Dishakshi Shinde

I’m a final-year CSE student focused on building production-grade AI systems and backend APIs. I bring hands-on experience with RESTful API design, relational database engineering, and end-to-end ML pipelines—from data cleaning to model selection.

In internships, I built 8+ RESTful API endpoints and implemented JWT-based authentication with role-based access control. I also designed and deployed APIs for internal data-exchange workflows, eliminating 3 recurring bottlenecks, and built automated data-collection pipelines using Firecrawl.

I enjoy performance and reliability work: I optimized slow queries (execution time cut from ~4s to ~0.8s) by adding composite indexes and rewriting nested sub-queries. My projects reflect this mindset—like an agentic travel planner that chains LLM reasoning with real-time web-scraped data, reducing average query execution time by 35%.

From real estate prediction to health-tech analytics, I’ve combined structured data engineering with ML experimentation (e.g., feature engineering and model evaluation). I’m actively exploring LLM-based agentic workflows and real-time inference systems, aiming to deliver secure, scalable experiences with clean, well-structured APIs.