Remote Pod Lead - Civil and structural Engineering

Turing, a rapidly growing AI company, is advancing the development and deployment of powerful AI systems by collaborating with leading AI labs and creating real-world solutions that address critical business challenges. We are currently looking for an experienced Civil or Structural Engineering expert to lead a team of trainers in developing realistic, terminal-based technical tasks for Terminal Bench Science. This role involves ensuring the engineering accuracy, reproducibility, and quality of all tasks produced, while coaching trainers to maintain high standards.

Key Responsibilities:
- Review engineering tasks comprehensively, including problem statements, structural and geotechnical models, load cases, simulation data, computational environments, reference solutions, and automated tests.
- Validate tasks related to structural analysis, finite-element methods (FEA), earthquake and wind engineering, structural dynamics, geotechnical modeling, hydraulics, hydrology, transportation, and infrastructure systems.
- Ensure tasks require authentic multi-step engineering reasoning and reflect realistic civil and structural engineering workflows.
- Verify engineering accuracy concerning units, equilibrium, boundary conditions, load combinations, design codes, numerical stability, convergence, and safety factors.
- Validate computational models, solvers, dependencies, and simulation results for reproducibility and technical correctness.
- Review automated graders to confirm they assess meaningful engineering outputs such as forces, deflections, drifts, settlements, factors of safety, flow rates, and structural performance.
- Identify technical errors, unrealistic assumptions, incorrect tolerances, and potential shortcuts that bypass proper engineering analysis.
- Provide clear, actionable feedback to task developers and track revisions through to completion.
- Mentor and support technical trainers, allocate work, monitor quality and productivity, and resolve technical challenges.
- Maintain quality standards, technical documentation, and best practices throughout engineering task development.

Required Qualifications:
- Ph.D., postdoctoral experience, or equivalent advanced technical expertise in Civil Engineering, Structural Engineering, Geotechnical Engineering, or a closely related field.
- Strong programming skills in Python, C/C++, Julia, Fortran, or MATLAB/Octave, with proficiency in Linux environments.
- Hands-on expertise in at least one core area such as structural analysis, FEA, earthquake engineering, geotechnical modeling, or hydraulic/hydrological modeling.
- Deep understanding of engineering principles, numerical methods, simulation workflows, and model validation.
- Working knowledge of engineering design standards like ASCE 7, ACI, AISC, Eurocodes, or IS codes.
- Experience reviewing complex technical work, engineering simulations, research outputs, or computational models.
- Strong analytical judgment with the ability to detect technical inaccuracies, edge cases, and flawed engineering assumptions.
- Experience mentoring, reviewing, 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 analysis tools such as OpenSees/OpenSeesPy, Code_Aster, CalculiX, FEniCS, Gmsh, PyNite, EPANET, SWMM, HEC-RAS, MODFLOW, SUMO, QGIS, or GDAL.
- Familiarity with commercial engineering software like SAP2000, ETABS, Abaqus, PLAXIS, or STAAD.Pro.
- Knowledge of nonlinear time-history analysis, performance-based design, reliability analysis, or structural health monitoring.
- 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.
- Professional engineering licensure such as PE, SE, CEng, or equivalent.
- Industry experience in buildings, bridges, transportation networks, water systems, or major infrastructure projects.
- Prior involvement in AI training, technical quality control, benchmark development, or evaluation programs.

Offer Details:
This is a contractor assignment requiring a minimum commitment of 40 hours per week, with at least 4 hours daily overlapping with Pacific Standard Time (PST). The contract duration is four weeks, with an expected start date in the near term. Please note that this role does not include medical benefits or paid leave.