Research Associate at University of York

Spearheaded an international AI research initiative in computer vision and automated defect detection, improving defect identification rates by 27% in industrial prototypes through deep learning deployment. Engineered and refined CNN-based image classification and segmentation models, improving accuracy by 23% and reducing false positives by 18% using high-resolution imaging datasets. Designed and scaled a Python-based training/validation/testing pipeline across 10,000+ samples, reducing manual processing time by 40%. Conducted predictive analytics on multi-sensor time-series data to forecast component failure with 92% precision, enabling earlier intervention. Utilised an HPC cluster for distributed training, cutting runtimes by 60% and speeding experimentation. Streamlined preprocessing workflows with reusable modules, improving consistency and efficiency by 30%. Produced technical documentation, workflow diagrams, and process flowcharts, reducing ramp-up time for new researchers by 5

Software Developer at Tata Consultancy Services Ltd

Engineered Python-based backend services to accelerate workflows and data processing, increasing throughput by 35% and reducing batch latency. Designed and tuned advanced SQL queries using joins, window functions, and subqueries for reporting across 50M+ records, reducing query response times by 40%. Built robust ETL pipelines integrating REST APIs and CSV/XML flat files with relational databases to automate daily ingestion for 8+ enterprise applications. Developed and maintained RESTful APIs using Flask and FastAPI to integrate with 5+ cross-functional teams, reducing service downtime by 30%. Containerised backend systems with Docker for faster deployment and improved scalability in Linux environments. Implemented RBAC and logging for improved security and compliance with internal audit standards. Participated in Agile delivery through sprint planning, code reviews, and client demos, contributing to 15% faster project delivery.