Mechanical & Aerospace Engineering Task Lead
Posted 15 Oct 2026
Advertised as “Mechanical & Aerospace Engineering Task Lead (AI Project)”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- People management
- Employment
- Remote
- Contract
- Contract
No salary listed for this role.
Field of studyAerospace Engineering, Mechanical Engineering (or related)
Study levelDoctorate or higher
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
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Lead and mentor a team of 5–10 technical trainers, ensuring consistent task quality, productivity, and timely delivery.
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Review engineering tasks end to end, including problem statements, geometry and mesh files, simulation inputs, material properties, reference solutions, and automated tests.
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Validate tasks involving finite-element analysis (FEA), computational fluid dynamics (CFD), thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion, and orbital mechanics.
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Ensure tasks reflect realistic mechanical and aerospace engineering workflows and require meaningful, multi-step technical reasoning.
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Verify engineering correctness across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames, and numerical stability.
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Validate computational environments, simulation tools, solvers, and dependencies to ensure reproducible results.
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Review automated graders to ensure they assess meaningful engineering outputs, including stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters, and safety margins.
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Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass genuine engineering calculations or simulations.