I'm Srikanth Reddy Nandireddy — an ML Engineer and Data Scientist who builds systems that actually ship.

Currently completing my M.S. in Data Science & AI at the University of Central Missouri (4.0 GPA, Graduate Student Achievement Award 2025–2026), I specialize in production-grade ML: RAG pipelines, multimodal deep learning, MLOps on AWS, and real-time inference APIs. My work doesn't stop at Jupyter notebooks — it ends with deployable, benchmarked systems.

My recent projects include a semantic RAG pipeline over 120 arXiv ML papers achieving MRR 1.000 with BGE embeddings, a real-time fraud detection system with ROC-AUC 1.000 deployed via CI/CD on AWS EC2, a cross-modal emotion recognition model fusing BERT, Wav2Vec2, and ViT on the MELD dataset, and a COVID-19 mortality forecasting dashboard comparing SARIMAX, Prophet, and XGBoost with near-zero overfitting (Holdout MAE ≈ CV MAE).

On the competitive side: CodeChef Global Rank #1, National Finalist in IICC (top 1% of 100K+ participants), 5★ HackerRank in DSA, and a 255-day GeeksforGeeks streak — not for show, but because the discipline carries into production code.

I write about applied ML, RAG systems, MLOps, and the gap between model accuracy and real-world deployment. If you've ever shipped a model only to watch it silently degrade in production, you're in the right place.

📌 Currently open to full-time roles in Data Science, ML Engineering, and Applied AI.

🌐 Portfolio: srikanthreddynandireddy.me