Responsibilities

• 
  Virtual Sign-off & Validation: Lead the
  structural durability and fatigue sign-off for critical systems like body
  structures, frames, and electric vehicle (EV) battery trays before
  physical prototype builds.
• 
  Advanced Simulation Leadership: Oversee complex,
  full-vehicle explicit and implicit dynamic simulations (e.g., ground
  strikes, curb strikes, and cyclic loading) to assess structural
  resilience.
• 
  Model Correlation: Drive the alignment between
  virtual simulation models and physical test results from proving grounds
  or lab rigs to ensure predictive accuracy.
• 
  Root Cause Analysis: Use physics-based principles
  and simulation data to diagnose and resolve durability failures from early
  development through production.
• 
  Technical Mentorship: Act as a "subject
  matter expert" (SME), coaching junior engineers and developing new
  CAE methodologies.
• 
  Cross-functional Collaboration: Engage with
  design, manufacturing, and "Road Load" teams to develop design
  load targets and ensure lessons learned are integrated into future vehicle
  architectures.

Requirements

Key Technical Skills & Qualifications

• 
  Simulation Software Expertise: Mastery of CAE
  tools such as Abaqus, Nastran and fatigue solvers
  like nCode DesignLife or FEMFAT.
• 
  Material Science Knowledge: Deep understanding of
  fatigue life prediction, plasticity, ductile failure, and metal joining
  methods (e.g., welding in HSLA steels or cast materials).
• 
  Data Processing: Proficiency in pre-processors
  ANSA or HyperMesh and Post-processors HyperView or
  Meta/Post. Familiarity in scripting languages
  like Python or MATLAB for automation would be a plus.
• 
  Communication & Presentation: Excellent
  communication skills, both written and verbal, with a proven ability to
  translate complex data into clear technical and executive presentations
  for leadership decision-making
• 
  Experience: Requires 10+ years of experience in
  structural components and CAE correlation for specialist roles.

Special Considerations:

• 
  AI & Machine Learning
• 
  Proficiency in applying
  Reduced Order
  Modeling (ROM)
  and
  Neural Networks
  to
  accelerate traditional CAE simulations.