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Remote Pod Lead Civil and structural Engineering
Job Location:
Hourly Salary:
Posted:
30 October 2026 (2 days ago)
Posted:
Application Deadline:
27 January 2027
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
About Turing:
Turing is one of the worlds fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems.
Turing helps customers in two ways: Working with the worlds leading AI labs to advance frontier model capabilities in thinking reasoning coding agentic behavior multimodality multilinguality STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.
Role Overview:
We are seeking an experienced Civil or Structural Engineering expert to lead a pod of trainers building realistic terminal-based technical tasks for Terminal Bench Science. You will review every task your trainers produce for engineering correctness reproducibility and grader reliability and coach trainers to consistently deliver high-quality tasks.
Reporting Structure:
Reports to the Civil & Structural Engineering Team Lead. Leads a pod of approximately 510 trainers.
What youll do:
- Review engineering tasks end to end including problem statements structural and geotechnical models load cases simulation data computational environments reference solutions and automated tests.
- Validate tasks involving structural analysis finite-element methods (FEA) earthquake and wind engineering structural dynamics geotechnical modeling hydraulics hydrology transportation and infrastructure systems.
- Ensure tasks require genuine multi-step engineering reasoning and reflect realistic civil and structural engineering workflows.
- Verify engineering accuracy across 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 ensure they evaluate 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 opportunities to bypass engineering analysis.
- Provide clear actionable feedback to task developers and track revisions through completion.
- Mentor and support technical trainers allocate work monitor quality and productivity and resolve technical blockers.
- Maintain quality standards technical documentation and best practices across engineering task development.
What were looking for:
- Ph.D. postdoctoral experience or equivalent advanced technical experience in Civil Engineering Structural Engineering Geotechnical Engineering or a closely related discipline.
- Strong programming experience in Python C/C Julia Fortran or MATLAB/Octave with proficiency in Linux environments.
- Hands-on expertise in at least one major area: structural analysis FEA earthquake engineering geotechnical modeling or hydraulic/hydrological modeling.
- Strong 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 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.
Nice to have:
- Experience with engineering simulation and analysis tools such as OpenSees/OpenSeesPy CodeAster 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 .
- Experience with nonlinear time-history analysis performance-based design reliability analysis or structural health monitoring.
- Familiarity with Docker Git CI/CD pipelines and automated testing.
- Experience 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 working on 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:
- Commitments Required: At least 4 hours per day and minimum 40 hours per week with overlap of 4 hours with PST.
- Employment type : Contractor assignment (no medical/paid leave)
- Duration of contract : 4 week expected start date is next week
Required Experience:
IC
About Company
Build GenAI and other enterprise applications, train and enhance LLMs, or hire on-demand technical professionals with Turing.
