4 days ago
Responsibilities
- Build and improve computer vision pipelines for detection, classification, tracking, and temporal understanding.
- Test first-person perception under camera motion, occlusion, motion blur, and changing lighting.
- Use synthetic and real-world data to identify failure cases and improve model performance.
- Train, evaluate, and debug vision models in PyTorch.
- Explore geometric vision, calibration, localization, pose estimation, and 3D perception.
- Optimize models for low-latency inference and edge deployment.
- Build tools to evaluate real-world performance and support factory deployments.
Requirements
- Study computer science, robotics, electrical engineering, mechanical engineering, or a related field, with an interest in computer vision and physical AI.
- Have Python skills and hands-on experience in computer vision, machine learning, or robotics.
- Helpful experience includes PyTorch, OpenCV, object detection, tracking, synthetic data, SLAM, VIO, 3D vision, CUDA, TensorRT, ROS2, or NVIDIA Jetson.
- Have built and debugged technical projects and be prepared to learn quickly and take ownership.
Benefits
- Visa sponsorship is available.
- Relocation from Germany is supported.
- On-site work in San Francisco, California, United States.
Categories
ML EngineeringRobotics
