Mechanical Engineering Expert - Remote

YO AI Labs is seeking a Mechanical Engineering Expert to support an AI training project focused on engineering design, physical modeling, simulation, technical problem-solving, and Python. The role involves solving, validating, and reviewing structural, thermal, mechanical, and multiphysics engineering tasks in a flexible contractor capacity.

Responsibilities:

• Solve and validate mechanical engineering problems involving design, analysis, simulation, and testing
• Translate engineering requirements into analytical and computational models
• Create and modify geometry, meshes, materials, loads, constraints, and solver inputs
• Perform structural, thermal, dynamic, fatigue, buckling, and vibration analyses
• Use Python to automate simulations, parameter sweeps, optimization, and post-processing
• Analyze stress, strain, displacement, temperature, deformation, frequency response, and safety factors
• Diagnose geometry, mesh, convergence, boundary-condition, and modeling issues
• Compare simulation results with calculations, experiments, and expected physical behavior
• Review AI-generated engineering solutions and develop reproducible reference solutions

Requirements:

• • Mechanical Engineering & Applied Mechanics
• • Engineering Design & Analysis
• • Structural & Thermal Analysis
• • Computational Modeling & Simulation
• • Python
• • CAD, Meshing & Simulation
• • Numerical Validation & Troubleshooting
• • Technical Problem-Solving
• Experience with CalculiX, Gmsh, Elmer, FEniCSx, CadQuery, OpenSCAD, OpenFOAM , or equivalent CLI/programmatic engineering tools
• • MS/PhD in Mechanical Engineering or related discipline, or BS in Mechanical Engineering with 1–2+ years of relevant professional experience
• • Strong mechanical-engineering fundamentals and simulation experience
• • Practical Python and programmatic engineering-tool experience
• • Ability to select and justify materials, loads, boundary conditions, assumptions, and model fidelity
• • Ability to validate results and clearly explain engineering decisions and trade-offs
• Python tools such as NumPy, SciPy, SymPy, pandas, Matplotlib, and Jupyter are beneficial