AI/ML Engineer Intern Candidate
Pre-final-year Computer Science and Engineering student with hands-on experience in machine learning, LLM-powered applications, agentic AI workflows, and RAG pipelines.
EDC (Entrepreneurship Development Cell)
B.Tech, Computer Science & Engineering
Expected 2027
Higher Secondary (12th)
2022
Score: 88.20%
Built a voice-controlled AI agent that converts speech into actions such as code generation, file creation, and summarization. Integrated AssemblyAI for speech-to-text and Groq LLM for intent detection and response generation, with a Streamlit interface, multi-intent handling, session memory, and safe execution with user confirmation.
Built ML-based disease prediction using symptom-based NLP, implemented RAG with FAISS for medical knowledge retrieval, and added conversational memory for context-aware responses using Python, Scikit-learn, LangChain, FAISS, and LLM APIs.
Built a multi-agent RAG pipeline using LangGraph to orchestrate document retrieval, web search, and answer synthesis. Integrated FAISS and ChromaDB vector stores with OpenAI embeddings, LangChain RAG chains, tool-calling agents, and a Streamlit interface with streaming responses and source citations.
Fine-tuned a RoBERTa transformer model for binary classification of disaster-related tweets using HuggingFace Datasets and Trainer API. Achieved Rank 76/560 (Top 14%) on Kaggle with a score of 0.83573, improving from 0.79007.