Principal BMS AI Algorithm Developer (Embedded Edge AI) (f/m/d)
Tasks
- Apply edge AI optimization techniques for efficient inference
- Architect hybrid models using battery chemistry impedance diagnostics and AI ML
- Deploy and optimize models on embedded platforms using C and AUTOSAR
- Develop and validate algorithms using MATLAB Simulink and Python
- Develop real time state of charge state of health state of power and fault diagnostics algorithms
- Develop safety prediction algorithms for thermal runaway precursors
- Ensure compliance with ISO 26262 standards
- Lead design and development of diagnostic and prognostic algorithms for embedded BMS
- Leverage electrochemical impedance spectroscopy for diagnostics
- Use NXP eIQ tools and embedded SDKs for deployment on automotive microcontrollers
Perks/Benefits
- N/A
Skills/Tech-stack
AUTOSAR | Artificial Intelligence | Battery Cell Chemistry | C# | Cell Chemistry | Edge AI | Electrochemical impedance spectroscopy | Electrochemical modeling | Embedded Systems | ISO 26262 | Impedance spectroscopy | MATLAB | Machine Learning | Mathematical Modeling | Model Pruning | Model Quantization | PyTorch | Python | Real Time | Real-time Systems | Simulink | State Estimation | TensorFlow | Time Systems
Education
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