Chemical Engineering Pod Lead

Lead a pod of 5 to 10 technical trainers creating terminal-based chemical engineering tasks for AI training and evaluation. Ensure technical accuracy, reproducibility and reliable automated grading.

• Review task statements, reaction kinetics, property data, flow sheets, reference solutions and automated tests.
• Validate reaction engineering, thermodynamics, phase equilibria, transport, separations, process control and optimization workflows.
• Verify mass and energy balances, units, thermodynamic consistency and numerical convergence.
• Review solver settings and graders for meaningful engineering outputs and prevent bypassed computations.
• Mentor trainers, provide actionable feedback, allocate work and monitor quality.

• Ph.D., postdoctoral experience or equivalent advanced technical experience in Chemical Engineering.
• Strong Python, Julia, C/C++ or MATLAB/Octave skills, with Linux proficiency.
• Expertise in process modeling, reaction kinetics, thermodynamic modeling, process simulation or optimization.
• Experience reviewing technical work, simulations or research outputs and leading small technical teams.
• Strong numerical methods, analytical judgment and written communication.

Cantera, Cool Prop, Pyomo, IDAES, DWSIM, CasADi or OpenFOAM;
Aspen Plus, Aspen HYSYS, gPROMS, Docker, Git, automated testing or AI evaluation experience.

Interest check form, AI interview and delivery review.