CAE Vehicle Optimization and Machine Learning Engineer

TL;DR

CAE Vehicle Optimization and Machine Learning Engineer: Lead development and deployment of advanced optimization and ML methods for complex vehicle performance challenges with an accent on multi-physics CAE, cross-domain issues, and physics-based AI. Focus on scaling reusable workflows, root-causing performance problems, and democratizing capabilities across CAE teams.

Location: Hybrid in Warren, Michigan – expected to report to office at least 3 times a week. No immigration sponsorship (H1-B, OPT, etc.). No relocation benefits.

Company

GM’s Vehicle Optimization and Machine Learning team in the CAE organization delivers innovative solutions at the intersection of optimization, multi-physics CAE, and AI/ML to enhance vehicle performance, minimize cost/mass, and accelerate program execution.

What you will do

• Lead development of advanced optimization methods and workflows using commercial CAE/optimization software and internal tools, including multi-disciplinary, stochastic/robust, and ML-enabled technologies.
• Apply optimization and ML to root cause and resolve cross-domain performance issues across structure, crash, NVH, aero/thermal, and propulsion systems while minimizing mass and cost.
• Develop and scale ML applications for CAE, creating custom tools, benchmarking physics-based AI solutions for faster convergence, root cause analysis, and design-space exploration.
• Democratize optimization and ML across CAE teams through training, coaching, and identifying adoption opportunities.
• Define and improve standard work for optimization and ML, ensuring robust, reusable practices aligned with GM processes.
• Collaborate with data, IT, and tool teams to integrate workflows with GM’s CAE, data management, and compute infrastructure.

Requirements

• B.S. in Mechanical, Aerospace, Civil, Electrical Engineering, Physics, or related.
• 5+ years in CAE toolsets, optimization, and ML fundamentals (industry/research).
• Experience with CAE tools: HyperMesh, OptiStruct, Abaqus, LS-DYNA, Simpack, Star-CCM+ or similar.
• Experience with optimization tools: Genesis, OptiStruct, HEEDS/iSIGHT or similar.
• Process automation/scripting: Python, MATLAB, VBA or similar.
• Knowledge of machine learning, focus on physics-based AI and integration into CAE/optimization workflows.
• Strong interpersonal skills and ability to multitask.

Nice to have

• M.S. or Ph.D. in Mechanical, Aerospace, Civil, Electrical Engineering, Physics, or Data Science.
• Experience with CAE morphing/parametric tools: DEP/MeshWorks, ANSA, HyperMorph or similar.

Culture & Benefits

• Human-centered design focus to create safer, smarter, connected vehicles.
• Comprehensive Total Rewards from day one, supporting well-being at work and home.
• Inclusive workplace fostering belonging and development.
• Non-discriminatory employment practices.