Design and implement Autonomous Vehicles software, including system integration, application design, performance/power optimization, and stress/stability/compliance testing.
Drive the reliability of the whole software system, including time sync, vehicle network, RADAR, LiDAR, and camera sensor processing, and fusion.
Help turn hard-won debugging expertise into tooling and automation, including AI-assisted analysis of logs and vehicle data, so that problems are found faster and recur less.
Develop a strong technical understanding of the stack, and proactively identify new opportunities and creative ways to solve or mitigate technical challenges.
What we need to see
Pursuing a BS or MS in CS/CE/EE/Robotics or a related field.
Demonstrated proficiency in both C/C++ and Python: C/C++ to understand and debug the vehicle software stack, Python to build the tooling around it.
Strong debugging instincts: you can read logs and traces, form a hypothesis, and prove or disprove it with evidence.
Ability of using modern AI coding assistants as part of your everyday workflow, while verifying what they produce.
Familiar with git or other version control tooling.
Ability and flexibility to work and communicate effectively in a multinational, multi-time-zone environment.
Self-motivated and a good teammate.
Ways to stand out from the crowd
Good knowledge of key Autonomous Driving technologies and the typical challenges of key components; prior experience in the AV field.
Worked with CAN and related tools, RADAR, LiDAR.
Hands-on experience with LLM-based tooling: prompt and context design, tool calling, agent workflows, or evaluation of model output on a real task.
Experience with large-scale log analysis and cloud-based workflows.
