[EAB] Automation & AI Tooling Intern (Python/ML/Simulink)

The Occupant Safety Systems (OSS) team at Bosch is responsible for developing and producing Airbag ECUs used in millions of vehicles worldwide. We combine engineering excellence and automation expertise to improve safety and efficiency in airbag development.
We are looking for a passionate intern to support our Calibration Automation and AI Tool Calibration Tool. You will work at the intersection of software automation engineering, AI/ML, and calibration engineering.
Key Responsibilities
1. Automation Tool Development
Develop and enhance Python-based tools to support calibration workflow (data processing, batch automation, reporting, visualization, etc.).
Maintain existing calibration utilities (GUI tools, batch job tools, file parsers).
Implement process improvements to reduce manual process
Make documentation, user guides, and best practices for tool usage.
2. Tool Maintenance & Enhancement (Boosting Model)
You will directly support the existing AI Calibration Quality Tool, which uses a Boosting-based ML model to detect abnormal airbag sensor signals
Maintain and update the Python AI tool used for signal anomaly detection.
Improve feature extraction logic for sensor and crash signals.
Analyze false positives/false negatives and propose model refinements.
Retrain the Boosting model with new datasets under engineer supervision.
Implement automatic reporting of detected anomalies for calibration engineers.
Integrate the AI module with existing calibration automation tools.
Ensure tool stability, accuracy, and performance.
3. Calibration Engineering Support
Process and prepare crash test data from vehicle/lab tests.
Undergraduate students in Computer Science, IT, Electrical/Automotive Engineering, or related field.
Strong Python, C\C++ programming skills.
Official university recommendation letter with stamp (mandatory)
Commitment: full-time or at least 4 days/week, duration 6 months
Basic knowledge of:
Machine Learning fundamentals
Signal processing concepts
Data structures & algorithms
Logical thinking, curiosity, and willingness to learn automotive systems.
Good English communication and teamwork skills.
Nice to Have
Experience with Boosting models (XGBoost, LightGBM, CatBoost).
Familiarity with sensor data, time-series, or anomaly detection.
Basic understanding of MATLAB/Simulink.
GUI development experience (Tkinter, PyQt, PySimpleGUI).
Experience with data automation / scripting / tool development.
Knowledge of vehicle dynamics or physics.

Employment type
Full-time

Work arrangement
No