CAE Engineer

LHH; Detroit (MI); On-site; USD 85,000 - 120,000; Full time

Job summary

LHH is seeking a CAE Engineer in Detroit to perform FEA/CAE simulations for automotive products and materials, focusing on crashworthiness, structural performance, NVH, fatigue, and durability. You will develop FE models, analyze results, and propose design improvements while collaborating with Product Development, R&D, Manufacturing, and suppliers.

Ideal candidates have a Mechanical/Aerospace engineering background, strong FEA knowledge, and experience with LS-DYNA, Abaqus, or similar software.

Qualifications

• Bachelor's degree in Mechanical or Aerospace Engineering or related field.
• Strong understanding of FEA fundamentals and engineering problem solving.
• Experience interpreting FEA results and correlating with physical behavior.
• Experience with automotive CAE applications is a plus.

Responsibilities

• Perform FEA/CAE simulations for crashworthiness, structural performance, NVH, fatigue, and durability.
• Develop FE models including meshing, material definitions, connections, loads, and boundary conditions.
• Analyze results, identify limitations, and propose design improvements.
• Support new product development and customer programs with CAE analyses.
• Plan and support physical testing to validate CAE predictions and refine models.
• Document modeling approaches, results, and engineering recommendations.
• Collaborate with cross-functional teams and suppliers to improve CAE methods.

Skills

FEA fundamentals

Problem solving

Written and verbal communication

Independent working

Education

Bachelor's degree in Mechanical Engineering or Aerospace Engineering

Tools

LS-DYNA

OptiStruct

Nastran

Abaqus

HyperWorks/HyperMesh

LS-PrePost

Job description

As a CAE Engineer, you will use finite element analysis (FEA) and simulation tools to evaluate and optimize automotive products and material solutions. Your work will support crashworthiness, structural performance, NVH, fatigue, and durability applications while helping engineering teams make informed product-design decisions.

You will collaborate with Product Development, R&D, Manufacturing, Quality, Commercial teams, customers, and suppliers to develop simulation models, analyze product performance, correlate CAE predictions with physical testing, and continuously improve analytical methods and capabilities.

Key Responsibilities

• Perform FEA and CAE simulations to evaluate automotive products and material solutions for crashworthiness, structural performance, NVH, fatigue, durability, and related applications.
• Develop finite element models, including geometry idealization, meshing, material definitions, connections, contacts, loads, constraints, and boundary conditions.
• Analyze simulation results to identify performance limitations and failure modes and recommend design improvements related to performance, weight, cost, manufacturability, and robustness.
• Provide analytical support for new product development, customer programs, and emerging technical opportunities.
• Perform and support coupon, component, subsystem, and system-level analysis and correlation activities.
• Apply appropriate modeling techniques and material models for polymers, composites, adhesives, metals, and multi-material structures.
• Support material characterization and model validation in collaboration with CAE, R&D, and laboratory teams.
• Plan and support physical testing used to validate CAE predictions, investigate discrepancies between simulation and test results, and refine models as needed.
• Verify model setup and simulation results, including material definitions, boundary conditions, loading, connections, contacts, mesh quality, units, and modeling assumptions.
• Participate in technical and peer reviews to ensure accuracy, consistency, and quality of CAE work.
• Clearly document modeling approaches, assumptions, results, conclusions, and engineering recommendations.
• Communicate technical findings effectively to engineering, manufacturing, commercial, supplier, and customer stakeholders.
• Support customer programs and technical activities at customer locations when needed.
• Develop and implement improved CAE methods, automation, optimization, and data-analysis techniques to increase simulation efficiency, accuracy, and repeatability.
• Manage assigned analyses and project commitments while collaborating effectively within cross-functional and global engineering teams.

Required Qualifications

• Bachelor’s degree in Mechanical Engineering, Aerospace Engineering, or a related engineering discipline.
• Knowledge of finite element analysis fundamentals, structural mechanics, and engineering problem-solving principles.
• Experience with commercial FEA solvers such as LS-DYNA, OptiStruct, Nastran, Abaqus, or comparable software.
• Experience with CAE preprocessing and postprocessing tools such as Altair HyperWorks/HyperMesh, LS-PrePost, or equivalent.
• Ability to interpret FEA results, evaluate model validity, and relate analytical predictions to physical product behavior.
• Understanding of automotive crashworthiness, structural performance, NVH, fatigue, durability, or related CAE applications.
• Strong written and verbal technical communication skills.
• Ability to work independently while contributing effectively within cross-functional teams.

Preferred Qualifications

• 1–3 years of relevant automotive, CAE, or FEA experience. Candidates with strong academic, internship, or co-op CAE experience may also be considered.
• Master’s degree in Mechanical Engineering, Aerospace Engineering, or another relevant engineering discipline.
• Experience with nonlinear FEA and/or explicit dynamics, particularly LS-DYNA for crash applications.
• Experience modeling polymers, fiber‑reinforced composites, adhesives, metals, or multi‑material structures.
• Experience correlating simulation results with coupon, component, subsystem, or system‑level physical testing.
• Familiarity with manufacturing processes such as injection molding, extrusion, pultrusion, stamping, assembly, or joining.
• Experience with Design of Experiments (DOE), optimization, parametric analysis, or sensitivity studies.