OpenFOAM CFD Engineer

Design/advise on simulation environments (cases, boundaries, solver configs) so that models receive meaningful, learnable training signals.

• Help author, review, and tune graders that evaluate model outputs; ensure graders measure meaningful physical correctness and learning signal quality.
• Review candidate-contributed tasks and graders; recommend fixes and calibrations for learnability and correctness.
• Occasionally implement or debug OpenFOAM cases and scripts (hands-on capability expected at least at a basic-to-moderate level).
• Work collaboratively with forward-deployed engineers to translate CFD pedagogy into software “curriculum” and grading approaches.
• Provide documentation or brief notes explaining why a given solution is correct/incorrect (so engineers can convert that into automated assessments)

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• CFD SME (framework - OpenFOAM)

• SME in application to solve ( they are building environments virtual worlds that models interact ) openFOAM to solve CFD problems, models are graded

• Deep, hands-on OpenFOAM experience, including independently building, configuring, running, debugging, and analyzing cases-not primarily using GUI wrappers.

• Ideally 1-2 minimum (less about experience more about capabilities)

• Strong CFD and numerical-methods fundamentals, including turbulence modeling with hands-on RANS experience; spatial and temporal discretization schemes; solver stability, residuals, and convergence assessment; initial and boundary-condition selection; mesh dependence; numerical error; and physical interpretation.

• Practical meshing expertise, including blockMesh, snappyHexMesh, or equivalent meshing workflows. (–> frameworks to create meshes: create 3d (nice to have)

• Experience performing solver verification and validation against analytical, experimental, benchmark, or other trusted reference data.

• Strong Linux command-line skills and experience creating reproducible simulation workflows. —> MUST HAVE

• Basic Git and pull-request workflow experience.

• Solid Python ability for scripting, automation, and writing deterministic evaluation/scoring logic.

• Ability to reason rigorously about what makes an engineering solution correct, including appropriate tolerances, acceptable solution variants, and disqualifying errors.