Ramakrishna Mamidi

Architected and deployed scalable AI/ML solutions on AWS and Azure, built end-to-end data pipelines and CI/CD for model training, and delivered predictive maintenance and anomaly-detection systems across manufacturing, finance, and retail clients.

Refactored backend for AutoUW offering, implemented document parsers and image-processing for 10,000+ documents across 30 formats, and developed a GENAI POC for automated document interaction and summarization.

Optimized SQL ETL for price-volume-mix analysis reducing runtime from 4 hours to 1, and built segmentation and KNN clustering models to extract insights from stitched datasets.

Built semantic search with transformers and FAISS, improved text-generation accuracy from 67% to 79%, developed ETL pipelines on Azure Databricks and marketing/sales optimization models that increased lead conversion by 75% in 6 months.

Led an R&D team of four to deliver RPA solutions for banking, auto, and pharma clients, developed an NLP/text-mining engine for RxGenie, and migrated e-commerce platforms using AWS Lambda automation.

Served as MIS lead performing data extraction, cleansing, visualization and automation to improve reporting efficiency, and built VBA and C# tools for research and data quality analysis.

Grade: 3.75 GPA

Completed a Bachelor of Technology in Electrical and Electronics Engineering with a strong academic record and relevant coursework in engineering and computing.