Research internship focused on constructing relational embeddings for semantic access to business data in relational databases, supporting semantic search, user intent understanding, and agentic AI workflows. Involves surveying and prototyping relational ML approaches, curating datasets, and evaluating methods for enterprise environments.

Design, develop, and debug software for databases and cloud services, focusing on SQL extensions and implementing data structures/algorithms to accelerate query performance. Apply Machine Learning algorithms to automate query processing tasks like result caching, partitioning, and clustering. Analyze and improve feature performance and scalability, contributing to complex, research-centric work in efficient SQL query execution. Provide technical direction and mentorship.