I am a Software Development Engineer with a strong focus on AI and Machine Learning systems. I enjoy building scalable, production-ready applications that combine solid software engineering principles with data-driven intelligence.
My experience spans backend development, ML model design, NLP systems, and end-to-end AI pipelines through internships, research-driven projects, and real-world deployments.
| Programming & Backend | Machine Learning & AI | Data & Distributed Systems | CS Fundamentals |
|---|---|---|---|
| Python, C, SQL | Scikit-learn, XGBoost | Pandas, NumPy | Data Structures & Algorithms |
| FastAPI, Flask | TensorFlow, Keras | Apache Spark, Hadoop | Operating Systems |
| REST APIs, Git | NLP, Transformers | Redis | Computer Networks |
| PostgreSQL, MongoDB, Docker | LSTMs, GNN, Time Series Analysis | Linux | System Design, Distributed Systems |
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Real-Time Stock Market Trend Prediction and Smart Investment Allocation
LSTM-based system for trend classification and confidence-driven portfolio allocation
https://github.com/latchumi-raman/real-time-stock-trend-prediction -
Content Generation LLM
End-to-end language model pipeline combining traditional NLP and deep learning methods
https://github.com/latchumi-raman/content-generation-llm -
AI-Powered Career Assistant (CareerPilot)
Resume enhancement, job matching, and interview preparation using NLP and LLM APIs
https://github.com/latchumi-raman/OverflowedStack_1_CareerPilot -
AI Evaluation Suite (Internship – IIT Madras)
Full-stack evaluation platform for black-box testing of LLMs and AI systems
- AI Evaluation Suite Intern — Wadhwani School of Data Science & AI, IIT Madras
- Autonomous Driving Systems Intern — NIT Trichy
- AI-Powered Healthcare Intern — Infosys Springboard
- 3rd Place – Agrithon 2.0 (National-Level Hackathon, DBT Sponsored)
Built an end-to-end computer vision pipeline for sugarcane disease detection using multi-modal CNN models.