MS CS · 3.9 GPA · Published Researcher · AI Systems Developer Intern @ Automate365
Bridging real-time deep learning performance with production-grade LLM systems.
I started with computer vision — building real-time vehicle detection systems and publishing peer-reviewed research. That obsession with making AI work in the real world never left.
At Automate365, I've shipped production RAG pipelines, real-time transcription systems, and end-to-end LLM fine-tuning infrastructure. I don't just prototype — I deploy.
I'm an MS grad from Southeast Missouri State (3.9 GPA), originally from Hyderabad, India, now based in Irving, TX. I bring a global perspective and a bias toward building things that actually work.
I build LLM pipelines, RAG systems, and CV models that run in production — not just Jupyter notebooks. Deployed at Automate365 serving real enterprise clients.
Peer-reviewed researcher with published work in computer vision. I understand the gap between academic AI and production AI — and how to bridge it.
From model fine-tuning and RAG architecture to FastAPI backends and React dashboards — I can own the entire AI product stack end to end.
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Deploying real-time LLM pipelines, hybrid RAG systems, and AI transcription infrastructure for enterprise clients in Irving, TX.
Built ML models for text classification and computer vision pipelines achieving 87% accuracy on production datasets.
3.9 GPA. Specialization in Advanced AI, Distributed Systems, and Human-Computer Interaction.
Engineering foundation in Algorithms, Data Structures, Database Systems, and OOP.
CVR Journal of Science & Technology · Vol. 24 · June 2023 · 3rd Prize Expo2K23
Read on ResearchGate →From Distributed Fine-Tuning to Hybrid Retrieval-Augmented Inference · 19 pages · IEEE format