Remote Pod Lead - Mechanical & Aerospace Engineering

Turing, a rapidly growing AI company, is at the forefront of advancing and deploying powerful AI systems. The company collaborates with leading AI labs to push the boundaries of model capabilities in areas such as reasoning, coding, multilinguality, STEM, and more. These advancements are then applied to develop real-world AI solutions that address critical business challenges.

Key Responsibilities:
Lead and mentor a team of 5–10 technical trainers focused on creating realistic, terminal-based engineering tasks for AI training and evaluation. Oversee the review of engineering tasks to ensure technical accuracy, reproducibility, and high evaluation standards. 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 authentic mechanical and aerospace engineering workflows requiring multi-step technical reasoning. Verify engineering correctness by checking 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 accurately assess engineering outputs such as stresses, deflections, aerodynamic coefficients, thermal performance, orbital parameters, and safety margins. Identify technical inaccuracies, unrealistic assumptions, and potential shortcuts in engineering calculations or simulations. Provide clear, actionable feedback, track revisions, and ensure all quality issues are resolved before task approval. Manage onboarding, work allocation, quality monitoring, escalation of blockers, and maintenance of technical documentation and best practices.

Required Qualifications:
Ph.D., postdoctoral experience, or equivalent advanced expertise in Mechanical Engineering, Aerospace Engineering, or a closely related field. Strong programming skills in Python, C/C++, Fortran, Julia, or MATLAB/Octave, with proficiency in Linux environments. Hands-on experience in at least one core 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, simulations, computational models, or research outputs. Ability to critically evaluate engineering assumptions, numerical accuracy, solver convergence, and computational result reliability. Strong analytical judgment to detect technical errors, edge cases, and flawed assumptions. Proven experience mentoring or leading small technical teams. Excellent written communication skills for delivering precise technical feedback and documenting quality standards.

Preferred Qualifications and Benefits:
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 like ANSYS, Abaqus, COMSOL, or NASTRAN, including the ability to replicate workflows using open-source alternatives. Knowledge of state estimation, trajectory optimization, topology optimization, aeroelastic analysis, or multidisciplinary design optimization. Experience with Docker, Git, CI/CD pipelines, and automated testing. Background in developing or evaluating AI coding agents, terminal-based agents, or LLM-generated engineering solutions. Industry experience in automotive, energy, manufacturing, robotics, aircraft, launch vehicles, satellites, or UAVs is a plus. Prior involvement in AI training, technical quality control, benchmark development, or evaluation programs is advantageous.

Offer Details:
This is a contractor role requiring a commitment of at least 4 hours daily and a minimum of 40 hours per week, with at least 4 hours overlapping with Pacific Standard Time (PST). The contract duration is approximately 4 weeks, with an expected start date as early as next week. Please note this is a contractor assignment without medical or paid leave benefits.