Mechanical & Aerospace Engineering

Role Overview

• Seeking an experienced Mechanical or Aerospace Engineering expert to lead a team of technical trainers developing realistic, terminal-based engineering tasks for a frontier AI training and evaluation initiative.
• Oversee a pod of approximately 5–10 trainers, review engineering tasks for technical accuracy, reproducibility, and evaluation quality, and ensure tasks reflect authentic mechanical and aerospace engineering workflows.
• Mentor trainers, maintain quality standards, and drive consistent task delivery.

Key Responsibilities

• Lead and mentor a pod of technical trainers, ensuring consistent quality, productivity, and timely delivery of engineering tasks.
• 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 evaluate meaningful engineering outputs such as stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters, and safety margins.
• Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass engineering calculations or simulations.
• Provide clear, actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval.
• Onboard trainers, allocate work, monitor quality and throughput, escalate blockers, and maintain technical documentation and best practices.

Requirements & Tech Stack

• Ph.D., postdoctoral experience, or equivalent advanced technical experience in Mechanical Engineering, Aerospace Engineering, 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, 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 evaluate engineering assumptions, numerical accuracy, solver convergence, and the reliability of computational results.
• Strong analytical judgment with 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 providing precise technical feedback and documenting quality standards.

Nice to Have

• Experience with engineering simulation and computational tools such as OpenFOAM, SU2, CalculiX, Code_Aster, FEniCS, Elmer, Gmsh, FreeCAD, CadQuery, MuJoCo, ROS, XFOIL, AVL, OpenVSP, JSBSim, OpenMDAO, pyCycle, poliastro, Orekit, GMAT, or SPICE.
• Familiarity with commercial engineering software such as ANSYS, Abaqus, COMSOL, or NASTRAN, including reproducing workflows using open-source tools.
• Experience with state estimation, trajectory optimization, topology optimization, aeroelastic analysis, or multidisciplinary design optimization.
• Familiarity with Docker, Git, CI/CD pipelines, and automated testing.
• Experience developing or evaluating AI coding agents, terminal-based agents, or LLM-generated engineering solutions.
• Industry or agency experience in automotive, energy, manufacturing, robotics, aircraft, launch vehicles, satellites, or UAVs.
• Prior experience in AI training, technical quality control, benchmark development, or evaluation programs.

Offer Details

• Commitments Required: At least 4 hours per day and minimum 40 hours per week with overlap of 4 hours with PST.
• Employment type: Contractor assignment (no medical/paid leave)
• Duration of contract: 4 weeks