Principal Vision Developer

The Nuclear Company is the fastest growing startup in the nuclear and energy space creating a never before seen fleet‑scale approach to building nuclear reactors. Through its design‑once, build‑many approach and coalition building across communities, regulators, and financial stakeholders, The Nuclear Company is committed to delivering safe and reliable electricity at the lowest cost, while catalyzing the nuclear industry toward rapid development in America and globally.

The Principal Vision Developer is a senior technical leadership role responsible for designing, developing, and deploying advanced computer vision and AI‑powered visual systems that transform nuclear construction, safety monitoring, and quality control. This position requires deep expertise in machine learning, image processing, camera systems integration, and real‑time video analytics to enable automated progress tracking, safety compliance monitoring, and intelligent inspection systems for Nuclear OS.

You’ll work at the intersection of artificial intelligence and nuclear infrastructure, helping to automate visual inspection, detect anomalies, and ensure construction quality through cutting‑edge computer vision technology.

• Design and develop AI‑powered computer vision systems for automated construction progress monitoring, comparing current site images to BIM models to determine completion percentages
• Build real‑time video analytics systems that analyze camera feeds and drone imagery to detect construction issues, missing components, and deviations from design
• 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
• Integrate AI‑enabled cameras into IoT sensor networks for real‑time data collection and analysis
• Implement camera calibration systems for accurate geometric measurements and 3D reconstruction
• Develop multi‑camera synchronization for stereo vision and 360‑degree coverage
• Build camera management systems for configuration, monitoring, and maintenance of distributed camera networks
• Integrate various camera types including fixed surveillance cameras, PTZ cameras, thermal/infrared cameras, and mobile drone cameras
• Design detection pipelines that process video streams from multiple cameras simultaneously
• Implement intelligent camera placement strategies to optimize coverage and minimize blind spots
• Create camera health monitoring systems to detect and alert on camera failures or degraded performance
• Develop bandwidth optimization for efficient video streaming from large camera networks

• Develop AI safety enforcement systems that analyze camera feeds in real time to detect PPE compliance (helmets, vests, safety glasses)
• Build perimeter monitoring systems that detect unauthorized personnel or equipment breaches during critical operations like heavy lifts
• Create automated alert systems that log safety violations and notify supervisors immediately when non‑compliance is detected
• Develop hazard detection models that identify unsafe conditions, obstructions, or potential safety risks in construction zones
• Implement worker tracking systems using camera‑based detection for safety monitoring and emergency response
• Build tailgating detection systems that identify when multiple people enter on a single badge swipe

• Build automated progress assessment systems using computer vision to track work package completion
• Develop material classification algorithms that automatically identify installed components and materials from construction site images
• Create surveillance video analysis systems to detect and track work packages’ components automatically
• Implement activity recognition models (using YOLO,…