2 months ago
Berlin, GermanySenior
Responsibilities
- Design and implement deep-learning models for 3D perception, including object detection, semantic segmentation, and occupancy prediction.
- Develop and optimize multimodal networks that fuse LiDAR, radar, and camera data for off-highway autonomous vehicles.
- Contribute to Vision-Language-Action models combining perception and language inputs for physical AI.
- Optimize training and inference pipelines for real-time deployment on NVIDIA edge GPUs.
- Lead perception data initiatives covering data pipelines, data curation, and model evaluation.
- Collaborate with interdisciplinary teams to integrate perception systems into the full autonomy stack.
Requirements
- Master’s or PhD in Computer Science, Robotics, Electrical Engineering, or a related field.
- Proficiency in Python and strong experience with PyTorch.
- Deep expertise in 3D perception and LiDAR-camera-radar sensor fusion.
- Practical experience deploying deep-learning models in real time on embedded hardware using TensorRT, ONNX, and Jetson/Orin.
- Solid understanding of machine learning, deep learning, and autonomous systems.
- Preferred: experience with transformer-based perception architectures or Vision-Language-Action models.
- Preferred: familiarity with BEV perception and multitask learning.
- Preferred: experience with C++, ROS, and mmdetection.
- Preferred: experience with perception in off-road, adverse-weather, or otherwise challenging conditions.
- Preferred: publications or significant industry experience in deep learning for autonomous driving or robotics.
Benefits
- Attractive compensation package and stock options.
- Beverages on-site and regular social events.
- Access to top-tier researchers, engineers, and thought leaders.
- Opportunity to influence robotic technologies and tackle significant technological challenges.
- Assistance with relocation to Berlin.
- Berlin/Potsdam-based role with an office environment.
Categories
ML EngineeringRobotics
