
CAE Engineer
Responsibilities
- Execute simulations to evaluate full vehicle structural crashworthiness performance for high and low speed frontal, side, rear impact and pedestrian protection
- Collaborate with Test Engineering teams to develop and support subsystem level and full vehicle crash tests
- Perform detailed post-crash test analysis and correlate CAE simulations to test results
- Where appropriate, conduct DOE/DFSS studies by utilizing optimization tools, on vehicle designs to meet performance requirements within the constraints of conflicting attributes such cost and mass.
- Develop inverse design frameworks using surrogate modeling and physics-informed AI to generate lightweight, high-performance structural concepts.
- Apply advanced machine learning techniques (e.g., PhysicsAI, neural surrogates, conditional variational autoencoders) to predict energy absorption and optimize design iterations, reducing simulation time and minimizing physical prototyping requirements.
- Partner with design, test, and hardware teams to define multidomain performance requirements, real-world crash scenarios, and system-level safety targets.
- Contribute to the development of scalable, ML-integrated simulation workflows and frameworks for faster, smarter decision-making across the vehicle development lifecycle.
Qualifications
- Master’s degree in mechanical engineering, or related discipline. PhD is preferred.
- 3 years of experience in CAE Structural Analysis
- Knowledge of Global regulatory and consumer safety requirements: FMVSS / UNECE / China, USNCAP, IIHS, Euro NCAP, China NCAP etc.
- Strong analytical skills to draw meaningful conclusions from CAE results
- Demonstrable ability to concisely present technical issues, CAE results, findings and propose next steps
- Knowledge of Inverse design, and AI-driven structural optimization.
- Strong proficiency in CAE tools including LS-DYNA, ANSA, HyperMesh, Primer, Genesis, and ANSYS ACP/Workbench.
- Knowledge of machine learning and optimization methods, including regression, surrogate modeling, neural networks, generative-AI architectures (e.g., cVAE, PINNs)
- Advanced scripting using Python and MATLAB.
- Demonstrated automating of CAE workflows and integrating ML models into engineering pipelines.
Base Pay Range (Annual)
$93,300 - $128,260 USD
Additional Compensation and Benefits: Lucid offers a wide range of competitive benefits, including medical, dental, vision, life insurance, disability insurance, vacation, and 401k. The successful candidate may also be eligible to participate in Lucid’s equity program and/or a discretionary annual incentive program, subject to the rules governing such programs. (Cash or equity incentive awards, if any, will depend on various factors, including, without limitation, individual and company performance.)
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