Senior Computer Vision

About

Equip Claude with the expertise of a senior computer vision engineer to build, optimize, and deploy advanced AI systems. This skill provides domain-specific guidance for the entire vision lifecycle, from training custom models using YOLO and SAM to architecting high-throughput inference pipelines and implementing MLOps best practices. It is particularly useful for teams needing to scale vision applications, ensure real-time performance targets, and follow enterprise-grade security and compliance standards in distributed environments.

Key Features

• Architectural patterns for scalable, real-time inference and high-throughput video processing
• Integration guidance for major frameworks including PyTorch, TensorFlow, OpenCV, and vision transformers
• Production-ready MLOps workflows covering model monitoring, drift detection, and automated retraining
• Senior-level technical leadership strategies for system design, security, and performance tuning
• 310 GitHub stars
• End-to-end vision model lifecycle management from training to deployment optimization

Use Cases

• Developing and fine-tuning custom object detection or image segmentation models for specialized datasets
• Scaling AI infrastructure using Kubernetes, Docker, and distributed computing frameworks
• Architecting low-latency video analysis pipelines for real-time production environments