// 01 · AI/ML Research
AI Evangelist
I actively champion responsible, practical AI adoption. My work spans RAG system design, LLM fine-tuning with QLoRA, agentic workflow orchestration with LangGraph, and production ML infrastructure. I've guided teams through AI adoption journeys — from initial proof-of-concept to production rollout.
My approach is empirical: design experiments, measure outcomes, iterate. I'm skeptical of AI hype and focused on deployable, explainable systems with real business impact.
// 02 · Leadership
Technology Leader
As a technology leader, I've driven the adoption of production-ready ML/AI solutions across the full product lifecycle — from architecture and prototyping through deployment, governance, and optimization. My leadership style centers on empowering multidisciplinary teams and delivering measurable results.
I've mentored engineers, championed cloud-native architectures, and navigated the organizational complexity of introducing AI into established engineering cultures.
// 03 · Research
Researcher
My research-driven approach is rooted in continuous experimentation. I design, train, and optimize language models and generative AI systems with a focus on production constraints — inference cost, latency, reliability, and explainability.
I contribute to open-source projects and share findings on this blog. Research is most valuable when it closes the loop between academic advancement and practical deployment.
// 04 · Education
IIT Roorkee
Completed the AI/ML program at IIT Roorkee via the Scaler program — one of India's premier technical institutions. The program covered machine learning fundamentals, deep learning architectures, NLP, and production ML systems.
Beyond formal education, I maintain an active learning practice: reading papers, building systems, and writing about what I learn.
