ML Engineer · Applied Scientist · Data Engineer · Full-Stack Systems Architect
Building intelligent, scalable, production-grade systems
across machine learning, data, and modern web platforms.
Portfolio · LinkedIn · Email · GitHub · Facebook
One of my original photographs — visual thinking beyond code.
- Agentic AI & LLM Systems — RAG, tool-using agents, evaluation, safety & reasoning
- Applied ML Research — model behavior, benchmarks, alignment, failure analysis
- MLOps & Data Engineering — scalable pipelines, deployment, monitoring
- Full-Stack Systems — distributed APIs, real-time platforms, end-to-end ownership
-
Quench++ — GitHub
Benchmarking contextual reasoning gaps between Indic and non-Indic languages in LLMs, extending QUENCH with multilingual evaluation, translation stress-tests, and robustness metrics. -
HorusLLM — GitHub
Research-focused LLM framework for model introspection, reasoning behavior analysis, and controlled evaluation of agentic decision pathways.
-
MineMEETS — GitHub
End-to-end ML pipeline system focusing on data ingestion, feature workflows, experiment tracking, and production deployment patterns. -
Flourish — GitHub
Scalable ML infrastructure emphasizing reproducibility, monitoring, and lifecycle management of learning systems.
-
Entropy — GitHub
AI-powered academic and community platform integrating RAG, intelligent agents, discussion forums, and collaborative research workflows. -
DreamDOT — GitHub
Creator-first social marketplace enabling monetization of digital art and writing through subscriptions, paywalls, analytics, and hybrid social–commerce design.
Languages: Python · TypeScript · Go · C++ · JavaScript
ML: PyTorch · Transformers · RAG · MLflow · NumPy · Pandas
Backend: FastAPI · Node.js · GraphQL · Microservices
Frontend: Next.js · React · Tailwind CSS
Data & Infra: PostgreSQL · MongoDB · Docker · Cloud Platforms
From research to production — I ship systems that reason, adapt, and scale.