AI and machine learning engineer focused on building reliable, practical software systems that turn complex data and workflows into useful decisions.
I work across applied AI, agentic systems, machine learning, MLOps, cloud architecture, and full-stack development. My projects combine research-oriented experimentation with production-minded engineering.
- Applied Artificial Intelligence
- Agentic Systems
- Machine Learning
- MLOps
- Cloud Architecture
- Full-Stack Development
Aspect-level analysis of earnings calls and filings using a traceable multi-agent pipeline. Claims are grounded in source sentences and tracked across reporting periods.
A regime-aware reinforcement learning system for large-order execution that adapts to market conditions while balancing cost, impact, liquidity, and time constraints.
A clinical and regulatory copilot built with Snowflake Cortex AI. It combines structured healthcare data with unstructured documents and provides inline evidence citations.
An AI-powered legal intelligence platform that translates complex contracts into plain-language explanations, context-driven risk analysis, and text-grounded guidance.
An interoperable healthcare AI agent for Parkinson's disease screening from speech biomarkers, with explainable predictions, clinical summaries, and FHIR R4 output.
An AI-powered decision platform for assessing and planning small modular reactor infrastructure in Kenya, with an emphasis on structured analysis and standards alignment.
- LinkedIn: https://www.linkedin.com/in/nishant-narudkar/
- GitHub: https://github.com/nishnarudkar
- Email: nishnarudkar@gmail.com
I am open to thoughtful collaboration on applied AI, machine learning systems, developer tools, and technically rigorous product ideas.

