Machine Learning Engineer
On-siteBerlin, State of Berlin, Germany or Potsdam, Brandenburg, Germany
Job Summary
Design and implement deep learning models for 3D perception, including object detection, semantic segmentation, and occupancy prediction. Develop and optimize multimodal networks fusing LiDAR, radar, and camera data for off-highway autonomous vehicles. Contribute to Vision-Language-Action models integrating perception and language inputs. Optimize training and inference pipelines for real-time deployment on NVIDIA edge GPUs. Lead data initiatives for the perception stack, from pipelines and curation to model evaluation. Collaborate with interdisciplinary teams to integrate perception systems into the full autonomy stack.
Required Qualifications
- Master's or PhD in Computer Science, Robotics, Electrical Engineering, or a related field
- Proficient in Python
- strong experience with PyTorch
- Deep expertise in 3D perception and sensor fusion (LiDAR-camera-radar)
- Practical experience deploying deep learning models in real time on embedded hardware (TensorRT, ONNX, Jetson/Orin)
- Solid understanding of machine learning, deep learning, and autonomous systems
Desired Qualifications
- Experience with transformer-based perception architectures or VLA models
- Familiarity with BEV perception and multitask learning
- Experience with C++, ROS, and mmdetection
- Experience with perception in off-road, adverse-weather, or otherwise challenging conditions
- Proven track record of publications or significant industry experience in deep learning for autonomous driving or robotics
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.