Mechanical and Aerospace Engineering Task Lead – AI Project

Gramian Consulting

. Lead and mentor a team of 5–10 technical trainers, ensuring consistent task quality, productivity, and timely delivery.

Posted 10/16/2026contractRemote • Pakistan, Indonesia, Kenya, Turkey, Nigeria, VietnamSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced technical expertise in Mechanical and Aerospace Engineering, with a strong focus on engineering simulation, numerical methods, and technical validation. Proven ability to lead and mentor technical teams while ensuring high-quality outputs and effective communication.

Highest-signal resume keywords

PhD In Mechanical EngineeringProgramming Skills In Python, C/C++, Fortran, Julia, MATLAB/OctaveExpertise In Finite-Element Analysis (FEA)Experience In Computational Fluid Dynamics (CFD)Strong Written Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Finite-Element Analysis (FEA)Computational Fluid Dynamics (CFD)ThermodynamicsHeat TransferDynamicsRoboticsFlight SimulationPropulsion ModelingNumerical MethodsTechnical Validation

Soft Skills

Analytical JudgmentMentoringTechnical FeedbackProblem-SolvingTeam Leadership

Tools & Technologies

LinuxCommand-Line EnvironmentsSimulation ToolsAutomated GradersComputational Environments

Industry Keywords

Mechanical EngineeringAerospace EngineeringEngineering SimulationComputational ModelingTechnical Documentation

Tech Stack

Tools & technologies

LinuxPythonC++

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.