Modeling Engineer

Description

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.

Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.

The Role:

Virtual Design, Development & Validation - Modeling Engineer :

You will be responsible to own and drive project management and contribute to delivery of Finite Element Analysis (FEA) models for full vehicle programs, collaborating with leadership to integrate process automation and AI/ML applications that enhance modeling efficiency and quality. Collaborate with cross-functional teams, including CAD & simulation engineering, to improve modeling workflows and support quality assurance across models and virtual engineering activities. You will have the chance to grow professionally in project management, virtual simulation, AI/ML, cloud platforms and enterprise leadership via mentorship, structured training, and active engagement in leadership and innovation networks - both internal and external to the department.

• Execute project management tasks and assist in planning and execution of full vehicle and subsystems models for programs to enable first time quality and ontime delivery of models
• Interact, proactively engage, effectively communicate and co-ordinate with Vehicle Performance Integration Manager/Design Release Engineer/Design Engineer/Suppliers/ Performance/Program teams to develop efficient workflows and refine plans for model builds while continuously assessing and mitigating risk.
• Contribute to globally distributed team efforts for model builds.
• Perform risk assessment, monitor progress and enable first time quality and ontime delivery of models
• Support root cause and preventive action activities on quality improvement opportunities for full vehicle safety, body, trim structure (NVH), and flex models. Demonstrate application of 5 why principles leading to process, people and tools improvement
• Identify & Lead efficiency and effectiveness improvement opportunities for master models builds
• Actively apply process integration principles on day to day activities and propose improvements
• Perform full Virtual Vehicle assembly, integration and quality checks on models
• Collaborate with VDDV consumer base and develop robust statement of requirements ( SoR ) for each modelling event
• Support design, development and deployment of AI/ML models to automate and enhance CAE modelling & simulation workflows, including meshing, boundary condition setup, post-processing, and predictive analytics.
• Work closely with CAE, CAD and data science teams to identify opportunities for AI-driven process optimization and digital transformation. Lead cross-functional projects that leverage modelling and simulation data for machine learning applications
• Collaborate with IT and data science teams to integrate machine learning solutions into production environments, ensuring robust model monitoring and continuous improvement
• Document workflows, results, and lessons learned for organizational knowledge sharing.
• Drive innovation by applying AI/ML to improve quality assurance, automate repetitive tasks, and improve model fidelity. Document workflows, results, and lessons learned for organizational knowledge sharing.
• Support technical leadership initiatives and contribute to projects aligned with technology roadmaps for modeling enterprise.

• Bachelor's degree in Engineering, Computer Science , Data Science or Physics
• 3-5 + years relevant experience in Virtual engineering :CAE / Design core / Validation / Design Release/Performance/ Data Analytics & Science/ AI & ML .
• Demonstrated skills in disciplined problem solving and data analysis.
• Knowledge of Finite Element Analysis (FEA) theory and application
• Experience with CAE, CAD or Data analytics tools (ANSA, HYPERMESH, LS-DYNA, Optistruct/NASTRAN, ABAQUS, Primer, Siemens NX/Python/AI-ML framework)
• Exposure to vehicle CAE modeling, simulation, or analysis-such as creating models, supporting, running, or interpreting results from full vehicle safety, trimmed structure, or subsystem models and CAE loadcases per standard work. Candidates with strong AI/ML/Automation expertise who have worked with virtual engineering math and simulation data are also encouraged to apply.
• Foundational experience in Python
• Ability to collaborate with cross-functional teams (e.g., CAD, simulation, data Science).
• Demonstrated skills in disciplined problem solving ( 5- Why ) and data analysis
• Strong communication and teamwork skills

• DFSS black belt or similar certification.
• 2+ years' experience with CAE, CAD, and data analytics tools such as ANSA, Primer, Animator, LS-Dyna, Nastran, Optistruct, Abaqus, HyperWorks (HyperMesh/HyperView), DEP Meshworks, PowerBi, Large Language Models, Python, TensorFlow, PyTorch, Databricks, NX, Teamcenter,Unified digital thread.
• Experience with CAE tool APIs and CAE workflow automation (e.g., ANSA, Altair, NASTRAN, ANSYS,Ls-dyna, Abaqus)
• Experience in AI/ML framework
• Experience developing and deploying AI/ML models for engineering applications (e.g., surrogate modeling, workflow automation).
• Familiarity with MLOps, data engineering, and cloud platforms (e.g., Databricks, Azure, AWS)
• Demonstrated ability to leverage IT platforms (Databricks, LLMs, Python) for optimizing virtual engineering workflows and managing large datasets."
• Experience in cross-functional leadership and change management. Exposure to vehicle development process and cross functional collaboration is a plus
• Masters qualification in Engineering /Data Science