Mechanical & Aerospace Engineering Task Lead (AI Projects)

New

Gramian ConsultancyEngineering AI

Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, VietnamContractLead

Salary not disclosed

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Job Details

Have a PhD degree; the posting states that a PhD is mandatory.
Have postdoctoral experience or equivalent advanced technical expertise in Mechanical Engineering, Aerospace Engineering, or a closely related discipline.
Have strong programming skills in Python, C/C++, Fortran, Julia, or MATLAB/Octave.
Be proficient in Linux and command-line environments.
Have hands-on expertise in at least one major area, such as FEA, CFD, dynamics, flight simulation, thermal modeling, astrodynamics, GNC, or propulsion modeling.
Understand engineering simulation, numerical methods, computational modeling, and technical validation.
Have experience reviewing complex technical work, engineering simulations, computational models, or research outputs.
Be able to assess engineering assumptions, numerical accuracy, solver convergence, and computational reliability.
Have strong analytical judgment and the ability to identify technical errors, edge cases, and flawed engineering assumptions.
Have experience mentoring, reviewing, or leading small technical teams.
Have excellent written communication skills for precise technical feedback and documentation.

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 FEA, CFD, thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion, and orbital mechanics.
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.
Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and ways 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.

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