🚀 AI & Data Science Aspirant | Machine Learning Engineer | LLMs • RAG • Agentic AI • MLOps | Data-Driven Problem Solver | Building Real-World AI Systems that Solve Practical Problems

I’m a Computer Science & Engineering student at Sir M Visvesvaraya Institute of Technology (CGPA: 9.1/10) with a strong interest in Artificial Intelligence, Machine Learning, and Generative AI.

I enjoy building practical AI systems that go beyond theory — from LLM fine-tuning and RAG pipelines to AI agents and deployed ML applications. My focus is on turning data and models into solutions that work in real-world scenarios.

Currently, I’m deepening my expertise in AI deployment, MLOps fundamentals, Agentic AI, and LLM-based systems using tools like MLflow, DVC pipeline, KubeFlow, Airflow, CI/CD, LangChain, LangGraph, LangSmith and CrewAI.

My core interests include Data Science, Machine Learning, NLP, Neural Networks, LLMs, and Retrieval-Augmented Generation (RAG). I rely on strong foundations in EDA, Mathematics statistics, and model optimization to build AI systems that are accurate, reliable, and interpretable.

I believe in continuous learning and hands-on experimentation as the best path to mastering AI.

Languages

Frameworks & Libraries

Developer Tools

• 🧩 Retrieval-Augmented Generation (RAG) — Designing RAG pipelines with embeddings and FAISS to enable context-aware LLM responses
• 🧠 Large Language Models (LLMs) — Fine-tuning and applying LLMs for domain-specific tasks using LoRA/QLoRA and Hugging Face
• 🤖 Agentic AI Systems — Building AI agents using LangChain, LangGraph, and CrewAI for multi-step reasoning and task automation
• 💬 NLP & Text Processing — Tokenization, lemmatization, TF-IDF, N-grams, and NER for extracting insights from text data
• 🔍 Model Fine-Tuning & Optimization — Adapting pre-trained models, hyperparameter tuning, and evaluation for performance improvement
• 📊 EDA & Feature Engineering — Data exploration, visualization, outlier handling, and feature creation for robust modeling
• 📈 Statistical Analysis — Probability, distributions, and hypothesis testing for data validation and interpretation
• 🧮 Machine Learning — Regression, classification, clustering, and model evaluation across real-world datasets
• 🧰 AI Deployment & MLOps Basics — Model serialization, API integration, and deploying ML/LLM apps using Flask, Streamlit, and cloud platforms

• 📚 Data Structures — Arrays, Strings, Linked Lists, Stacks, Queues, Trees, Graphs, Heaps, HashMaps
• ⚙️ Algorithms — Sorting, Searching, Recursion, Greedy, Divide & Conquer, Dynamic Programming,
• 🧠 Object-Oriented Programming (OOP) — Encapsulation, Inheritance, Polymorphism, Abstraction
• 🧮 Complexity Analysis — Time & Space Complexity, Big-O Notation, Optimization Techniques
• 🧰 Coding Platforms — LeetCode, HackerRank, GeeksforGeeks

LLM + RAG + GNN powered Legal AI

✔ Fine-tuned Phi-3 Mini (3.8B) using LoRA on a 76K legal dataset
✔ RAG pipeline with FAISS semantic retrieval
✔ Neo4j knowledge graph + GNN for case relationships
✔ vLLM serverless deployment with APIs
✔ Hugging Face model hosting

LangChain + LangGraph Agent System

✔ Automated JD parsing & resume ranking
✔ Multi-factor semantic scoring
✔ Streamlit dashboard with fairness checks
✔ Cloud deployment for real-time use

✔ Built a chat-based AI assistant that recommends low-pollution travel routes using real-time AQI data
✔ Integrated Google Maps API, AQI APIs, and Flask backend for dynamic route analysis
✔ Provided transport suggestions and health advisories based on air quality and route conditions

✔ Developed a LightGBM regression model achieving 93%+ prediction accuracy
✔ Incorporated weather and calendar-based features for context-aware demand forecasting
✔ Deployed as a Flask web application with real-time prediction capability

✔ Performed data cleaning, preprocessing, and imputation on loan datasets
✔ Conducted EDA and visualization to analyze borrower behavior patterns
✔ Identified key factors influencing loan defaults to support risk assessment decisions

• 🥇 5-Day AI Agents Intensive Course – Kaggle & Google
• 🥇 5-Day Gen AI Intensive Course – Kaggle & Google
• 🎓 Artificial Intelligence Intern – Skill Intern Pvt Ltd
• 💬 DSA Mentor – CSOC 2024, TechHub Community
• 🧩 Active participant in hackathons and AI innovation initiatives

📧 Email: manjusuresh197490@gmail.com
🔗 LinkedIn: linkedin.com/in/manjunath-suresh-82a41b261
💻 GitHub: github.com/Code10x-letscodewithManju
🤗 Hugging Face: huggingface.co/ManjunathCode10x
📊 Kaggle: kaggle.com/manjunathsuresh2003

⭐ “Continuous learning fuels continuous improvement — and I code to create impact.”