The Nuclear Company is looking to solve the problem of transforming nuclear construction through automated progress tracking, real-time safety monitoring, and intelligent quality control using AI-powered computer vision systems.
Requirements
- Expert proficiency in computer vision libraries (OpenCV, scikit-image, PIL/Pillow)
- Deep understanding of classical CV techniques (edge detection, feature extraction, optical flow, SLAM)
- Experience with 3D computer vision (stereo vision, structure from motion, photogrammetry)
- Knowledge of image processing techniques (filtering, segmentation, morphological operations)
- Proficiency in video analytics and real-time processing
- Understanding of camera calibration, lens distortion correction, and geometric transformations
- Expert knowledge of deep learning frameworks (PyTorch, TensorFlow, Keras)
Responsibilities
- Design and develop AI-powered computer vision systems for automated construction progress monitoring
- Build real-time video analytics systems that analyze camera feeds and drone imagery to detect construction issues
- Develop automated inspection systems using AI and computer vision to verify construction quality and detect deviations
- Create computer vision algorithms for anomaly detection, defect identification, and automated image analysis from drone and camera feeds
- Implement 3D reconstruction from image sequences and point clouds for digital twin development
- Design and deploy multi-camera networks across construction sites for comprehensive visual coverage
- Develop AI safety enforcement systems that analyze camera feeds in real-time to detect PPE compliance
Other
- Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or related field
- 12+ years of experience in computer vision, machine learning, or AI development
- 5+ years in a senior or lead role with demonstrated technical leadership
- Excellent problem-solving abilities with creative approach to vision challenges
- Strong communication skills to explain complex AI concepts to diverse stakeholders
