Headline

AI/Software Engineer | FastAPI Backends , RAG & LLM Systems | Python, LangChain, PyTorch | B.Tech AI ’26

About

Hi, I’m Vinit. I’m an AI/ML student who enjoys working with data, building practical applications, and exploring how technology can solve real problems. I like working with Python, SQL, Power BI, and I also have hands-on experience with front-end and full-stack tools like HTML, CSS, JavaScript, React, and Next.js. I’ve built projects like an AI Language Coach, a Health Insurance Cost Prediction model, and Customer Purchase Behavior Analysis, along with some web-based tools like a real-time collaborative whiteboard. I enjoy taking an idea and actually building something useful out of it — whether it’s an AI model or a web app. I’m someone who learns fast, experiments a lot, and keeps improving through practice. I genuinely enjoy solving problems, understanding how things work, and creating things that feel meaningful. Right now, I’m looking for an internship where I can apply what I’ve learned, work on real projects with a team, and grow as an engineer while contributing wherever I can.

Location

Nagpur

Work experience

Python Intern at Virtual Galaxy Infotech Ltd., Dec 2025 - May 2026 · 6 mos, Nagpur, Contributed to the backend development and AI capabilities of two production-oriented applications, building scalable APIs, document processing pipelines, and LLM-powered features while collaborating with a Senior Software Developer through code reviews and Git-based workflows. • Designed, developed, and maintained FastAPI backend services for both applications, implementing REST APIs, structured JSON responses, concurrent request handling, and multi-format file processing. • Developed a RAG-based Smart Document Assistant using Python, FAISS, and Sentence Transformers, enabling semantic question answering across PDF, Word, PowerPoint, and text documents with response times of 4–5 seconds for documents up to 100 pages. • Enhanced the assistant with AI-powered document summarization, PowerPoint generation, and image generation capabilities, producing outputs within 8–10 seconds. • Built the document ingestion and extraction pipeline for GenData, a full-stack synthetic data platform with user authentication, using the LLaVA vision-language model to transform PDFs, Word documents, PowerPoint presentations, text files, and images into structured data in approximately 20 seconds. • Implemented a LangChain-based prompt-to-schema pipeline that generated synthetic CSV and JSON datasets from natural language prompts in approximately 30 seconds. • Collaborated in a shared Git workflow using feature branches, pull requests, code reviews, and merge conflict resolution while working with senior developers.

Python Programming Intern at MotionCut, Oct 2025 - Nov 2025 · 2 mos, Remote, • Developed five Python applications during a one-month internship, including an NLP-based emotion detection system, a festival reminder application, an emoji-based mood responder, a colour psychology outfit recommender, and an auto nickname generator. • Applied Natural Language Processing (NLP) using NLTK for text preprocessing, sentiment analysis, and rule-based logic to build interactive terminal-based applications with real-time text input and output. • Implemented object-oriented programming (OOP), modular design, and efficient file handling to develop maintainable, reusable, and well-structured Python applications. • Independently debugged, tested, and refined application logic, submitting completed projects through Git repositories for review and feedback.

Education

Bachelor of Technology, Artificial Intelligence, G H Raisoni College of Engineering & Management