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
- Contributed to open-source projects through Hacktoberfest
- Submitted multiple pull requests across different repositories
- Improved existing codebases by fixing bugs and enhancing functionality
- Gained experience in collaborative development, version control, and code review processes
- 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: pranavtamada.official@gmail.com
- LinkedIn: https://www.linkedin.com/in/pranav-siddhartha-tamada
Always open to collaborating on impactful AI projects



