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Wajahat Ali B. AI, Machine Learning and LLM Platforms

My name is Wajahat Ali B. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: Python, Machine Learning, Natural Language Processing, Large Language Model, Multimodal Large Language Model, etc.. I hold a degree in Master of Computer Science (MSCS). Some of the notable projects I've worked on include: Multi-Domain Object Detection and Tracking Projects, Underwater Object Identification using Deep Learning, Real-Time Object Detection using YOLOv5, Deep Learning-Based Body Pose Recognition System, Smart Real-Time Human Detection and Recognition, etc.. I am based in Bagh, Pakistan. I've successfully completed 7 projects while developing at Softaims.

I specialize in architecting and developing scalable, distributed systems that handle high demands and complex information flows. My focus is on building fault-tolerant infrastructure using modern cloud practices and modular patterns. I excel at diagnosing and resolving intricate concurrency and scaling issues across large platforms.

Collaboration is central to my success; I enjoy working with fellow technical experts and product managers to define clear technical roadmaps. This structured approach allows the team at Softaims to consistently deliver high-availability solutions that can easily adapt to exponential growth.

I maintain a proactive approach to security and performance, treating them as integral components of the design process, not as afterthoughts. My ultimate goal is to build the foundational technology that powers client success and innovation.

Main technologies

  • AI, Machine Learning and LLM Platforms

    3 years

  • Python

    1 Year

  • Machine Learning

    1 Year

  • Natural Language Processing

    2 Years

Additional skills

Direct hire

Potentially possible

Previous Company

MTech Solutions

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Experience Highlights

Multi-Domain Object Detection and Tracking Projects

Led the development of three advanced computer vision systems: (1) Real-time object detection using YOLOv5 for general-purpose recognition, (2) Underwater object identification using CNNs tailored for

Underwater Object Identification using Deep Learning

Built a deep learning model to detect and classify underwater objects in murky and low-light conditions. Leveraged data augmentation and pre-trained CNN models to improve performance. The system aids

Real-Time Object Detection using YOLOv5

Developed a real-time object detection system using YOLOv5 to accurately identify and locate multiple objects in video feeds. Focused on training with custom datasets and optimizing the model for fast

Deep Learning-Based Body Pose Recognition System

These two projects focuses on real-time human body pose estimation using advanced AI and deep learning techniques. By leveraging models like OpenPose or MediaPipe, the system accurately detects key bo

Smart Real-Time Human Detection and Recognition

This project leverages advanced computer vision and AI techniques to identify and track people in real-time from live video streams. Using deep learning models like YOLO/ResNet, the system ensures hig

Education

  • NUST

    Master of Computer Science (MSCS) in Artificial Intelligence

    2024-01-01-2026-01-01

Languages

  • English (Fluent)
  • Urdu (Fluent)