Mechanical & Aerospace Engineering Task Lead (AI Project)
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 15h ago
The date the source published, not the day we noticed it (2026-10-15). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Pakistan, Indonesia, Kenya, Turkey, Nigeria, Vietnam
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $7,250/mo
Middle 50% of 9 listings that do state pay — Engineering · all levels · Turkey · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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Workable employer's own board first seen 2h ago · last seen just now
The listing
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Role
We are seeking an experienced Mechanical or Aerospace Engineering Expertto lead a team of technical trainers developing realistic, terminal-based engineering tasks for advanced AI training and evaluation. You will oversee a pod of approximately 5–10 trainers, review tasks for engineering accuracy and reproducibility, and ensure automated graders reliably assess technical outcomes. This role combines advanced engineering expertise, computational modeling, technical quality assurance, and team leadership to help evaluate and improve next-generation AI systems.
CAPACITY: Minimum 40 hours per week
SENIORITY: Senior / Technical Lead
LANGUAGE: Strong written English
Key Responsibilities
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.
Requirements
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.