Mechanical & Aerospace Engineering Task Lead (AI Projects)

About the role

A boutique consultancy specialising in IT professional services and engineering talent solutions is looking for an experienced Mechanical or Aerospace Engineering expert to lead a team of technical trainers developing realistic, terminal-based engineering tasks for advanced AI training and evaluation. The role oversees a pod of about 5-10 trainers, reviews tasks for engineering accuracy and reproducibility, and ensures automated graders reliably assess technical outcomes. It is a 4-week contractor assignment, paid hourly up to 40 hours per week, fully remote.

Key responsibilities

• Lead and mentor 5-10 technical trainers, ensuring consistent task quality, productivity and on-time delivery.
• Review tasks end to end, including problem statements, geometry and mesh files, simulation inputs, material properties, reference solutions and automated tests.
• Validate tasks covering FEA, CFD, thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion and orbital mechanics.
• Check engineering correctness across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames and numerical stability.
• Verify computational environments, simulation tools, solvers and dependencies so results are reproducible.
• Review automated graders to ensure they assess meaningful outputs such as stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters and safety margins.
• Identify technical inaccuracies, unrealistic assumptions and incorrect tolerances, then give actionable feedback and track revisions.
• Onboard trainers, allocate work, monitor quality and throughput, resolve blockers and maintain technical documentation.

Required profile

• PhD, postdoctoral experience or equivalent advanced technical expertise in Mechanical, Aerospace or a closely related discipline.
• Experience reviewing complex technical work, engineering simulations, computational models or research outputs.
• Ability to judge engineering assumptions, numerical accuracy, solver convergence and computational reliability.
• Strong analytical judgment and ability to spot technical errors and flawed assumptions.
• Experience mentoring, reviewing or leading small technical teams.
• Excellent written communication for precise technical feedback and documentation.

Required skills

• Strong programming in Python, C/C++, Fortran, Julia or MATLAB/Octave.
• Proficiency in Linux and command-line environments.
• Hands-on expertise in at least one area such as FEA, CFD, dynamics, flight simulation, thermal modeling, astrodynamics, GNC or propulsion modeling.
• Understanding of engineering simulation, numerical methods, computational modeling and technical validation.