General Motors
Senior Engineer – Virtualization, AI &ML
General Motors, Warren, Michigan, United States, 48091
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 The Senior Engineer – Virtualization, AI &ML will lead advanced initiatives applying machine learning, artificial intelligence, and data analytics to EV battery design, simulation, and performance optimization. This role will focus on predictive modeling, intelligent automation, and virtual validation to accelerate battery development for next-generation electric vehicles. The lead virtual engineer will collaborate across engineering disciplines to integrate AI-driven solutions into battery CAE workflows, enabling smarter, faster, and more sustainable energy storage systems.
What You'll Do
Develop and deploy AI/ML and Generative AI methodologies for EV battery design, thermal management, and lifecycle prediction.
Create data-driven models for battery performance, degradation, and safety under diverse operating conditions.
Implement optimization algorithms for cell and pack architecture, balancing energy density, cost, and durability.
Explore emerging technologies such as reinforcement learning and graph-based models for advanced battery system modelling and analysis.
Accelerate simulation workflows for electrochemical, thermal, and structural analysis using AI-driven surrogate models.
Perform test-to-model correlation leveraging advanced analytics to validate virtual predictions against physical testing.
Communicate insights through interactive dashboards and visualization tools for stakeholders.
Contribute to benchmarking activities for AI/ML tools and virtual engineering technologies in battery systems.
Your Skills & Abilities (Required Qualifications)
MS or PhD in Electrical Engineering, Mechanical Engineering, Computer Science, Applied Mathematics, or related STEM field.
Strong foundation in machine learning, data analytics, and optimization techniques.
Proficiency in programming languages such as Python, C++, and experience with AI frameworks (TensorFlow, PyTorch).
Proven experience with AI/ML and Generative AI frameworks in system design or simulation.
Ability to bridge research and practical implementation in complex engineering environments.
Prior research publications or patents in AI-driven engineering solutions.
Excellent analytical, problem-solving, and communication skills.
Strong organizational and leadership skills
What Will Give You a Competitive Edge (Preferred Qualifications)
Familiarity with EV battery design principles, electrochemical modeling, and CAE workflows.
Experience with MATLAB/Simulink and integration of AI workflows into simulation environments.
Track record of delivering enterprise-grade virtual engineering tools
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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 The Senior Engineer – Virtualization, AI &ML will lead advanced initiatives applying machine learning, artificial intelligence, and data analytics to EV battery design, simulation, and performance optimization. This role will focus on predictive modeling, intelligent automation, and virtual validation to accelerate battery development for next-generation electric vehicles. The lead virtual engineer will collaborate across engineering disciplines to integrate AI-driven solutions into battery CAE workflows, enabling smarter, faster, and more sustainable energy storage systems.
What You'll Do
Develop and deploy AI/ML and Generative AI methodologies for EV battery design, thermal management, and lifecycle prediction.
Create data-driven models for battery performance, degradation, and safety under diverse operating conditions.
Implement optimization algorithms for cell and pack architecture, balancing energy density, cost, and durability.
Explore emerging technologies such as reinforcement learning and graph-based models for advanced battery system modelling and analysis.
Accelerate simulation workflows for electrochemical, thermal, and structural analysis using AI-driven surrogate models.
Perform test-to-model correlation leveraging advanced analytics to validate virtual predictions against physical testing.
Communicate insights through interactive dashboards and visualization tools for stakeholders.
Contribute to benchmarking activities for AI/ML tools and virtual engineering technologies in battery systems.
Your Skills & Abilities (Required Qualifications)
MS or PhD in Electrical Engineering, Mechanical Engineering, Computer Science, Applied Mathematics, or related STEM field.
Strong foundation in machine learning, data analytics, and optimization techniques.
Proficiency in programming languages such as Python, C++, and experience with AI frameworks (TensorFlow, PyTorch).
Proven experience with AI/ML and Generative AI frameworks in system design or simulation.
Ability to bridge research and practical implementation in complex engineering environments.
Prior research publications or patents in AI-driven engineering solutions.
Excellent analytical, problem-solving, and communication skills.
Strong organizational and leadership skills
What Will Give You a Competitive Edge (Preferred Qualifications)
Familiarity with EV battery design principles, electrochemical modeling, and CAE workflows.
Experience with MATLAB/Simulink and integration of AI workflows into simulation environments.
Track record of delivering enterprise-grade virtual engineering tools
#J-18808-Ljbffr