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Create a website for my resume using orange, dark gray, and white theme: Sovit Ranjan Rath sovitrath5@gmail.com — +91 9439678558 — DebuggerCafe.com — GitHub — LinkedIn Professional Summary Generative AI & Computer Vision Engineer with 2+ years of experience building multimodal AI systems (LLMs/VLMs, RAG) and 3 years experience in Deep Learning based computer vision. Authored 340+ technical articles and courses bridging cutting-edge research with real-world applications. Passionate about deploying generative AI to accelerate creative workflows in gaming. Core Skills • Generative AI: LLMs (Phi, Whisper), Vision-Language Models (CLIP, SAM), RAG Systems, Image Generation • Frameworks: PyTorch, TensorFlow, Hugging Face, LangChain, ONNX, Streamlit/Gradio • Technical Domains: Multimodal AI, Computer Vision, Model Optimization, Agentic Workflows • Deployment: Local AI systems, scalable pipelines, real-time applications • Collaboration: Cross-functional leadership (Product, Engineering, Research) Professional Experience Indegene — Lead SWE (GenAI & LLMs) — Apr 2025 – Present • Slashed API costs by 98.2% by optimizing in-memory context from 2M to 36k tokens. Architected an agentic workflow enabling code execution and dynamic UI visualization (graphs/charts) for healthcare solutions and built tools for real-time data interaction using generative AI. • Built MCP (Model Context Protocol) server for Excel reasoning integrated with GPT and Claude APIs, deployed internally across the organization. Converted existing FastAPI server archi- tecture to MCP server for enhanced AI agent capabilities. OpenCV University — Technical Lead, AI Education — Feb 2021 – Apr 2025 • Led development of 4+ courses on deep learning and computer vision, used by developers and engineers globally. Engineered multimodal RAG pipelines (text/vision/audio) and demo apps for CLIP-based semantic search and Whisper transcription. Collaborated with product/marketing teams to align AI education with industry needs. DebuggerCafe.com — Author & Consultant — 2020 – Present • Published 340+ tutorials on generative AI, RAG, and computer vision with reproducible code. Designed quantized CV models for low-compute environments and real-time video analysis pipelines. Key Projects • Multimodal AI Library: Integrated CLIP, SAM, and Molmo for NLP-guided image segmentation. • Local RAG System: Built a Python-based Q&A tool using Sentence Transformers + Phi and custom vector search. • Vision Transformers Library: Created pip-installable ViT/Swin/DETR implementations. • Object Detection Toolkit: Developed modular training scripts for Faster RCNN (PyTorch). Education B.Tech, Information Technology — 2016-2020 — CGPA: 8.61/10Technical Presence • 340+ Articles on LLMs, VLMs, generative AI, and deep learning (DebuggerCafe.com). • Open Source: GitHub repositories for RAG, vision transformers, and AI tools. - Initial Deployment
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