Remote Pod Lead - Civil and structural Engineering

Turing, a rapidly growing AI company, is advancing the development and deployment of cutting-edge AI systems. The company collaborates with leading AI labs to push the boundaries of model capabilities in areas like reasoning, coding, and multilingual STEM knowledge. These advancements are then applied to create real-world AI solutions addressing critical business challenges.

We are looking for an experienced Civil or Structural Engineering expert to lead a team of trainers focused on developing realistic, terminal-based technical tasks for Terminal Bench Science. In this role, you will ensure the engineering accuracy, reproducibility, and reliability of all tasks produced by your team. You will also provide coaching and mentorship to maintain high-quality deliverables.

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 ways to bypass 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 blockers.
- Maintain quality standards, technical documentation, and best practices throughout engineering task development.

Required Qualifications:
- Ph.D., postdoctoral experience, or equivalent advanced technical experience in Civil Engineering, Structural Engineering, Geotechnical Engineering, or a closely related discipline.
- 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 to identify technical inaccuracies, 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 Additional Information:
- Experience with engineering simulation and analysis tools like OpenSees/OpenSeesPy, Code_Aster, CalculiX, FEniCS, Gmsh, PyNite, EPANET, SWMM, HEC-RAS, MODFLOW, SUMO, QGIS, or GDAL.
- Familiarity with commercial engineering software such as 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 experience 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 expected contract duration is four weeks, with an anticipated start date next week. Please note this is a contractor assignment without medical or paid leave benefits.