AI Engineer (in progress) building real-world intelligent systems
Focused on ML pipelines, prediction systems, and LLM-powered applications
Strong foundation in DSA + applied machine learning

• Building end-to-end ML systems (data → model → API)
• Developing LLM-powered applications (RAG, embeddings, vector DBs)
• Solving real-world problems using AI (security, prediction, automation)

• Built an ML pipeline to predict Air Quality Index using pollutant data
• Performed feature engineering, model comparison, and cross-validation
• Identified variance issues across folds due to temporal data shifts
• Tech: Python, Scikit-learn, Pandas

• Browser-based system to detect phishing URLs using heuristic + blacklist approach
• Integrated OpenPhish dataset for high-confidence detection
• Achieved strong accuracy with real-world applicable features
• Tech: JavaScript, ML heuristics

• Designing an intelligent assistant using RAG + Knowledge Graph
• Focus: structured reasoning + context-aware responses
• Working with embeddings, vector databases, and prompt engineering

Languages:
Python, JavaScript, C++

AI / ML:
Scikit-learn, Pandas, NumPy, NLP basics

Backend / Systems:
FastAPI, REST APIs

LLM / AI Tools:
Embeddings, Vector Databases (learning), Prompt Engineering

Other Tools:
Git, GitHub, Postman

• Wrote Doctests for Dijkstra's algorithm
• Fixed multiple UI/UX issues and improved UI components
• Improved database of a web application.

• Strong problem-solving skills (DSA + algorithms)
• Ability to build end-to-end systems, not just models
• Focus on real-world applications, not just theory

• Email: [email protected]
• LinkedIn: https://www.linkedin.com/in/pranav-siddhartha-tamada

Always open to collaborating on impactful AI projects