Ai Developer

Developed production-ready image search engine processing 18,000+ images using ResNet-50 architecture for feature extraction, enabling real-time similarity matching with 95% accuracy. Engineered robust data pipeline scraping and processing 400K+ images from major e-commerce platforms, building custom CNN model for real-time attribute extraction achieving 83% accuracy across 50+ features. Implemented tree-based image retrieval algorithms, reducing inference time by 8X while maintaining recommendation accuracy, enabling sub-second response times. Developed k-means clustering model for fabric and style differentiation using advanced distance metrics, improving product categorization accuracy by 25%. Awarded Best Use of AI Technology at IREC Awards 2024 for developing innovative AI solutions that transformed e-commerce product discovery.

Led comprehensive testing initiative for Project Phoebe, writing extensive unit tests that increased code coverage from 30% to 81% across 7,000+ lines of code, significantly improving system reliability. Collaborated with product, engineering, and business teams on critical financial data analytics and reporting systems, reducing report generation time by 50%.