Role Description:

Do you want to work in an innovative and inclusive culture where your contributions serve a greater purpose? Are you skilled in algorithm development, C++ implementation, testing, and deployment? If so, this could be the perfect opportunity for you! Here, you’ll work with cutting-edge technology, making cars smarter and safer with the ultimate goal of reducing traffic accidents. Your work can be tested in vehicles—sometimes on the very same day!

About the Team:
The team focuses on map-based road estimation for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD). The goal is to locate the vehicle within high-definition maps using sensors such as cameras, lidar, and GNSS. This localization is critical for planning vehicle trajectories, enabling autonomous driving functionality.

The team consists of five highly skilled developers working pragmatically and data-driven in an agile and hybrid environment.

Example Responsibilities:

• Develop and evaluate high-performance and safety-critical signal processing algorithms for ADAS and AD features.
• Manage the entire product development lifecycle, from requirement analysis and system design to implementation and testing.
• Write and review C++ production code in a Linux environment, adhering to safety-critical standards.
• Conduct testing, including vehicle-based tests, to ensure functionality and quality.
• Participate in forums and discussions shaping the product’s future direction.
• Develop Python tools to monitor and evaluate algorithm performance.

Requirements and Qualifications:

• Strong C++ programming skills and experience developing complex real-time algorithms.
• Background in signal processing and localization algorithms such as Kalman filtering.
• Proficiency in Python and experience with embedded systems development.
• Understanding of software architecture, test strategies, and data-driven performance evaluation.
• Familiarity with continuous integration and tools such as Git, Gerrit, and Jenkins.
• Degree in computer science, software engineering, electrical engineering, or a related field (M.Sc. or B.Sc.).

Nice-to-have:

• Knowledge of functional safety and safety-critical systems.
• Experience with agile methodologies and a strong quality mindset.

Practical Information:

• Assignment Length: ASAP to 2025-12-31
• Location: Hybrid