Mechanical & Aerospace Engineering Task Lead (AI Project)

Gramian Consultancy is seeking an experienced Mechanical or Aerospace Engineering expert to lead a team of technical trainers focused on developing realistic, terminal-based engineering tasks for advanced AI training and evaluation. This senior technical lead role involves managing a pod of 5 to 10 trainers, ensuring the engineering accuracy and reproducibility of tasks, and overseeing the reliability of automated graders that assess technical outcomes. The position requires a blend of advanced engineering knowledge, computational modeling skills, technical quality assurance, and leadership to support the evaluation and enhancement of next-generation AI systems. The role demands a minimum commitment of 40 hours per week and strong written English communication skills.

Key Responsibilities

- Lead and mentor a team of 5 to 10 technical trainers, maintaining consistent task quality, productivity, and timely delivery.
- Conduct thorough reviews of engineering tasks, 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 accurately represent realistic mechanical and aerospace engineering workflows and require meaningful, multi-step technical reasoning.
- Verify engineering correctness across multiple aspects such as units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames, and numerical stability.
- Validate computational environments, simulation tools, solvers, and dependencies to guarantee reproducible results.
- Review automated graders to confirm 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 potential shortcuts that bypass genuine engineering calculations or simulations.
- Provide clear, actionable technical feedback, track revisions, and ensure all quality issues are resolved before task approval.
- Onboard new trainers, allocate work efficiently, monitor quality and throughput, resolve technical blockers, and maintain comprehensive technical documentation and best practices.

Required Qualifications

- 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 with 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.
- Deep 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 critically assess engineering assumptions, numerical accuracy, solver convergence, and computational reliability.
- Strong analytical judgment with the ability to detect technical errors, edge cases, and flawed engineering assumptions.
- Experience mentoring, reviewing, or leading small technical teams.
- Excellent written communication skills for delivering precise technical feedback and maintaining documentation.

This role offers the opportunity to work at the intersection of advanced engineering and AI development, leading a specialized team to create high-quality, technically rigorous training tasks that push the boundaries of AI capabilities.