AI CoE Manager Machine Vision & Vision Inspection

Role Overview: You will lead the design and delivery of real-time vision inspection solutions for defect detection, segmentation, OCR, anomaly detection, and measurement systems. You will also build and mentor a strong AI/ML engineering team and establish robust AI and MLOps practices for production environments. Key Responsibilities: - Architect and optimize real-time vision inspection systems using OpenCV and C++ - Develop hybrid pipelines combining classical image processing and deep learning - Work with high-speed cameras, optics, lighting, and industrial interfaces (GigE, CameraLink, Line/Area Scan) - Build AI models using CNNs, U-Net, YOLO, OCR, anomaly detection - Optimize edge AI performance using TensorRT, ONNX, CUDA, OpenVINO - Establish dataset governance, model versioning, CI/CD, and monitoring pipelines - Collaborate with mechanical, electrical, and automation teams for system-level integration - Lead code reviews, design reviews, and technical standards across the team Qualification Required: - Strong C++ (C++11/14/17) and OpenCV experience - Machine Vision / Vision Inspection / Image Segmentation - Experience in pharmaceutical, packaging, or manufacturing inspection systems - Understanding of cameras, optics, lighting, and imaging architecture - Hands-on with PyTorch/TensorFlow for computer vision models - Experience in performance optimization and real-time processing Additional Details: We are looking for professionals with deep expertise in Machine Vision, OpenCV, C++, and Industrial Imaging Systems who have built and deployed production-grade inspection solutions under real-world constraints such as latency, accuracy, lighting variation, and hardware limitations. Professionals from machine vision, industrial automation, pharma inspection, or optical inspection environments are ideal for this role. If you have built real-time vision inspection systems in pharma or manufacturing and are ready to lead an AI CoE, share your profile or connect for more details. Role Overview: You will lead the design and delivery of real-time vision inspection solutions for defect detection, segmentation, OCR, anomaly detection, and measurement systems. You will also build and mentor a strong AI/ML engineering team and establish robust AI and MLOps practices for production environments. Key Responsibilities: - Architect and optimize real-time vision inspection systems using OpenCV and C++ - Develop hybrid pipelines combining classical image processing and deep learning - Work with high-speed cameras, optics, lighting, and industrial interfaces (GigE, CameraLink, Line/Area Scan) - Build AI models using CNNs, U-Net, YOLO, OCR, anomaly detection - Optimize edge AI performance using TensorRT, ONNX, CUDA, OpenVINO - Establish dataset governance, model versioning, CI/CD, and monitoring pipelines - Collaborate with mechanical, electrical, and automation teams for system-level integration - Lead code reviews, design reviews, and technical standards across the team Qualification Required: - Strong C++ (C++11/14/17) and OpenCV experience - Machine Vision / Vision Inspection / Image Segmentation - Experience in pharmaceutical, packaging, or manufacturing inspection systems - Understanding of cameras, optics, lighting, and imaging architecture - Hands-on with PyTorch/TensorFlow for computer vision models - Experience in performance optimization and real-time processing Additional Details: We are looking for professionals with deep expertise in Machine Vision, OpenCV, C++, and Industrial Imaging Systems who have built and deployed production-grade inspection solutions under real-world constraints such as latency, accuracy, lighting variation, and hardware limitations. Professionals from machine vision, industrial automation, pharma inspection, or optical inspection environments are ideal for this role. If you have built real-time vision inspection systems in pharma or manufacturing and are ready to lead an AI CoE, share your profile or connect for more details.