Computational Fluid Dynamics AI Evaluation Engineer

You will review and solve advanced computational fluid dynamics problems, then assess whether AI-generated technical answers are correct, accurate, and technically sound. Your feedback will help improve how AI systems interpret, solve, and explain engineering simulations.

The work includes practical simulation judgment, theoretical fluid-dynamics questions, troubleshooting, validation, and clear written and verbal explanations.

• Evaluate CFD problems involving mesh generation, turbulence models, multiphase flow, heat transfer, and solver configuration.
• Review AI-generated engineering responses for correctness, technical accuracy, and engineering integrity.
• Use mesh-independence studies, turbulence-model selection, boundary-condition checks, and convergence analysis to troubleshoot problems.
• Validate fluid-flow, heat-transfer, and multiphysics results against experimental or analytical data.
• Document feedback and explain technical findings clearly to support AI learning and performance.

This is a remote, part-time contractor opportunity for an individual technical contributor. Compensation is $50 to $150 per hour equivalent, paid per task that meets the project specifications.

• Pay: $50 to $150 per hour equivalent, paid per task that meets the project specifications.
• Location: Open to candidates in the United Arab Emirates, Argentina, Austria, Bangladesh, Belgium, Bahrain, Brazil, Canada, Switzerland, Chile, Colombia, Germany, Denmark, Algeria, Egypt, Spain, France, the United Kingdom, Ghana, Greece, Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, the Netherlands, Oman, Peru, the Philippines, Pakistan, Palestine, Portugal, Qatar, Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, the United States, Uzbekistan, Vietnam, and South Africa.
• Language: Excellent written and verbal English proficiency.
• 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: Strong understanding of Navier-Stokes equations, RANS, LES, DES, meshing strategies, boundary conditions, and verification and validation.
• Tools and practices: Experience with CFD tools and familiarity with ASME V&V 20, AIAA CFD verification and validation, ITTC procedures, or comparable practices are helpful.
• Helpful background: Experience with ANSYS Fluent, STAR-CCM+, OpenFOAM, COMSOL, or Converge, plus 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 work uses human review and expertise to improve systems that generate answers, solve problems, and interpret information. People with specialized engineering knowledge are needed to judge technical accuracy and explain where an AI response succeeds or fails.