Muhammad Tayyab

TAYYAB MANAN ML Engineer & AI Developer Islamabad, Pakistan Portfolio | GitHub | LinkedIn PROFESSIONAL SUMMARY ML Engineer specializing in Computer Vision, NLP, and MLOps with 2 years of hands-on experience building production ML systems. Expert in PyTorch, TensorFlow, and LangChain for developing multi-agent AI systems serving 100+ daily users. Combining deep learning expertise with geospatial AI to deliver scalable, data-driven solutions. Currently pursuing MS in AI Engineering at COMSATS with focus on Computer Vision. PROFESSIONAL EXPERIENCE Junior AI Developer Jan 2023 - Present COINTEGRATION, Islamabad, Pakistan • Built 5+ production ML models reducing processing time by 40% • Developed multi-agent systems using LangChain and AutoGen serving 100+ daily users • Implemented automated workflows with Model Context Protocol, saving 15 hours/week • Collaborated in Agile methodology with cross-functional teams for iterative development Technologies:LangChain, OpenAISdk, AutoGen, Model Context Protocol, CrewAI ML Engineer & Geospatial AI Developer Jan 2022 - Present Freelance, Islamabad, Pakistan • Built ML-powered geospatial applications achieving R²=0.89 for water resource prediction models • Deployed Flask REST APIs serving ML models for 145 districts with real-time satellite data processing • Reduced client data processing time by 60% through ML automation and predictive analytics • Developed computer vision solutions for remote sensing applications using TensorFlow and PyTorch Technologies:Python, Scikit-learn, TensorFlow, Flask, Google Earth Engine, React, Next.js, PostgreSQL EDUCATION Bachelor of Science in Geography/GIS 2021 - 2025 University of the Punjab, Lahore, Pakistan GPA: 3.0/4.0 • Outstanding performance in GIS and Remote Sensing Masters in Artificial Intelligence Engineering 2025 - Present (Expected 2027) COMSATS, Islamabad, Pakistan • Distinguished academic record in AI Engineering and Deep Learning • Excellence in AI Engineering with focus on Computer Vision TECHNICAL SKILLS Machine Learning & AI: Deep Learning & Computer Vision: PyTorch, TensorFlow, Scikit-learn, LangChain, AutoGen, CrewAI Computer Vision, NLP, Neural Networks, Model Training, Transfer Learning MLOps & Deployment: Programming Languages: Flask APIs, Model Deployment, Docker, CI/CD, Model Context Protocol Python, JavaScript, TypeScript, SQL, R Data Science & Analysis: Geospatial AI & Remote Sensing: Pandas, NumPy, Matplotlib, Seaborn, Jupyter Google Earth Engine, QGIS, ArcGIS, PostGIS, GDAL Web Development: Databases & Cloud: React, Next.js, Node.js, Tailwind CSS, REST APIs PostgreSQL, SQLite, Firebase, Google Cloud, Vercel Tools & Methodologies: Git, Agile, OpenAI SDK, Model Optimization, A/B Testing KEY PROJECTS Wheat Yield Prediction using Machine Learning View Project GitHub ML regression model for agricultural yield forecasting using satellite imagery and climate data • Built supervised ML model achieving 0.137 t/ha prediction error on test set • Engineered features from multi-spectral satellite imagery and climate variables using Google Earth Engine • Applied cross-validation and hyperparameter tuning for optimal model performance Technologies:Scikit-learn, Python, NumPy, Pandas, Google Earth Engine, Feature Engineering TeacherRank Live Demo Comprehensive teacher rating and review platform for educational institutions • Built full-stack web application with REST APIs for real-time data synchronization • Implemented responsive design delivering seamless experience across all devices • Achieved 60% bundle size reduction through code splitting and lazy loading optimizations Technologies:React, TypeScript, Supabase, TanStack Query, Tailwind CSS, Vite WaterTrace Pakistan Live Demo GitHub Geospatial AI system analyzing 22 years of satellite data for groundwater prediction -) • Developed ML regression models achieving R²=0.89 for groundwater level predictions across 145 districts • Deployed Flask REST API serving ML models with real-time GRACE satellite data processing • Engineered feature extraction pipeline processing 22 years of geospatial time-series data Technologies:Scikit-learn, Flask, Google Earth Engine, React, Predictive Analytics, GRACE/GLDAS EV Suitability Analysis - Geospatial AI Live Demo GitHub ML-driven spatial optimization for Electric Vehicle infrastructure planning • Implemented weighted scoring algorithm processing demographic, economic, and infrastructure layers for 5 tehsils • Applied geospatial ML techniques for optimal site selection achieving 90%+ coverage target • Integrated multi-criteria decision analysis with spatial data processing pipeline Technologies:Python, Scikit-learn, QGIS, ArcGIS, OpenStreetMap, Multi-criteria Analysis CERTIFICATIONS Going Places with Spatial Analysis Sep 2024 ESRI Cartography Mar 2024 ESRI Spatial Data Science ESRI Nov 2023 Shade Equity Jun 2023 ESRI ACHIEVEMENTS Open Source Contributor Active contributor to ML, AI, and web development open source projects 2022-Present