Physics Expert

In this role, you will create and evaluate advanced Physics problems, develop structured solutions, and collaborate with researchers to enhance AI reasoning and evaluation systems.

This opportunity is ideal for candidates with strong academic backgrounds in Physics or Applied Physics who are passionate about research, problem-solving, and AI innovation.

• Design and solve challenging Physics problems to evaluate AI model capabilities

• Develop clear, step-by-step solutions with strong scientific reasoning

• Collaborate with LLM researchers to improve evaluation quality

• Help create Physics evaluation benchmarks spanning undergraduate to PhD-level topics

• Analyze areas where AI models struggle, including abstraction and symbolic reasoning

• Provide detailed annotations and constructive feedback

• Master’s degree, Ph.D., Postdoctoral degree, or currently pursuing advanced studies in:

  • Physics

  • Applied Physics

  • Related fields

• Strong analytical and research skills

• Excellent English communication and comprehension skills

• Ability to work independently in a remote environment

• Reliable desktop/laptop and internet connection

• Availability for 40 hours/week with at least 4 hours overlap with PST

Candidates should be proficient in at least three of the following tools:

QuTiP, OQuPy, QuSpin, TenPy, Strawberry Fields, openEMS, ngspice, Quantum ESPRESSO, OpenFOAM, FEniCS/FEniCSx (DOLFINx), WarpX, REBOUND, PYTHIA, Kwant, Elmer FEM, GF180MCU PDK, Sky130 PDK, FreeCAD, Project Chrono, Scilab Xcos, volare, emcee, Icarus Verilog, GTKWave, Verilator, gmsh, Elmer, pyarmadillo, and MeshLab.

• LinkedIn profile must be included in the resume

• Candidates will undergo background verification after onboarding

• Work allocation begins only after successful verification

• This is a freelance/contractor engagement with no medical or paid leave benefits

• Fully remote work environment

• Opportunity to work on cutting-edge AI projects

• Collaborate with leading LLM research teams

• Potential contract extension based on performance and project requirements