I'm a developer who specializes in... from... Give an introduction about yourself, who are you, what are your most important skills and what differentiates you from other devs. This is the first thing clients will see. They are often interested in sector experience and knowledge, so please mention it. --- Junior AI Engineer Local Firm, Lahore (Jan 2025 – Present) Worked on computer vision projects including Welding Defect Detection and Dimension Compliance System using YOLO and OpenCV. Deployed AI solutions with FastAPI, Flask, and Docker for real-time industrial inspection. AI Researcher (FYP & Publication) University Project, Faisalabad (Sep 2024 – Dec 2024) Developed an AI-Powered Smart Farming System integrating IoT sensors, ML models, and an LLM chatbot. Published in IEEE Xplore (2025) under AI in Agriculture. AI Developer (Freelance Projects) Remote (2023 – 2025) Built and deployed multiple end-to-end ML/DL projects, including: Potato Leaf Disease Detection (CNN, 98% accuracy) Coating Defect Detection (deep learning for cracks, bubbles, scratches) Voice Emotion Detection (CNN + Librosa, 7,000+ clips) Resume Classification System (NLP + ML, 93% accuracy) LLM-based Chatbots and RAG applications for real-world use cases…

Asad Gulshair

I'm a developer who specializes in... from... Give an introduction about yourself, who are you, what are your most important skills and what differentiates you from other devs. This is the first thing clients will see. They are often interested in sector experience and knowledge, so please mention it. --- Junior AI Engineer Local Firm, Lahore (Jan 2025 – Present) Worked on computer vision projects including Welding Defect Detection and Dimension Compliance System using YOLO and OpenCV. Deployed AI solutions with FastAPI, Flask, and Docker for real-time industrial inspection. AI Researcher (FYP & Publication) University Project, Faisalabad (Sep 2024 – Dec 2024) Developed an AI-Powered Smart Farming System integrating IoT sensors, ML models, and an LLM chatbot. Published in IEEE Xplore (2025) under AI in Agriculture. AI Developer (Freelance Projects) Remote (2023 – 2025) Built and deployed multiple end-to-end ML/DL projects, including: Potato Leaf Disease Detection (CNN, 98% accuracy) Coating Defect Detection (deep learning for cracks, bubbles, scratches) Voice Emotion Detection (CNN + Librosa, 7,000+ clips) Resume Classification System (NLP + ML, 93% accuracy) LLM-based Chatbots and RAG applications for real-world use cases…

Available to hire

I’m a developer who specializes in… from…

Give an introduction about yourself, who are you, what are your most important skills and what differentiates you from other devs. This is the first thing clients will see. They are often interested in sector experience and knowledge, so please mention it.

Junior AI Engineer
Local Firm, Lahore (Jan 2025 – Present)

Worked on computer vision projects including Welding Defect Detection and Dimension Compliance System using YOLO and OpenCV.

Deployed AI solutions with FastAPI, Flask, and Docker for real-time industrial inspection.

AI Researcher (FYP & Publication)
University Project, Faisalabad (Sep 2024 – Dec 2024)

Developed an AI-Powered Smart Farming System integrating IoT sensors, ML models, and an LLM chatbot.

Published in IEEE Xplore (2025) under AI in Agriculture.

AI Developer (Freelance Projects)
Remote (2023 – 2025)

Built and deployed multiple end-to-end ML/DL projects, including:

Potato Leaf Disease Detection (CNN, 98% accuracy)

Coating Defect Detection (deep learning for cracks, bubbles, scratches)

Voice Emotion Detection (CNN + Librosa, 7,000+ clips)

Resume Classification System (NLP + ML, 93% accuracy)

LLM-based Chatbots and RAG applications for real-world use cases

See more

Skills

Experience Level

Python
Expert
Docker
Expert
PyTorch
Expert
SQL
Expert
TensorFlow
Expert
GitHub
Expert
Keras
Expert
MySQL
Expert
R
Expert
ETL
Expert
PostgreSQL
Expert
MongoDB
Expert
Power BI
Expert
Tableau
Expert
Kubernetes
Intermediate
See more

Language

English
Fluent

Work Experience

AI Engineer at Evolution Software
June 30, 2025 - October 2, 2025
Gained hands-on experience in model development, evaluation, and deployment on AI research projects.
Junior Artificial Intelligence Engineer at RICI Pakistan Pvt Ltd
July 1, 2025 - Present
Leading development of AI-powered inspection systems for industrial applications; built YOLO and CNN-based models for welding and coating defect detection; designed dimension-compliance system using OpenCV + ARUCO markers; designed annotation pipelines and collaborated with cross-functional teams on data prep, model training, deployment, and reporting.
Co-Author at IEEE Xplore
June 30, 2025 - Present
AI-Driven Smart Agriculture: An Integrated Approach for Soil Analysis, Irrigation, and Crop-Fertilizer Recommendations.
Lead AI Inspection Systems Engineer at RCI Pakistan Pvt Ltd
July 1, 2025 - Present
Led development of AI-powered inspection systems for industrial applications. Implemented Welding Defect Detection using YOLO and CNN-based models to detect porosity, spatter, lack of fusion, undercut, and good/bad welds from high-resolution images. Designed AI pipeline for detecting coating issues such as cracks, bubbles, scratches, and surface irregularities. Developed Dimension Compliance System using OpenCV + ARUCO markers for real-world scaling. Designed annotation pipeline to build high-quality data sets for training and deployed models into web and mobile apps for real-time inspection. Collaborated with cross-functional teams, contributing to dataset preparation, model training, deployment, and reporting.
AI Intern at Evolution Software
July 1, 2025 - October 3, 2025
Collaborated on AI research projects involving model development, evaluation, and deployment. Developed a deep learning–based Voice Emotion Detection System using MFCC and spectral features; achieved 75%+ accuracy by tuning CNN and LSTM architectures on 10,000+ audio samples. Built a Drug Recommendation System using patient data and supervised learning techniques to suggest personalized medicines and treatments. Contributed to end-to-end ML pipelines including data cleaning, feature engineering, model optimization, and testing.

Education

BS in Data Science at Government College University, Faisalabad
January 1, 2021 - January 1, 2025
Bachelor of Science in Data Science at Government College University, Faisalabad
January 1, 2021 - January 1, 2025
Bachelor of Science in Data Science at Government College University Faisalabad
January 1, 2021 - January 1, 2025

Qualifications

Add your qualifications or awards here.

Industry Experience

Agriculture & Mining, Manufacturing, Software & Internet, Education, Healthcare, Computers & Electronics, Professional Services
    uniE621 AI-Powered Smart Farming System
    The AI-Powered Smart Farming System is an end-to-end solution designed to help farmers increase yield, reduce costs, and make data-driven decisions. By combining IoT sensors, Machine Learning, and an AI chatbot, the system provides real-time insights on soil health, irrigation schedules, crop recommendations, and fertilizer usage. Features Real-Time Soil Monitoring – IoT sensors track pH, NPK, temperature, and moisture. Crop Recommendation Engine – ML model suggests the best crop to grow based on soil & climate conditions. Irrigation & Fertilizer Guidance – AI predicts optimal irrigation schedules and fertilizer usage. AI Chatbot Integration – Farmers interact with a chatbot to ask queries about crops, irrigation, and farming techniques. Dashboard & Alerts – Easy-to-use dashboard with real-time updates and smart alerts via web app. Tech Stack AI/ML: Python, Scikit-learn, TensorFlow IoT: Real-time sensors for pH, moisture, and nutrients APIs: FastAPI & Flask for deployment Deployment: Docker for scalable deployment Visualization: Power BI / Python Dash for dashboards Chatbot: LLM-based intelligent assistant ✔️ Helps farmers maximize yield and minimize input cost ✔️ Provides predictive analytics for smarter decisions ✔️ Fully scalable and customizable for different regions/crops ✔️ Combines AI + IoT + Chatbot → unique end-to-end digital farming solution Academic & Industry Validation Published in IEEE Xplore (2025) under AI in Agriculture. Tested with real-world IoT datasets. Currently being enhanced with LLM-based advisory chatbot for improved farmer interaction. datascience machinelearning AI EndtoendAIsolution Data AI Deeplearning…
    paper AI Engineer

    Developed an AI-powered computer vision system to ensure industrial parts meet exact dimensional standards. Using OpenCV + ArUco markers, the system measures inner and outer diameters of disks and flanges with real-world scaling. This project automates manual inspection, reduces human error, and ensures compliance with international standards.

    Tech Stack: Python, OpenCV, ArUco Markers, Computer Vision

    Role: Designed dataset pipeline, implemented detection & measurement logic, and deployed as a real-time inspection tool.