Remote Pod Lead - Civil and structural Engineering

Turing, a rapidly growing AI company, is advancing the development and deployment of cutting-edge AI systems by collaborating with leading AI labs and building real-world solutions that address critical business challenges. We are currently seeking an experienced Civil or Structural Engineering expert to lead a team of trainers in creating realistic, terminal-based technical tasks for Terminal Bench Science. This role involves ensuring the technical accuracy, reproducibility, and quality of engineering tasks while mentoring 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 bypasses of engineering analysis.
- Provide clear, actionable feedback to task developers and track revisions through to completion.
- Mentor and support technical trainers by allocating work, monitoring quality and productivity, and resolving technical challenges.
- Maintain quality standards, technical documentation, and best practices across 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 major 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 such as 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 on 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 as early as next week. Please note that this is a contractor role without medical benefits or paid leave.