Battery Cell Electrochemistry Analysis Engineer

GM•Warren, MI

9d•Hybrid

About The Position

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 Global Virtual Engineering (GVE) at General Motors is looking for driven individuals to become Computer Aided Engineers (CAE) and lead the future of virtual engineering. As a company we are focused on using virtual tools as the primary driver to enable speed and built in quality. This position is a highly technical, interdisciplinary role focused on advancing the future of virtual engineering by developing, integrating, and deploying multi-physics battery cell and pack models. The role combines electrochemical modeling, data science, battery design optimization, and cross-functional technical leadership to deliver models and tools that guide electrochemical, thermal, mechanical, electrical, and safety-related design decisions for electric vehicles. This involves characterization & optimization of battery cell performance for vehicle range, charging capability, and battery aging effects.

Requirements

BS in Computer Science, Data Analytics, Statistics, Chemical, Electrical, or Mechanical Engineering Required; Chemical Engineering preferred.
Strong understanding of modeling processes and tools especially physics based degradation mechanisms and transport phenomena
3+ years of experience using data analytics and knowledge of machine learning and predictive methods.
3+ years of battery electrochemistry modeling experience
Proficiency using relevant tools: Python, MATLAB, Power BI, DataBricks, COMSOL, MATLAB/SIMULINK, SABER, and PyBaMM

Nice To Haves

Advanced degree (MS or greater) in Chemical Engineering, Electrochemical Engineering, Materials Engineering, Mechanical Engineering, or Electrical Engineering preferred.
5+ years of experience using data analytics and knowledge of machine learning and predictive methods.
5+ years of battery electrochemistry modeling experience
Solid understanding of thermo-electric technologies and systems design
Solid understanding and working knowledge of fundamental physics, equations and numerical methods underpinning all software used

Responsibilities

Battery Modeling & Simulation Develop, maintain, and calibrate physiochemical, electrochemical, thermal, mechanical, and safety models for current and future battery chemistries.
Use COMSOL, MATLAB/SIMULINK, SABER, Python, and PyBaMM to implement multi-scale and multi-dimensional cell models.
Collaborate with test teams to enhance test protocols to support model development Participate in development of material test methods and provide electrochemical parameter database
Incorporate cell performance variation, aging mechanisms, and thermal behavior into simulation frameworks
Document models, assumptions, and intended model usage
Support electric vehicle execution by releasing models integrated into full vehicle co-sims supporting calibration, diagnostics, battery state estimation, controls development and warranty
Data Mining & Automation Develop methods to gain data insights applying statistics and machine learning to cell performance data
Improve analysis efficiency by applying variation and statistical methods paired with ML learning