Machine Learning Engineer - Planning & E2E Driving

Machine Learning Engineer - Planning & E2E Driving

SafeAD

Karlsruhe, Germany

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.