Huawei Research Center Germany & Austria
Vehicle Dynamics Controls Principal(m/w/x)
Full-timeOn-siteSenior
München
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DEDE63 NXP Semiconductors Germany GmbH
Principal BMS AI Algorithm Developer (Embedded Edge AI)(m/w/x)
München
Full-timeOn-siteSenior
AI/ML
Nejo AI Summary
Designing AI-driven diagnostic and prognostic algorithms for embedded BMS platforms, architecting hybrid models combining cell chemistry and AI/ML. 10+ years of battery systems experience required. Real-time SoC, SoH, and SoP algorithm development.
Requirements
- Master’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 estimation, Degradation modeling, Fault diagnostics & safety prediction)
- Hands-on experience with MATLAB, Simulink, Python, and Electrochemical Impedance Spectroscopy (EIS)
- Experience deploying algorithms on embedded systems (C/C++, AUTOSAR)
- Hands-on experience with NXP AI toolchain (eIQ Machine Learning Software Development Environment, Deployment on NXP S32K / S32G platforms or similar automotive MCUs)
- Expertise in state estimation and mathematical modeling techniques
- Strong understanding of real-time and resource-constrained systems
- Battery cell chemistry & electrochemical modeling
- Electrochemical impedance spectroscopy (EIS)
- MATLAB, Simulink, Python
- Embedded AI / Edge ML
- NXP eIQ AI tools & automotive MCU platforms (S32K/S32G)
- AI frameworks (TensorFlow, PyTorch, etc..)
- Real-time systems & optimization
- Safety-critical automotive systems
Tasks
- Lead 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)
- Develop real-time algorithms for State of Health (SoH)
- Develop real-time algorithms for State of Power (SoP)
- Develop real-time algorithms for fault detection and anomaly diagnosis
- Develop real-time algorithms for 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
- Define technical roadmap for AI-driven BMS systems
- Act as SME in battery algorithms, impedance diagnostics, and embedded AI
- Drive innovation in intelligent BMS features
- Mentor cross-functional teams
Work Experience
- 10 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- MATLAB
- Simulink
- Python
- Electrochemical Impedance Spectroscopy (EIS)
- C/C++
- AUTOSAR
- NXP AI toolchain
- eIQ Machine Learning Software Development Environment
- NXP S32K / S32G platforms
- automotive MCUs
- TensorFlow
- PyTorch
- Embedded AI
- Edge ML
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of DE63 NXP Semiconductors Germany GmbH and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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DEDE63 NXP Semiconductors Germany GmbH
Principal BMS AI Algorithm Developer (Embedded Edge AI)(m/w/x)
München
Full-timeOn-siteSenior
AI/ML
Nejo AI Summary
Designing AI-driven diagnostic and prognostic algorithms for embedded BMS platforms, architecting hybrid models combining cell chemistry and AI/ML. 10+ years of battery systems experience required. Real-time SoC, SoH, and SoP algorithm development.
Requirements
- Master’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 estimation, Degradation modeling, Fault diagnostics & safety prediction)
- Hands-on experience with MATLAB, Simulink, Python, and Electrochemical Impedance Spectroscopy (EIS)
- Experience deploying algorithms on embedded systems (C/C++, AUTOSAR)
- Hands-on experience with NXP AI toolchain (eIQ Machine Learning Software Development Environment, Deployment on NXP S32K / S32G platforms or similar automotive MCUs)
- Expertise in state estimation and mathematical modeling techniques
- Strong understanding of real-time and resource-constrained systems
- Battery cell chemistry & electrochemical modeling
- Electrochemical impedance spectroscopy (EIS)
- MATLAB, Simulink, Python
- Embedded AI / Edge ML
- NXP eIQ AI tools & automotive MCU platforms (S32K/S32G)
- AI frameworks (TensorFlow, PyTorch, etc..)
- Real-time systems & optimization
- Safety-critical automotive systems
Tasks
- Lead 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)
- Develop real-time algorithms for State of Health (SoH)
- Develop real-time algorithms for State of Power (SoP)
- Develop real-time algorithms for fault detection and anomaly diagnosis
- Develop real-time algorithms for 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
- Define technical roadmap for AI-driven BMS systems
- Act as SME in battery algorithms, impedance diagnostics, and embedded AI
- Drive innovation in intelligent BMS features
- Mentor cross-functional teams
Work Experience
- 10 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- MATLAB
- Simulink
- Python
- Electrochemical Impedance Spectroscopy (EIS)
- C/C++
- AUTOSAR
- NXP AI toolchain
- eIQ Machine Learning Software Development Environment
- NXP S32K / S32G platforms
- automotive MCUs
- TensorFlow
- PyTorch
- Embedded AI
- Edge ML
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of DE63 NXP Semiconductors Germany GmbH and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
DE63 NXP Semiconductors Germany GmbH
Industry
Automotive
Description
The company is a leading semiconductor company.
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