Computational Engineering Expert

**Pay:** $20-$60 per hour (USD). **Job Title:** Computational Engineering Expert **Job Type:** Contractor **Location:** Remote **Job Summary:** In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. **Key Responsibilities:** 1. Leverage your expertise in computational, simulation, or systems engineering to inform advanced AI benchmarking and evaluation processes. 2. Analyze and provide feedback on AI models’ performance in realistic engineering scenarios related to CFD, FEA, robotics, and more. 3. Review, assess, and enhance technical datasets, workflows, and simulation results for quality and accuracy. 4. Utilize domain-specific tools such as ANSYS, Abaqus, COMSOL, OpenFOAM, and MATLAB to validate engineering solutions. 5. Create detailed written assessments and communicate complex technical insights clearly with the team. 6. Collaborate with a diverse group of domain experts to identify gaps and opportunities for AI model improvement. 7. Contribute to the development of robust, real-world benchmarks for AI systems in computational engineering fields. **Required Skills and Qualifications:** 1. PhD or equivalent industry/research experience in a computational, simulation, or systems engineering discipline. 2. Proven expertise in areas such as CFD, FEA, computational mechanics, robotics, control systems, or signal processing. 3. Hands-on experience with simulation, analytical, or technical modeling tools (e.g., ANSYS, Abaqus, MATLAB, OpenFOAM). 4. Strong problem-solving and systems-thinking skills, with a commitment to technical excellence. 5. Exceptional written and verbal communication skills, enabling clear knowledge transfer and collaborative work. 6. Comfortable with scripting and scientific workflows in Python and/or MATLAB. 7. Ability to synthesize complex domain knowledge into actionable insights for interdisciplinary teams. **Preferred Qualifications:** 1. Experience applying AI/ML techniques within engineering domains or workflows. 2. Familiarity with HPC, optimization, or large-scale simulation environments. 3. Publication record, patents, or deep R&D involvement in computational engineering or simulation.