We are looking for a technically oriented QA & System Validation Student to join our team and work on advanced automotive perception technologies based on Stereo Vision and Stereo Camera Calibration.
This is a hands-on role combining software, hardware, computer vision, and real-world automotive systems. You’ll be involved in testing, system validation, troubleshooting, data analysis, and technical debugging, with exposure to Field Application Engineering (FAE) activities.
What You’ll Do:
Execute functional, regression, and system-level tests.
Design and execute test cases based on product requirements.
Analyze logs, test results, and system behavior to identify issues.
Investigate, reproduce, and document software and system failures.
Work with real-world sensor data, video, and Computer Vision datasets.
Develop scripts and tools for test automation and data analysis.
Support system setup, troubleshooting, and FAE/POC activities.
Requirements
3rd/ 4th year B.Sc. student in Computer Science, Software Engineering, Computer Engineering, or Systems Engineering.
Available 3+ days per week.
Strong technical, analytical, and troubleshooting skills.
Hands-on experience with Linux and command line.
Good knowledge of Python.
Strong technical English, written and spoken.
Independent, curious, and quick to learn new technologies.
Advantage
QA / software testing / system validation experience.
Python test automation.
Networking basics (TCP/IP, SSH, ports).
Git and CI/CD.
Computer Vision, Stereo Vision, camera calibration.
NVIDIA Jetson / CUDA / GPU environments.
Jira / Agile / Scrum.
You don’t need to know Stereo Vision on day one. We’re looking for someone who is curious, hands-on, and naturally asks “Why isn’t this working?” — then investigates, reproduces, collects evidence, and finds the root cause.
