Chemical Engineering Task Lead – AI Training & Evaluation

• Lead, mentor, and coordinate a team of 5–10 technical trainers, ensuring consistent quality, productivity, and timely delivery.
• Review engineering tasks end to end, including problem statements, reaction kinetics, thermodynamic and property data, process flowsheets, computational environments, reference solutions, and automated tests.
• Validate tasks involving reaction engineering, thermodynamics, phase equilibria, transport phenomena, separation processes, process simulation, process control, optimization, combustion, and electrochemical engineering.
• Ensure tasks reflect realistic chemical engineering workflows and require meaningful, multi-step technical reasoning.
• Verify mass and energy balances, thermodynamic consistency, property data, unit handling, numerical accuracy, and solver convergence.
• Validate computational models, stiff ODE/DAE solvers, tolerances, initial conditions, dependencies, and simulation results for reproducibility.
• Review automated graders to ensure they assess meaningful engineering outputs, including conversion, yield, selectivity, purity, energy consumption, and process constraint satisfaction.
• Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass genuine engineering calculations.
• Provide actionable technical feedback, track revisions, and ensure issues are resolved before task approval.
• Onboard trainers, allocate assignments, monitor quality and throughput, resolve technical blockers, and maintain documentation and best practices.

• PhD, postdoctoral experience, or equivalent advanced technical expertise in Chemical Engineering.
• Strong programming skills in Python, Julia, C/C++, or MATLAB/Octave.
• Proficiency in Linux and command-line environments.
• Hands-on expertise in at least one major area, such as process modeling, reaction kinetics, thermodynamic modeling, process simulation, or optimization.
• Strong understanding of chemical engineering fundamentals, numerical methods, computational modeling, and technical validation.
• Experience reviewing complex technical work, chemical process simulations, computational models, or research outputs.
• Ability to evaluate mass and energy balances, thermodynamic assumptions, numerical accuracy, solver convergence, and computational reliability.
• Strong analytical judgment and the ability to identify technical errors, edge cases, and flawed engineering assumptions.
• Experience mentoring, reviewing, or leading small technical teams.
• Excellent written communication skills for precise technical feedback and documentation.