Computational Structural and Mechanical Engineer, AI Benchmark

Design graduate-level computational engineering challenges that evaluate advanced AI systems on real scientific workflows, including simulation execution, result interpretation, experiment design, and extracting hidden information from data. This remote hourly role centers on creating original problems, testing them with advanced AI models, and refining them to achieve the intended level of difficulty.

You will build problems grounded in practical research workflows rather than routine data-labeling tasks. Assignments may require an AI system to calculate an exact answer from a fully specified setup or to strategically plan queries and experiments, interpret partial findings, choose useful measurements, and efficiently narrow possible answers.

• Create challenging computational problems requiring proficient use of specialized scientific software.
• Develop original, graduate-level tasks based on real scientific and engineering workflows.
• Test problems against advanced AI models and iteratively revise them to meet target difficulty.
• Design tasks that require sound reasoning, not simply large amounts of computation or surface-level pattern matching.
• Write problem setups, oracle functions, and solution validators in Python.

• Graduate-level training in a relevant STEM field, including an MS, PhD, or equivalent research experience. Advanced degrees are preferred.
• Demonstrated hands-on proficiency with at least one relevant open-source scientific software library through research publications, open-source contributions, or professional work.
• Experience applying these tools to real research problems, including an understanding of limitations, edge cases, and genuinely challenging problem design.
• Strong Python programming skills.
• Ability to work independently and improve problem designs in response to feedback.
• Comfort working in a Linux terminal environment and remote compute sandboxes.
• Experience with tools such as FEniCSx/DOLFINx, scikit-fem, OpenFOAM, deal.II, MFEM, MOOSE, CalculiX, Elmer FEM, Code_Aster, SfePy, FiPy, Devito, Cantera, CoolProp, Pyomo, or SimPy is especially relevant.
• Relevant expertise may include finite-element analysis, computational mechanics, structural analysis, elasticity, CFD, multiphysics simulation, heat and mass transfer, thermodynamics, combustion, fluid mechanics, HVAC and thermal systems, manufacturing simulation, optimization, or thermophysical-property calculations.
• Useful experience includes beam, plate, and shell analysis; linear or nonlinear elasticity; finite-element and variational formulations; mesh refinement and convergence studies; continuum and solid mechanics; coupled multiphysics; thermal-fluid simulation; structural or system optimization; reliability analysis; and related numerical workflows.
• Knowledge of Euler-Bernoulli and Timoshenko beam theory, continuum mechanics, finite-element methods, Galerkin and variational methods, finite-volume methods, PDE discretization, constitutive modeling, thermodynamics, numerical linear algebra, and nonlinear solution methods is valued.
• Experience with other open-source structural or mechanical engineering software, including scientific codes and solver frameworks written in Python, C, C++, or Fortran, will be considered.

• Experience across multiple relevant domains or tools.
• Familiarity with benchmark or evaluation design.
• Experience teaching scientific subjects or creating exams and problem sets.
• Experience with computational reproducibility and containerized environments.

• Remote, hourly engagement.
• Availability of at least 15 to 20 hours per week.

$70 to $85 per hour.