I turn large language models into production systems that move the needle — building RAG pipelines, LLM-powered applications, and scalable ML/data pipelines for healthcare and enterprise.
I'm a Generative AI & AI/ML Engineer based in Boston, with experience delivering production-ready solutions across Databricks, Azure, AWS, and GCP.
Currently at Databricks, I design and deploy RAG pipelines, LLM-powered applications, and vector search solutions — building enterprise chatbots, semantic search tools, and document intelligence workflows that process 10M+ records daily.
Before that, I built AI/ML solutions for healthcare and life sciences at Verily, improving prediction accuracy by 25% through end-to-end ML pipelines and responsible AI practices.
I hold an MS in Data Analytics Engineering from Northeastern University, and I'm certified across Databricks, Azure, and Google Cloud's Gen AI and ML platforms.
Generative AI, healthcare AI, MLOps — production AI systems across regulated and enterprise environments.
Real problems across ML, analytics, and full-stack systems — built end-to-end.
CNN-based multi-class classification pipeline for brain tumor detection from MRI scans. Implemented and compared deep learning architectures (ResNet, VGG) to optimize precision and recall across 4 tumor categories.
Analyzed 50K+ patient records using SQL and Python to identify key drivers of 30-day hospital readmissions. Cohort and trend analysis surfaced patterns contributing to ~25% of readmissions, directly informing clinical intervention strategies.
EDA on 500K+ transaction records to surface fraud patterns using optimized SQL queries (joins, CTEs, window functions). Built dynamic Power BI and Tableau dashboards monitoring fraud rate, transaction trends, and risk segmentation — cutting manual review by 40%.
Power BI dashboards analyzing revenue performance across 15+ regions with DAX measures and calculated columns. Time-series analysis surfaced seasonal patterns and growth opportunities — automated recurring reporting, reducing manual effort by 50%.
Recommendation engine combining collaborative filtering and content-based approaches. Built NLP pipeline for sentiment analysis on user reviews to generate features for personalized restaurant ranking across 10K+ reviews.
End-to-end system for managing academic reports and student records with role-based access control, automated report generation, and administrative workflow management.
Full-featured e-commerce web portal with product catalog, shopping cart, order management, and customer authentication. Implemented responsive design and database-backed inventory management.
Currently seeking Generative AI Engineer and AI/ML Engineer roles in Boston or remote. Let's talk about how I can drive results on your team.
lokeshcy510@gmail.com