I'm a Data Science & AI Engineer focused on building real-world intelligent systems, not just models.
- 🎯 Preparing for Data Science / AI roles
- 🎙️ Building voice agents (Twilio + ElevenLabs)
- 🧠 Working on LLMs, RAG pipelines & system design
- 📊 Strong interest in financial ML & applied AI
- ⚡ I care about latency, scalability, and real deployment
Languages
Python · C++ · SQL
AI / ML
PyTorch · Scikit-learn · Pandas · NumPy · Hugging Face
Backend & Systems
FastAPI · Flask · REST APIs · Docker
Infra & Tools
Linux · Git · AWS (basics)
Focus Areas
LLMs · Voice AI · RAG · Financial Systems
- Built a multi-agent system based on Model Context Protocol (MCP) for financial workflows
- Designed specialized agents for lead qualification, data extraction, validation, and decision-making
- Implemented context sharing and coordination between agents for consistent outputs
- Integrated LLMs with structured pipelines to reduce hallucination and improve reliability
- Optimized for real-time execution, low latency, and modular scalability
- Converts natural language queries into executable SQL for financial datasets
- Handles complex multi-constraint queries (filters, ratios, temporal conditions)
- Built a constraint extraction + query generation pipeline
- Ensures logical correctness, execution success, and low-latency responses
- Developed a RAG-based chatbot for institutional and financial data access
- Pipeline: document ingestion → embedding → retrieval → LLM generation
- Supports context-aware Q&A over large unstructured datasets
- Designed for scalable deployment and efficient retrieval performance
