Das ist der Job
We believe the key to achieving this is all AI and mapless.
Darum lohnt es sich
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 What we’ll offer you: The chance to work on state-of-the‑art technology for autonomous driving in a motivated team A working place characterized by a flat hierarchy, quick processes and full focus on tech Stock options #J-18808-Ljbffr Machine Learning Engineer (m/f/d) – Planning & E2E Driving Our mission at SafeAD is to deliver the most intelligent and safe autonomous driving technology.
Our technology is used by some of the world’s largest automakers and Tier 1 suppliers.
