In this role, you’ll:
- Develop ML-based motion planners that navigate complex urban environments safely
- Lead experiments in End-to-End (E2E) driving and high-level maneuver planning
- Investigate the use of Foundation Models/VLA for interpretable decision-making and “reasoning” in edge cases
- Bridge the gap between perception outputs and control commands using probabilistic frameworks
- Work on large ML models and big data with our ever growing in-house compute
- Test your software in our self-driving vehicle
We require you to have:
- MSc/PhD in Computer Science, Robotics or equivalent experience
- Experience with sequence to sequence modelling with transformers and / or foundation models
- Strong experience programming in C++ and Python
- A strong team player and learning mindset
It’s a plus if you have:
- Hands-on experience in the fields of autonomous driving and computer vision
- Background in Reinforcement Learning (RL), Imitation Learning, or Behavior Cloning
- Worked in mid to large software projects