• Designing and implementing automated test frameworks for ADAS functions, focusing on automating the workflow to test ADAS on the test- benches
• Building automated log analysis pipelines based on cutting edge LLMs to parse, classify, and triage relevant failures from in-vehicle and simulation runs — reducing manual triage time
• Developing scripts and tools to detect regressions, anomalies, and performance degradations across large volumes of test logs and sensor data
• Integrating test automation tooling into existing CI/CD infrastructure to enable continuous validation of ADAS software changes.

• Pursuing a Master's or PhD degree in Computer Science, Electrical Engineering, Computer Engineering, or Robotics
• Strong Python programming skills; experience writing production- quality scripts for data processing or test automation
• Familiarity with Linux-based development environments and shell scripting (Bash)
• Experience with version control systems such as Git and GitLab
• Analytical mindset with the ability to work through ambiguous failure scenarios and communicate findings clearly.

Ways to Stand Out from the Crowd:

• Prior exposure to test automation frameworks
• Experience with C++ in an embedded or automotive software context
• Familiarity with automotive data formats (e.g., MDF, ROS bags) or in-vehicle bus protocols (CAN, Ethernet).