Vignesh Bhat N profile photo 1 on Tal

Vignesh Bhat N

AI Engineer Intern @EZEU | CSE Graduate

Bengaluru

< 1 year of work experience

EZEU (OPC) INDIA PVT LIMITED
Jun 20262 mosPresent

Bengaluru, Karnataka, India

LogicBrackets
Jan 20266 mosJun 2026

Bengaluru, Karnataka, India

Scalable Architecture: Designed an object-oriented, production-ready FastAPI Service-Router backend supporting asynchronous, high-concurrency multi-page document processing. SeitonDMS RAG Chatbot: Engineered an advanced Retrieval-Augmented Generation (RAG) chatbot within SeitonDMS, enabling high-accuracy contextual information querying directly from drive-uploaded documents. Document Intelligence: Integrated PP-Structure (DSR) alongside local Qwen-VL multi-modal models for zero-shot entity recognition and context-aware Key-Value extraction, achieving a 92% layout reconstruction accuracy rate. Optimization & Deployment: Containerized backend services utilizing multi-stage Docker builds and deployed the infrastructure onto Cloud GPUs, leveraging the vLLM framework and custom LRU caching to eliminate CUDA memory leaks.

Education

Bapuji Institute of Engineering & Technology, Davanagere

Bachelor of Engineering - BE, Computer Science

Bapuji Institute of Engineering & Technology, Davanagere

Science

Sir MV PU college

20202 yrs2022

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Vignesh Bhat N on Tal

Headline

AI Engineer Intern @EZEU | CSE Graduate

About

CSE Graduate and Software Engineering Intern at ezeu, specializing in the intersection of high-concurrency backend systems, cloud deployment, and machine learning applications. Current Experience: AI Engineer Intern at ezeu, focusing on scalable product development and cloud architectures. AI & Document Intelligence (Ex-LogicBrackets): Architected seiton-ai-ocr-v1, integrating multi-modal LLMs (Qwen-VL) and remote PaddleOCR-VL via vLLM to hit a 92% text reconstruction accuracy rate. Engineered a production-grade RAG chatbot within SeitonDMS for highly accurate document querying. MLOps & Cloud Infrastructure: Skilled in multi-stage Docker containerization and deploying high-throughput, low-latency API architectures directly onto Cloud GPUs. Core Tech Stack: Python, FastAPI, PyTorch, Multi-Modal LLMs, vLLM, Docker, Cloud GPUs, Vector Databases, OpenCV, Git.

Location

Bengaluru

Work experience

AI Engineer Intern at EZEU (OPC) INDIA PVT LIMITED, Jun 2026 - Present · 2 mos, Bengaluru, Karnataka, India

Software developer Intern at LogicBrackets, Jan 2026 - Jun 2026 · 6 mos, Bengaluru, Karnataka, India, Scalable Architecture: Designed an object-oriented, production-ready FastAPI Service-Router backend supporting asynchronous, high-concurrency multi-page document processing. SeitonDMS RAG Chatbot: Engineered an advanced Retrieval-Augmented Generation (RAG) chatbot within SeitonDMS, enabling high-accuracy contextual information querying directly from drive-uploaded documents. Document Intelligence: Integrated PP-Structure (DSR) alongside local Qwen-VL multi-modal models for zero-shot entity recognition and context-aware Key-Value extraction, achieving a 92% layout reconstruction accuracy rate. Optimization & Deployment: Containerized backend services utilizing multi-stage Docker builds and deployed the infrastructure onto Cloud GPUs, leveraging the vLLM framework and custom LRU caching to eliminate CUDA memory leaks.

Education

Bachelor of Engineering - BE, Computer Science, Bapuji Institute of Engineering & Technology, Davanagere

Science, Sir MV PU college

Vignesh Bhat N - AI Engineer Intern in Bengaluru | Tal