Bosch Car Multimedia team is looking for full-time AI (Intern) working at Ho Chi Minh, Vietnam.
The CM team develops high-quality, state-of-the-art Automotive Head Unit and Home Appliance Linux/Android-based systems. Together with other Bosch locations worldwide, we provide software solutions for navigation, vehicle functions, autonomous driving, camera, and IoT features to the car marker.
Our team also contributes to Bosch smart home & IoT solutions through SW delivery to Home appliance products.
As an AI Intern, your typical work activities include:
Collaborate with cross-functional teams including
software engineers and cybersecurity experts to design and implement AI-driven security solutions for automotive applications.
Develop and optimize machine and deep learning models for configuration tools, intrusion detection, anomaly detection, threat prediction, and real-time monitoring of in-vehicle systems.
Build and maintain datasets for training and validation purposes, ensuring high data quality and integrity.
Participate in threat modeling and risk assessment exercises to identify potential security weaknesses and recommend countermeasures.
Stay up-to-date with the latest advancements in AI, machine learning, and automotive security to continuously enhance the effectiveness of our solutions.
Collaborate with external partners, researchers, and industry stakeholders to share insights and best practices in automotive security.
Actively participate in code reviews, debugging, and troubleshooting to ensure the reliability and robustness of AI-based security solutions.
Document research findings, design decisions, and implementation details clearly and comprehensively.
Must be undergraduate student at university.
Able to work full-time in 6 months.
Have a good understanding of Machine Learning. Basic Knowledge of Deep Neural Network is a plus.
Familiar with Python or C/C++, and (basic command) Linux OS.
Familiar with Pandas, Numpy, scikit-learn, Pytorch/Tensorflow, etc.
Knowledge of common ML frameworks and optimization techniques.
Knowledge of developing Deep Learning and classic ML models for practical applications.
Note: We have a large number of applications and will contact only the suitable candidates