Internship - Python Software Engineering for Data Analysis in Machine Learning (Automotive Unit)

ZF LIFETEC is one of the world's leading suppliers of passive safety systems. As Simi Automotive, a global innovation leader for motion capture software and complete systems for recording and analyzing human movements and a subsidiary of ZF LIFETEC, we contribute our experience with camera-based systems to developing solutions for vehicle interior monitoring and occupant safety. We are working on adaptive restraint systems with our colleagues at ZF LIFETEC.

• Support our team to select fitting statistical metrics and plot types to analyze and visualize the available data
• Implement methods to access, analyze and visualize the data using Python
• Incorporate visualizations into a web app and create an interactive dashboard using a Python framework
• Get acquainted with our internal data infrastructure and machine learning datasets
• Understand annotation types required for various computer vision tasks in the automotive domain
• Write clean, maintainable code and comprehensive unit tests

• Currently enrolled at a university pursuing a Bachelor’s or Master’s degree in computer science or similar
• Study program requires a mandatory internship of minimum 18 weeks
• Practical experience in Python
• Experience with Python libraries such as NumPy and Matplotlib is a plus
• Basic understanding of SQL databases
• Attention to detail as well as precise and structured working style
• Good verbal and written communication skills in English

• Closely collaborate with a small and agile team of highly motivated machine learning and software engineers
• Actively contribute to a Python-based data analysis tool which will benefit future machine learning tasks
• Opportunity to get hands-on experience with exciting computer vision solutions in the automotive domain
• Possibility to write your Bachelor’s thesis or to continue as a working student

Please apply with your up-to-date and complete CV in tabular form, a motivational statement including your earliest possible start date and a current transcript of records.

We look forward to your application!