Senior Software Engineer - Battery State Estimation

About GM

Qualifications

• Bachelor’s degree in Electrical, Mechanical, Chemical, or Computer Engineering, or Computer Science.
• Familiarity with lithium‐ion chemistries such as LFP and high‐nickel NMC/LMR and associated aging mechanisms.
• Experience with ETAS INCA, MDA, or similar calibration and measurement tools.

Responsibilities

• Design, develop, and productionize robust battery state estimation algorithms for SOC, SOH, and SOP using physics‐based, model‐based, and hybrid data‐driven estimation techniques.
• Develop observers and filters (e.g., equivalent‐circuit and electrochemical‐informed models, Kalman‐filter‐based approaches) that remain accurate across temperature extremes, power transients, sensor noise, and battery aging.
• Incorporate calendar and cycle aging effects into estimation logic so outputs remain truthful throughout the battery lifecycle and across chemistries and pack architectures.
• Implement estimation algorithms as production‐quality embedded software in C/C++, meeting GM standards for safety, cybersecurity, and coding discipline, including MISRA compliance.
• Architect software with a focus on modularity, portability, and hardware abstraction, enabling reuse across multiple vehicle programs and evolving E/E architectures.
• Define and advocate calibration strategies and model‐based approaches that reduce complexity while improving robustness and long‐term maintainability.
• Lead shift‐left verification, technical root-cause analysis and validation through MIL, SIL, and HIL test environments to enable early defect discovery and high validation coverage.
• Develop automated regression, robustness, and fault‐injection test suites integrated into CI pipelines to enforce built‐in quality throughout development.
• Collaborate cross‐functionally with Cell and Pack Engineering, Systems & Functional Safety, Validation, Calibration, Vehicle Performance, SDV Platform and Research & Development teams.
• Mentor and guide other engineers, contribute to technical planning events, and help evolve GM’s battery estimation architecture as a scalable SDV service.
• Own deliverables end‐to‐end and continuously improving technical rigor, development efficiency, and software quality.
• Bachelor’s degree in Electrical, Mechanical, Chemical, or Computer Engineering, or Computer Science.
• Minimum 5 years of experience delivering embedded software for high‐voltage battery systems or similar complex engineering systems.
• Strong proficiency in C/C++ for embedded systems development.
• Demonstrated hands‐on production experience with SOC, SOH, and/or SOP estimation algorithms deployed in vehicles.
• Strong proficiency in MATLAB/Simulink and Python, with hands-on experience in modeling, analysis, automation, and Model-Based Development (MBD) workflows.
• Demonstrated success executing software and controls feature verification in MIL, SIL, and HIL environments.
• Experience working in Agile/Scrum environments and cross‐functional automotive programs.
• Proven ability to operate effectively in ambiguous, fast‐paced SDV development contexts with strong technical ownership and accountability.
• Proven experience leveraging Battery Data to generate actionable insights that improve battery performance, reliability, and lifecycle characteristics.
• Master’s or PhD degree in Engineering or Computer Science.
• Deep expertise in battery modeling and estimation techniques, including observer design and Kalman filter–based approaches.
• 8+ years of experience delivering embedded software for high‐voltage battery systems or similar complex engineering systems.
• Hands‐on experience with battery cell characterization, pack testing, and lab‐based validation.
• Familiarity with lithium‐ion chemistries such as LFP and high‐nickel NMC/LMR and associated aging mechanisms.
• Experience with ETAS INCA, MDA, or similar calibration and measurement tools.
• Experience working within Software‐Defined Vehicle (SDV) architectures and CI/CD‐based software delivery pipelines.
• 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}. Relocation benefits are available for candidates who qualify under company policy.