Remote Pod Lead - Mechanical & Aerospace Engineering

About the role

Turing, an AI company, is hiring an experienced Mechanical or Aerospace Engineering expert to lead a pod of about 5-10 technical trainers who develop realistic, terminal-based engineering tasks for a frontier AI training and evaluation initiative. The role reviews tasks for technical accuracy, reproducibility and evaluation quality, mentors trainers and maintains quality standards.

Key responsibilities

• Lead and mentor a pod of trainers, ensuring consistent quality, productivity and timely delivery.
• Review tasks end to end, including problem statements, geometry and mesh files, simulation inputs, material properties, reference solutions and automated tests.
• Validate tasks covering FEA, CFD, thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion and orbital mechanics.
• Check engineering correctness across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames and numerical stability.
• Verify computational environments, simulation tools, solvers and dependencies for reproducible results.
• Review automated graders to ensure they assess meaningful outputs such as stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters and safety margins.
• Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances and ways to bypass engineering calculations, then give clear, actionable feedback and track revisions.
• Onboard trainers, allocate work, monitor quality and throughput, escalate blockers and maintain technical documentation and best practices.

Required profile

• Ph.D., postdoctoral experience or equivalent advanced technical experience in Mechanical, Aerospace or a closely related discipline.
• Strong programming skills in Python, C/C++, Fortran, Julia or MATLAB/Octave, with proficiency in Linux environments.
• Hands-on expertise in at least one major area: FEA, CFD, dynamics, flight simulation, thermal modeling, astrodynamics, GNC or propulsion modeling.
• Experience reviewing complex technical work, engineering simulations, computational models or research outputs.
• Ability to evaluate engineering assumptions, numerical accuracy, solver convergence and result reliability.
• Experience mentoring, reviewing or leading small technical teams.
• Nice to have: experience with AI training, technical quality control, benchmark development or evaluation programs, and industry experience in automotive, energy, manufacturing, robotics, aircraft, launch vehicles, satellites or UAVs.

Required skills

• Programming: Python, C/C++, Fortran, Julia, MATLAB/Octave, Linux
• Nice to have: OpenFOAM, SU2, CalculiX, Code_Aster, FEniCS, Elmer, Gmsh, FreeCAD, CadQuery, MuJoCo, ROS, XFOIL, AVL, OpenVSP, JSBSim, OpenMDAO, pyCycle, poliastro, Orekit, GMAT, SPICE, ANSYS, Abaqus, COMSOL, NASTRAN, Docker, Git, CI/CD pipelines, automated testing, AI coding agents and LLM-generated engineering solutions

Contractor assignment with no medical or paid leave, at least 4 hours per day and 40 hours per week with 4 hours of overlap with PST time, starting next week.