Chief Vision Scientist

• Design and implement robust, efficient, and well-tested perception algorithms for real-world scenarios
• Integrate classical and ML image processing algorithms for classification, depth sensing, and 3D reconstruction
• Select optimal sensors (e.g., LIDARs, time-of-flight cameras, stereo vision) for various applications
• Create AI and ML models to enhance object detection, classification, and tracking capabilities
• Utilize deep learning techniques to improve system accuracy and efficiency
• Conduct extensive testing, validation, and calibration to ensure system accuracy and reliability
• Collaborate with cross-functional teams, including mechanical, system, mechatronic, software and software quality assurance engineers, and domain experts

• Master’s or PhD degree in Computer Science, Computer Vision, Machine Learning, or a related field
• Demonstrated experience designing, implementing, testing, and optimizing vision solutions for robotic or automation applications
• Experience working with pixels, low-level statistical features and filter responses, and higher-level representations (feature descriptors, embeddings)
• Experience implementing algorithms (statistical, ML, DL) for applications such as object detection, tracking, classification, scene segmentation, or SLAM
• Proficiency in AI/ML frameworks (e.g. PyTorch) and computer vision libraries (e.g., OpenCV, PCL, Open3D, CUDA)
• Familiarity with various depth sensing modalities (e.g., LiDAR, stereo vision, time-of-flight) and sensor fusion
• Excellent problem-solving skills, attention to detail, and ability to work in a dynamic environment

• Experience with deploying vision systems in real-world robotic solutions
• Knowledge of robotic control systems, automation protocols, and communication interfaces
• Familiarity with robotic simulation platforms (Issac Sim, Gazebo) to develop robotic systems
• Experience developing within the ROS2 ecosystem

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