Principal Vision Developer

The Nuclear Company-posted 23 days ago

Full-time • Senior

Hybrid • Seattle, WA

11-50 employees

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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.

Computer Vision System Development
Camera Systems Integration & Detection
Safety & Compliance Monitoring
Progress Tracking & Quality Control
Machine Learning & AI Model Development
Integration & Deployment
Robotic Vision & Automation
Advanced Vision Applications
Technical Leadership & Innovation

Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or related field (Master's or Ph.D. preferred)
12+ years of experience in computer vision, machine learning, or AI development
5+ years in a senior or lead role with demonstrated technical leadership
Experience in industrial, construction, or manufacturing applications preferred
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
Strong experience with camera integration, configuration, and management
Knowledge of camera protocols (ONVIF, RTSP, HTTP streaming, GigE Vision)
Understanding of camera specifications (resolution, frame rate, dynamic range, sensor types)
Experience with various camera types (IP cameras, thermal cameras, PTZ cameras, industrial cameras)
Proficiency in multi-camera synchronization and calibration
Knowledge of video compression standards (H.264, H.265, MJPEG)
Understanding of network bandwidth requirements and optimization for video streaming
Familiarity with camera mounting, positioning, and field-of-view calculations
Expert knowledge of deep learning frameworks (PyTorch, TensorFlow, Keras)
Strong experience with CNNs, vision transformers, and modern architectures (ResNet, YOLO, Mask R-CNN, ViT)
Proficiency in object detection, semantic segmentation, and instance segmentation
Experience with model training, hyperparameter tuning, and optimization
Knowledge of transfer learning, fine-tuning, and domain adaptation
Understanding of data augmentation, regularization, and model evaluation techniques
Expert programming skills in Python (primary) and C++ (for performance-critical code)
Proficiency in GPU programming (CUDA, cuDNN) for accelerated inference
Experience with MLOps tools (MLflow, Weights & Biases, TensorBoard)
Knowledge of containerization (Docker, Kubernetes) for model deployment
Familiarity with cloud platforms (AWS SageMaker, Azure ML, Google Cloud AI)
Understanding of REST APIs, microservices, and distributed systems
Experience with large-scale image datasets and data annotation tools (Labelbox, CVAT, Label Studio)
Knowledge of data pipelines, ETL processes, and data versioning (DVC)
Proficiency in database systems for image metadata and results storage
Understanding of edge computing and model optimization (TensorRT, ONNX, quantization)
Familiarity with streaming video processing and real-time analytics
Experience with video management systems (VMS) and network video recorders (NVR)
Understanding of construction processes, quality control, and safety requirements
Knowledge of BIM models, CAD data, and 3D visualization
Familiarity with industrial inspection and automated monitoring systems
Experience with regulatory compliance and documentation requirements
Understanding of nuclear facility operations and safety protocols (preferred)
Knowledge of security systems and surveillance best practices
Excellent problem-solving abilities with creative approach to vision challenges
Strong communication skills to explain complex AI concepts to diverse stakeholders
Project management experience delivering production vision systems
Ability to work collaboratively across engineering, operations, security, and safety teams
Strategic thinking with focus on scalable, maintainable solutions
Attention to detail for accuracy-critical applications

Ph.D. in Computer Vision, Machine Learning, or related field
Publications in top-tier computer vision conferences (CVPR, ICCV, ECCV)
Experience in nuclear, energy, or highly regulated industries
Background in robotics, autonomous systems, or industrial automation
Knowledge of 3D sensors (LiDAR, depth cameras, structured light)
Experience with multi-camera systems and camera networks
Familiarity with real-time operating systems and embedded vision
Certifications in AI/ML (AWS ML Specialty, Google ML Engineer, etc.)
Contributions to open-source computer vision projects
Experience with video surveillance systems and security analytics
Knowledge of lighting design for optimal camera performance

Competitive compensation packages
401k with company match
Medical, dental, vision plans
Generous vacation policy, plus holidays

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