CFD Engineer (Computational Fluid Dynamics AI)

You will evaluate and solve advanced computational fluid dynamics problems, then review AI-generated technical answers for accuracy and sound engineering judgment. The work covers simulation setup, fluid flow, heat transfer, multiphysics, and clear written and verbal feedback.

Tasks use text-based evaluation and question answering. You will explain errors, assess model reasoning, and provide feedback that helps improve AI performance.

• Evaluate CFD problems involving meshing, turbulence models, multiphase flow, heat transfer, and solver configuration.
• Review AI-generated engineering responses for correctness, technical accuracy, and engineering integrity.
• Troubleshoot simulations through mesh-independence studies, turbulence-model selection, boundary conditions, and convergence analysis.
• Compare fluid-flow, heat-transfer, and multiphysics results with experimental or analytical data.
• Document feedback and explain technical conclusions clearly in writing and conversation.

This is a remote, part-time contractor opportunity for an individual technical contributor. No, Australia is not listed, and Vietnam.

• Pay: $50 to $150 per hour equivalent, paid per task that meets project specifications.
• Work arrangement: Remote contractor, part time, with output-based compensation.
• Location: Open to candidates in AE, AR, AT, BD, BE, BH, BR, CA, CH, CL, CO, DE, DK, DZ, EG, ES, FR, GB, GH, GR, ID, IN, IT, JO, JP, KE, KG, KW, KZ, LB, LK, MA, MX, MY, NG, NL, OM, PE, PH, PK, PS, PT, QA, SA, SG, TH, TN, TW, US, UZ, VN, and ZA.
• Language: Professional fluency in English.
• Education: A bachelor's degree or higher in mechanical engineering, aerospace engineering, chemical engineering, fluid dynamics, thermofluids, or a related field is preferred, or equivalent practical experience.
• Experience: At least three years of hands-on CFD simulation and validation experience is preferred.
• Technical knowledge: Navier-Stokes equations, RANS, LES, DES, meshing strategies, boundary conditions, and verification and validation.
• Helpful tools and background: ANSYS Fluent, STAR-CCM+, OpenFOAM, COMSOL, Converge, technical problem authoring, committee service, competition leadership, or recognized CFD contributions.

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

AI training is the human work behind systems that learn to answer questions and solve problems. People with specialized engineering knowledge review model outputs, identify mistakes, and provide examples that help AI systems become more accurate and useful.