Remote Pod Lead - Mechanical & Aerospace Engineering

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

Key Responsibilities:
Lead and mentor a team of 5 to 10 technical trainers responsible for developing realistic, terminal-based engineering tasks for an AI training and evaluation initiative. 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 and require multi-step technical reasoning. Verify engineering correctness across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames, and numerical stability. Confirm that computational environments, simulation tools, solvers, and dependencies produce reproducible results. Review automated graders to ensure they assess 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 potential shortcuts in engineering calculations or simulations. Provide clear, actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval. Manage onboarding of trainers, allocate tasks, monitor quality and throughput, escalate blockers, and maintain 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 major 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, engineering simulations, computational models, or research outputs. Ability to critically evaluate engineering assumptions, numerical accuracy, solver convergence, and computational result reliability. Strong analytical judgment 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.

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 replicating workflows using open-source tools. 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 or agency experience in automotive, energy, manufacturing, robotics, aircraft, launch vehicles, satellites, or UAVs. Prior involvement in AI training, technical quality control, benchmark development, or evaluation programs.

Offer Details:
This is a contractor role requiring a minimum commitment of 40 hours per week, with at least 4 hours overlapping with Pacific Standard Time (PST). The contract duration is four weeks, with an expected start date in the near future. Please note that this is a contractor assignment without medical benefits or paid leave.