Principal BMS AI Algorithm Developer (Embedded Edge AI) (f/m/d)
NXP Semiconductors
Principal BMS AI Algorithm Developer (Embedded Edge AI) (f/m/d)
Job Description
We are seeking a highly experienced Principal BMS AI Algorithm Developer to lead the design and deployment of advanced diagnostic and prognostic algorithms for next‑generation Battery Management Systems (BMS) within an automotive OEM environment.This role focuses on edge-based intelligence, where algorithms run directly on embedded BMS hardware, operating under strict constraints on latency, compute, memory, and functional safety. You will drive innovation at the intersection of battery cell chemistry, electrochemical modeling, impedance-based diagnostics, embedded systems, and AI/ML, enabling real-time monitoring of battery health and prediction of safety-critical events.Key ResponsibilitiesLead the design and development of AI-driven diagnostic and prognostic algorithms for embedded BMS platforms.Architect hybrid models combining battery cell chemistry, impedance diagnostics, and AI/ML approaches.Develop real-time algorithms for:State of Charge (SoC)State of Health (SoH)State of Power (SoP)Fault detection and anomaly diagnosisSafety prediction (e.g., thermal runaway precursors)Leverage electrochemical impedance spectroscopy (EIS) for advanced diagnostics.Develop and validate algorithms using MATLAB, Simulink, and Python.Deploy and optimize models on embedded platforms (C/C++, AUTOSAR).Utilize NXP eIQ AI/ML tools and embedded SDKs for deployment on automotive microcontrollers.Apply edge AI optimization techniques (quantization, pruning, efficient inference).Ensure compliance with ISO 26262 and automotive OEM standards.Collaborate across System, hardware, software, and Validation teams.Required QualificationsMaster’s or PhD in Electrical Engineering, Electrochemistry, Computer Science, or related field.10+ years of experience in BMS or battery systems (Automotive OEM / Tier-1 preferred).Deep expertise in battery cell chemistry and electrochemical behavior.Proven experience in battery algorithm development:SoC / SoH / SoP estimationDegradation modelingFault diagnostics & safety predictionHands-on experience with:MATLAB, Simulink, PythonElectrochemical Impedance Spectroscopy (EIS)Experience deploying algorithms on embedded systems (C/C++, AUTOSAR).Hands-on experience with NXP AI toolchain, including:eIQ Machine Learning Software Development EnvironmentDeployment on NXP S32K / S32G platforms or similar automotive MCUsExpertise in state estimation and mathematical modeling techniques.Strong understanding of real-time and resource-constrained systems.Leadership & Principal-Level ExpectationsDefine technical roadmap for AI-driven BMS systems.Act as SME (Subject Matter Expert) in battery algorithms, impedance diagnostics, and embedded AI.Drive innovation in intelligent BMS features.Mentor cross-functional teams.Key SkillsBattery cell chemistry & electrochemical modelingElectrochemical impedance spectroscopy (EIS)MATLAB, Simulink, PythonEmbedded AI / Edge MLNXP eIQ AI tools & automotive MCU platforms (S32K/S32G)AI frameworks (TensorFlow, PyTorch, etc..)Real-time systems & optimizationSafety-critical automotive systemsMore information about NXP in Germany...#LI-38ff
Locations
- Munich
Skills Required
- BMSintermediate
- battery cell chemistryintermediate
- NXP AI toolchainintermediate
- state estimationintermediate
- battery algorithm developmentintermediate
Required Qualifications
- Master’s or PhD in Electrical Engineering, Electrochemistry, Computer Science, or related field. (degree in phd in electrical engineering)
- 10+ years of experience in BMS or battery systems (Automotive OEM / Tier-1 preferred). (experience, 10 years)
- Deep expertise in battery cell chemistry and electrochemical behavior. (experience)
- Proven experience in battery algorithm development:SoC / SoH / SoP estimationDegradation modelingFault diagnostics & safety prediction (experience)
- Hands-on experience with:MATLAB, Simulink, PythonElectrochemical Impedance Spectroscopy (EIS) (experience)
- Experience deploying algorithms on embedded systems (C/C++, AUTOSAR). (experience)
- Hands-on experience with NXP AI toolchain, including:eIQ Machine Learning Software Development EnvironmentDeployment on NXP S32K / S32G platforms or similar automotive MCUs (experience)
- Expertise in state estimation and mathematical modeling techniques. (experience)
- Strong understanding of real-time and resource-constrained systems. (experience)
- Master’s or PhD in Electrical Engineering, Electrochemistry, Computer Science, or related field. (degree in phd in electrical engineering)
- 10+ years of experience in BMS or battery systems (Automotive OEM / Tier-1 preferred). (experience, 10 years)
- Deep expertise in battery cell chemistry and electrochemical behavior. (experience)
- Proven experience in battery algorithm development: (experience)
- SoC / SoH / SoP estimation (experience)
- Degradation modeling (experience)
- Fault diagnostics & safety prediction (experience)
- Hands-on experience with: (experience)
- MATLAB, Simulink, Python (experience)
- Electrochemical Impedance Spectroscopy (EIS) (experience)
- Experience deploying algorithms on embedded systems (C/C++, AUTOSAR). (experience)
- Hands-on experience with NXP AI toolchain, including: (experience)
- eIQ Machine Learning Software Development Environment (experience)
- Deployment on NXP S32K / S32G platforms or similar automotive MCUs (experience)
- Expertise in state estimation and mathematical modeling techniques. (experience)
- Strong understanding of real-time and resource-constrained systems. (experience)
Responsibilities
- Lead the design and development of AI-driven diagnostic and prognostic algorithms for embedded BMS platforms.
- Architect hybrid models combining battery cell chemistry, impedance diagnostics, and AI/ML approaches.
- Develop real-time algorithms for:State of Charge (SoC)State of Health (SoH)State of Power (SoP)Fault detection and anomaly diagnosisSafety prediction (e.g., thermal runaway precursors)
- Leverage electrochemical impedance spectroscopy (EIS) for advanced diagnostics.
- Develop and validate algorithms using MATLAB, Simulink, and Python.
- Deploy and optimize models on embedded platforms (C/C++, AUTOSAR).
- Utilize NXP eIQ AI/ML tools and embedded SDKs for deployment on automotive microcontrollers.
- Apply edge AI optimization techniques (quantization, pruning, efficient inference).
- Ensure compliance with ISO 26262 and automotive OEM standards.
- Collaborate across System, hardware, software, and Validation teams.
- Lead the design and development of AI-driven diagnostic and prognostic algorithms for embedded BMS platforms.
- Architect hybrid models combining battery cell chemistry, impedance diagnostics, and AI/ML approaches.
- Develop real-time algorithms for:
- State of Charge (SoC)
- State of Health (SoH)
- State of Power (SoP)
- Fault detection and anomaly diagnosis
- Safety prediction (e.g., thermal runaway precursors)
- Leverage electrochemical impedance spectroscopy (EIS) for advanced diagnostics.
- Develop and validate algorithms using MATLAB, Simulink, and Python.
- Deploy and optimize models on embedded platforms (C/C++, AUTOSAR).
- Utilize NXP eIQ AI/ML tools and embedded SDKs for deployment on automotive microcontrollers.
- Apply edge AI optimization techniques (quantization, pruning, efficient inference).
- Ensure compliance with ISO 26262 and automotive OEM standards.
- Collaborate across System, hardware, software, and Validation teams.
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