Durability CAE Engineer

InDepth Engineering Solutions, LLC | Full time Durability CAE Engineer Novi, United States | Posted on 02/05/2026 Virtual Sign-off & Validation: Lead thestructural durability and fatigue sign-off for critical systems like bodystructures, frames, and electric vehicle (EV) battery trays beforephysical prototype builds. Advanced Simulation Leadership: Oversee complex,full-vehicle explicit and implicit dynamic simulations (e.g., groundstrikes, curb strikes, and cyclic loading) to assess structuralresilience. Model Correlation: Drive the alignment betweenvirtual simulation models and physical test results from proving groundsor lab rigs to ensure predictive accuracy. Root Cause Analysis: Use physics-based principlesand simulation data to diagnose and resolve durability failures from earlydevelopment through production. Technical Mentorship: Act as a "subjectmatter expert" (SME), coaching junior engineers and developing newCAE methodologies. Cross-functional Collaboration: Engage withdesign, manufacturing, and "Road Load" teams to develop designload targets and ensure lessons learned are integrated into future vehiclearchitectures. Requirements Key Technical Skills & Qualifications Simulation Software Expertise: Mastery of CAEtools such asAbaqus,Nastran and fatigue solverslikenCode DesignLifeor FEMFAT. Material Science Knowledge: Deep understanding offatigue life prediction, plasticity, ductile failure, and metal joiningmethods (e.g., welding in HSLA steels or cast materials). Data Processing: Proficiency in pre-processorsANSAorHyperMeshand Post-processors HyperView orMeta/Post. Familiarity in scripting languageslikePythonorMATLABfor automation would be a plus. Communication & Presentation: Excellentcommunication skills, both written and verbal, with a proven ability totranslate complex data into clear technical and executive presentationsfor leadership decision-making Experience: Requires 10+ years of experience instructural components and CAE correlation for specialist roles. Special Considerations Proficiency in applying Reduced OrderModeling (ROM) and Neural Networks toaccelerate traditional CAE simulations. #J-18808-Ljbffr