Senior Researcher, AI/ML Battery Modeler

Job Description

Senior Researcher, AI/ML Battery Modeler

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to the Research Administration Building at our Global Technical Center in Warren, MI three times per week, at minimum.

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.

Why GM Battery R&D?

At GM, your work won’t sit on a shelf – you’ll see it power real vehicles on the road. You’ll move ideas from theory → model → product, working at the intersection of fundamental science, advanced modeling, and real-world impact. Our Research team offers the opportunity to:

• Work alongside globally recognized experts across battery materials, modeling, and systems engineering

• Tackle open-ended, high-impact problems spanning electrochemistry, thermal science, mechanics, data science, and AI

• Leverage cutting-edge experimental facilities, advanced instrumentation, and high-performance computing

• Use state-of-the-art AI/ML and scientific modeling tools to generate new insights

• Be supported to publish and present original research in leading journals and top conferences

• Collaborate with battery suppliers, tier 1 research universities, national labs, and DOE/NSF-funded programs

• See your research directly implemented in GM EVs at a global scale

• Grow across technical, leadership, and research career paths in a deeply technical environment

The Role
As a Senior Researcher, you will shape the future of electric mobility by developing next-generation battery models using advanced AI/ML techniques. You’ll build physics-informed, data-driven, and hybrid models – while defining new modeling approaches that push the boundaries of battery science and AI.

What You’ll Do

• Develop and deploy advanced AI/ML models, including physics-informed and hybrid approaches, to predict battery performance, aging, and degradation

• Build and refine Multiphysics models that couple electrochemical, thermal, and mechanical behavior

• Identify and develop novel modeling approaches for next-generation battery chemistries and systems

• Turn complex experimental and simulation datasets into actionable insights using Python-based scientific computing and ML frameworks

• Partner with engineering teams to translate research into production, integrating models into battery management systems (BMS) and product workflows

• Publish and present your work through peer-reviewed journals, conferences, and technical forums

• Drive technical direction through deep problem solving, collaboration, and influence across disciplines

• Contribute to intellectual property and patents for new algorithms and modeling innovations

Your Skills & Abilities (Required Qualifications)

• Master’s or Ph.D. in Electrical Engineering, Physics, Computer Science, Materials Science, Chemical Engineering, or related field with a focus on AI/ML

• Proven experience developing AI/ML models, ideally applied to batteries, electrochemical systems, or Multiphysics domains

• Strong Python proficiency (required) with experience in ML/scientific libraries (e.g., PyTorch, TensorFlow, NumPy, SciPy)

• Strong analytical skills with the ability to extract insight from complex datasets

• Demonstrated research experience (e.g., publications, technical reports, or conference presentations)

• Ability to clearly communicate complex technical concepts to diverse audiences

• Strong collaboration and problem-solving skills, with the ability to influence across teams

• Commitment to continuous learning and advancing the state of the art in AI/ML and battery technology

What will give you a competitive edge (Preferred Qualifications)

• Experience with physics-informed or hybrid modeling approaches

• Background in battery degradation, aging, or lifetime modeling

• Familiarity with battery management systems (BMS) or system-level integration

• Experience with large-scale datasets or high-