Experience time

9+ Years

Qualification

Master’s Degree

Hi, I’m Sophia Ramirez, an experienced Computer Vision Engineer with a passion for building intelligent image and video processing solutions. With 8+ years in AI and machine learning, I have worked on cutting-edge projects, including facial recognition, object detection, medical imaging analysis, and autonomous vehicle perception systems.

I specialize in deep learning models for vision-based applications, using technologies like TensorFlow, OpenCV, PyTorch, and YOLO. Whether you need an AI-powered security system, an advanced image classification tool, or real-time object detection, I have the expertise to deliver robust and efficient solutions.

I believe AI should enhance human capabilities, and I am committed to developing ethical and responsible vision-based AI applications. Let’s work together to bring your AI vision to life!

Work Experience

Senior Computer Vision Engineer
VisionTech AI 2019 - Present Developed AI-powered surveillance systems with real-time threat detection. Created custom deep learning models for medical image segmentation and diagnostics.
AI Research Scientist
Autonomous Driving Lab, Madrid 2016 - 2019 Designed object detection and tracking models for self-driving vehicles. Improved lane detection algorithms using deep learning techniques.

Education

Polytechnic University of Madrid
Master’s in Computer Science & AI 2017 - 2019 Specialized in deep learning, image processing, and AI ethics. Thesis: "Enhancing Object Recognition in Computer Vision Systems".
University of Barcelona
Bachelor’s in Electrical Engineering 2010 - 2014 Focused on signal processing, robotics, and AI applications in engineering.

Honors & awards

Best AI Vision Solution | European AI Awards
2021 Awarded for designing a real-time facial recognition security system used in smart cities.
Top 10 Women in AI | AI Tech Spain
2020 Recognized for contributions to AI-powered medical imaging solutions for early disease detection.
Outstanding Research in AI & Vision | CVPR Conference
2019 Published breakthrough research on improving the accuracy of object tracking in low-light conditions.
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