AI/ML Engineer - RAG & ML Automation

SHIVUNAPURAM PRAVEEN

AI/ML Engineer AI Automation

Hyderabad, India +91-770******* *******************@*****.*** LinkedIn GitHub Portfolio

PROFESSIONAL SUMMARY

AI/ML Engineer with a B.Tech in Electronics and Communication Engineering and hands on experience in Python, Machine Learning, Generative AI, and SQL. Built a Retrieval Augmented Generation (RAG) chatbot using LangChain, FAISS and LLMs. Developed and evaluated supervised ML models with Scikit learn during an AI/ML internship. Skilled in data preprocessing, exploratory data analysis, vector embeddings, and building end to end LLM powered applications. Immediate joiner and open to relocation.

TECHNICAL SKILLS

Machine Learning: Supervised Learning (Logistic Regression, Decision Tree, Random Forest, KNN, SVM), Clustering, Dimensionality Reduction, Cross Validation, Scikit learn

Deep Learning: ANN, CNN, RNN, LSTM

Generative AI & NLP: LLMs, RAG, LangChain, LangGraph, Fine Tuning, Prompt Engineering, Prompt Templates, Tokenization, Vector Embeddings, FAISS, NLP

Data Analysis: Pandas, NumPy, Matplotlib, Exploratory Data Analysis (EDA), Data Preprocessing, Feature Engineering Languages & Databases: Python, SQL, PostgreSQL

Tools & Platforms: Streamlit, Google Colab, Git, GitHub, VS Code, Jupyter Notebook PROFESSIONAL EXPERIENCE

AI/ML Engineer Intern Datavalley Jan 2026 Present

• Collected, cleaned and preprocessed datasets using Python, Pandas and NumPy to prepare data for model training.

• Performed exploratory data analysis (EDA) to identify patterns, detect outliers and extract actionable insights.

• Built and evaluated supervised machine learning models using Scikit learn (Logistic Regression, Decision Trees, Random Forest, KNN, SVM).

• Used Git and GitHub for version control and collaborative project development. KEY PROJECTS

YouTube AI Transcript Extractor (RAG Chatbot)

Tech Stack: Python, RAG, LLMs, LangChain, FAISS, YouTube Transcript API, Streamlit

• Built an AI powered chatbot that lets users ask natural language questions about any YouTube video and receive accurate, context aware answers.

• Developed the full RAG pipeline: extracted video transcripts, preprocessed and chunked text, generated vector embeddings and stored them in a FAISS vector database.

• Implemented retrieval of the most relevant transcript segments and used an LLM through LangChain to generate answers with corresponding video timestamps.

EDUCATION

Bachelor of Technology Electronics and Communication Engineering 2024 Kommuri Pratap Reddy Institute of Technology, Ghatkesar CGPA: 6.2 / 10 Intermediate (MPC) 2020

Sri Venkateshwara Junior College, Sangareddy 80% Secondary School Certificate (SSC) 2018

Zilla Parishath High School, Shivampet CGPA: 7.7 / 10

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