CAE Modeling Lead

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

You will be responsible for leading the project management and delivery of Finite Element Analysis (FEA) models for full vehicle programs, integrating process automation and AI/ML applications to enhance modeling efficiency and quality. By uniting modelling art and science with data-driven innovation, you will collaborate with cross-functional teams, including CAD & simulation engineering, to continuously improve modeling workflows, accelerate GxDP and ensure robust quality assurance across models and virtual engineering activities. You will have opportunities for professional growth in project management, AI/ML, cloud platforms, and enterprise leadership through mentorship, training, and participation in leadership & innovation communities

What You'll Do

Independent Project Management and leadership 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.

Lead and leverage globally distributed team for model builds

Perform risk assessment, monitor progress and enable first time quality and ontime delivery of models

Lead conducting robust root cause and preventive action summary on quality improvement opportunities on 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 with a focus on Safety and NVH models

Collaborate with VDDV consumer base and develop robust statement of requirements ( SoR ) for each modelling event

Design, develop, and deploy 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

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.

Leverage internal best practices and provide technical leadership and lead road to lab to math projects in alignment with Technology Roadmaps & Vision for modelling enterprise

Your Skills & Abilities (Required Qualifications)

Bachelor's degree in Engineering, Computer Science , Data Science or Physics

6+ years relevant experience in Virtual engineering: CAE / Design core / Validation / Design Release/Performance/ Data Analytics & Science/ AI & ML .

Knowledge of vehicle development process and cross functional interfaces

Demonstrated skills in disciplined problem solving and data analysis.

Knowledge of Finite Element Analysis (FEA) theory and application

Experience with CAE/CAD/data analytics tools (ANSA, HYPERMESH, LS-DYNA, Optistruct/NASTRAN, ABAQUS, Primer, Siemens NX/Catia/Python/AI-ML framework)

3+ years of hands -on experience and demonstrated ability in creating Full Vehicle Safety and Crashworthiness /Trimmed Structure/Complex vehicle subsystem models and analysis/synthesis of vehicle CAE loadcases for product development

Foundational experience in Python

Demonstrated 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 problem-solving, communication, and project management skills.

What Will Give You A Competitive Edge (Preferred Qualifications)

DFSS black belt or similar certification.

10+ years relevant experience in Virtual engineering: CAE / Design Release / Performance/ Data Analytics & Science.

3+ years’ experience with CAE, CAD, and data analytics tools such as ANSA, Primer, Animator, LS-Dyna, Nastran, Optistruct/Radioss, Metapost, 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 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).

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.

Masters qualification in Engineering /Data Science /MBA

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.)

This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.

This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Total Rewards | Benefits Overview

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Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

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