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Mahmut Veli, Computer Vision Engineer, Deep Learning, AI, Qt, C++, QML, Python, Pytorch on www.freelancermap.com

Pytorch on www.freelancermap.com

San Francisco, CARemote OKFull-time$140k – $220k / year

About this role

Mahmut Veli, Computer Vision Engineer, Deep Learning, AI, Qt, C++, QML, Python, Pytorch on www.freelancermap.com Computer Vision Engineer, Deep Learning, AI, Qt, C++, QML, Python, Pytorch Istanbul, Turkey Only remote Master of Engineering (MEng), Control systems engineering Istanbul, Turkey Only remote Master of Engineering (MEng), Control systems engineering Profile attachments MahmutVeli_Projects_Vision_HMIs.pdf About me With 12+ years of experience in Computer Vision and Software development, my expertise spans Deep Learning and AI-driven (DL/ML) solutions for Machine Vision Systems, Qt/C++/QML & Python development, and full-stack application design, delivering scalable and efficient production-grade systems. Artificial Intelligence Computer Vision C++ (Programming Language) CMake Supervisory Control and Data Acquisition (SCADA) Python (Programming Language) OpenCV Qt Modeling Language (QML) Qt (Software) AWS CLI PyTorch Keras Scikit Learn Hello, With 12+ years of experience in Computer Vision and software development, I have worked with global companies to build high-performance applications. My expertise spans modern C++ development, AI-driven solutions, and full-stack application design, delivering scalable and efficient software. ✅ Computer Vision & AI Proficient in OpenCV, ONNX Runtime, TensorRT, OpenVINO, MVTec HALCON, YOLO, RF-DETR, DeepSORT, PaddleOCR, Tesseract OCR, EasyOCR, DINO, GroundingDINO, CLIP, SAM, Hugging Face Transformers, Milvus, Albumentations, Scikit-learn, and AWS SageMaker. I develop AI-driven applications for object detection, classification, segmentation, tracking, features extraction, image retrieval, and anomaly detection. I also work with ONNX to optimize AI models for deployment. ✅ 3D Point Clouds Processing Processing Point Clouds using PCL (C++) and Open3D (Python). Train custom models on spatial unorganized point clouds for 3D object detection and segmentation using PointNet++ and RandLaNet. Develop

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