or fixed hours required
Key Qualifications
- Master’s degree or PhD in Physics, Applied Physics, or a closely related quantitative field (or equivalent recognized qualification); relevant experience is a plus — postgraduate and doctoral graduates welcome
- Strong command across core areas of advanced physics — quantum mechanics, electrodynamics, statistical mechanics, or general relativity
- Able to write and critique rigorous physical derivations with correct notation, complete mathematical structure, and precise reasoning
- Sharp eye for subtle derivation errors, unit inconsistencies, or violations of physical principles — can detect and explain flawed reasoning in plain English
- Self-directed; capable of sustained independent focus on demanding, research-level problems
Nice to Have
- Computational proficiency in Python (NumPy, SciPy), MATLAB, or Mathematica for simulation and numerical problem design
- Hands-on experience with specialized tools such as COMSOL, LTspice, or symbolic computation packages
- Research background in condensed matter, photonics, quantum information, or biophysics
- Published research or graduate teaching experience in physics
- Familiarity with LaTeX and formal mathematical/physical typesetting
Why Chegg
- Fully remote and flexible — no fixed schedule
- Task-based commitment, typically 10–40 hours per week
- Real-world challenges with direct impact on AI accuracy and safety
- Pathway to ongoing projects for high-quality contributors