Open to opportunities

Alishba Riaz

@alishbariaz

Message

AI Engineer building practical deep learning and computer vision solutions.

Pakistan

Message

What I'm looking for

I’m looking for a role where I can build and deploy practical AI and computer vision solutions—especially using Python and deep learning—to solve real-world problems and keep improving from hands-on projects.

I’m an AI Engineer and Python Developer with a Computer Engineering background, focused on practical, real-world applications of deep learning and computer vision. I’ve built hands-on solutions across AI, IoT, and embedded systems, with strong skills in Python, C++, and computer vision workflows.

My standout work is a real-time drone-based forest fire detection system, where I trained and deployed a YOLOv5 model for fire and smoke detection. I also integrated GPS-based location tracking for emergency response and used a Firebase-based web portal for real-time alerts and remote monitoring—improving efficiency through automated AI-driven detection and wireless communication. I’m now looking to contribute and grow in teams that turn AI into impactful, reliable products.

Experience

Work history, roles, and key accomplishments

PTCL Intern

Pakistan Telecommunication Company Limited

Jul 2024 - Aug 2024 (1 month)

Supported networking and telecommunication operations in a professional environment, including hands-on learning of FlashFiber services and network infrastructure concepts. Assisted with technical troubleshooting, documentation, and day-to-day operational tasks while improving teamwork and communication.

Networking Telecommunications FlashFiber Services Network Infrastructure Troubleshooting Technical Documentation Network Operations Team Collaboration

Education

Degrees, certifications, and relevant coursework

Bahria University (BSEAS), Islamabad H-11/4

Bachelor of Computer Engineering, Computer Engineering

2021 - 2025

Completed a Bachelor of Computer Engineering at Bahria University (BSEAS), Islamabad. Built an AI-based forest fire detection system as a final-year project using YOLOv5 and a Raspberry Pi drone setup.