Freelance Mechanical CFD Engineer - AI Trainer

Accountabilities: CFD simulation and analysis: Set up and run computational fluid dynamics simulations using CAD geometries and appropriate simulation methodologies. Simulation configuration: Prepare simulation models, define suitable boundary conditions, and perform meshing using established CFD workflows. Reference solution development: Build accurate, verified reference solutions that can be used to evaluate AI agents on expert-level fluid simulation tasks. AI output evaluation: Review and assess AI-generated engineering solutions for technical correctness, numerical reliability, and consistency with expected simulation outcomes. Verification and validation: Conduct mesh-independence studies and validate simulation results against experimental data, established benchmarks, or other reliable references. Automated testing: Develop Python scripts and checks to evaluate AI-generated results, identify errors, and verify compliance with engineering expectations. Technical documentation: Clearly document simulation methods, assumptions, validation approaches, and expected results to support reproducible and reliable evaluations. Engineering problem-solving: Apply advanced CFD knowledge to investigate complex fluid mechanics problems and identify potential issues in simulation workflows. Collaborative project delivery: Contribute technical expertise to AI training and evaluation projects, maintaining high standards of accuracy and consistency throughout assigned tasks. Requirements A degree in Mechanical Engineering, Aerospace Engineering, or a related discipline, such as Energy Engineering or Oil and Gas Engineering. A PhD is preferred but not required. Several years of hands-on CFD experience in an industrial or research environment. Practical experience with CFD tools such as OpenFOAM, ANSYS Fluent, ANSYS CFX, or STAR-CCM+, including mesh generation and simulation setup. Strong understanding of fluid mechanics, numerical simulation methods, and CFD modeling principles. Experience with verification and validation practices, including mesh-independence studies and validation against experimental data or established benchmarks. Proficiency in Python for scripting, automating checks, and evaluating simulation outputs. Familiarity with GitHub and version control workflows. English proficiency at B2 level or above, with the ability to understand technical documentation and communicate engineering findings clearly. Strong analytical thinking, attention to detail, and the ability to identify inconsistencies in complex technical results. Ability to work independently, manage assigned tasks, and deliver accurate, well-documented work in a remote freelance environment. Nice to have: Professional or research experience in aerospace, automotive, offshore engineering, or turbomachinery. Experience with multiphase flows or particle-laden flow simulations. A background in advanced engineering research, numerical modeling, or simulation-based design. Interest in AI model training, technical evaluation, and the application of engineering expertise to AI development. Benefits Fully remote work: Work from anywhere in India with a laptop and a reliable internet connection. Flexible schedule: Organize your working hours around your availability and project requirements. Part-time freelance engagement: Estimated workload of approximately 10–20 hours per week during active project phases; actual workload is not guaranteed and depends on project activity. Project-based compensation: Earn up to the equivalent of $9 per hour, depending on your expertise and pace of contribution. Compensation varies according to project scope, complexity, and required skills. Performance-based bonuses: Access bonus programs that reward high-quality work and consistent delivery. AI and engineering exposure: Apply your CFD expertise to the training and evaluation of advanced AI agents working on complex engineering tasks. Technical development: Strengthen your experience in simulation verification, automated testing, Python-based evaluation, and AI-assisted engineering workflows. Independent working environment: Contribute your specialist knowledge while managing your work remotely and independently. Global technology projects: Participate in technical initiatives that combine engineering expertise with the development of AI-driven solutions.