Mechanical and Aerospace Engineering Task Lead – AI Project

• Lead and mentor a team of 5–10 technical trainers, ensuring consistent task quality, productivity, and timely delivery.
• Review engineering tasks end to end, including problem statements, geometry and mesh files, simulation inputs, material properties, reference solutions, and automated tests.
• Validate tasks involving finite-element analysis (FEA), computational fluid dynamics (CFD), thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion, and orbital mechanics.
• Ensure tasks reflect realistic mechanical and aerospace engineering workflows and require meaningful, multi-step technical reasoning.
• Verify engineering correctness across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames, and numerical stability.
• Validate computational environments, simulation tools, solvers, and dependencies to ensure reproducible results.
• Review automated graders to ensure they assess meaningful engineering outputs, including stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters, and safety margins.
• Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass genuine engineering calculations or simulations.
• Provide actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval.
• Onboard trainers, allocate work, monitor quality and throughput, resolve technical blockers, and maintain technical documentation and best practices.
• Work as a senior/technical lead on advanced AI training and evaluation tasks for Gramian Consultancy’s engineering talent solutions.

• PhD, postdoctoral experience, or equivalent advanced technical expertise in Mechanical Engineering, Aerospace Engineering, or a closely related discipline.
• Strong programming skills in Python, C/C++, Fortran, Julia, or MATLAB/Octave.
• Proficiency in Linux and command-line environments.
• Hands-on expertise in at least one major area, such as FEA, CFD, dynamics, flight simulation, thermal modeling, astrodynamics, guidance, navigation and control (GNC), or propulsion modeling.
• Strong understanding of engineering simulation, numerical methods, computational modeling, and technical validation.
• Experience reviewing complex technical work, engineering simulations, computational models, or research outputs.
• Ability to assess engineering 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.
• Minimum capacity of 40 hours per week.
• Strong written English.