Logavignesh M

Machine Learning Engineer specialising in computer vision, generative AI, and deployable ML systems. Experienced in YOLO, OpenCV, FastAPI, Docker, AWS, MLflow, and RAG pipelines with hands-on expertise in building scalable AI applications across railway inspection, forecasting, and LLM-based systems. Strong foundation in MLOps, cloud deployment, and end-to-end ML workflows.

Junior Data Scientist - 360DigiTMG

(2025-10)

• Built YOLO-v8 wagon damage detection system for railway inspection achieving ~88% mAP and reducing manual inspection effort by ~35%
• Developed real-time traffic congestion detector using OpenCV + YOLO with 91% accuracy on live CCTV feeds
• Designed power consumption forecasting system using LSTM + XGBoost reducing forecast error by 18% over ARIMA baseline
• Worked on deployment-oriented ML workflows using FastAPI, Docker, and cloud-based development practices

AI & Python Trainer - APSSDC

(2026-01 - 2026-03)

• Delivered Python & AI training to 50+ students
• Mentored teams on end-to-end ML projects from problem framing to deployment
• Conducted sessions on machine learning workflows, computer vision, and AI deployment fundamentals

AI & Data Science Intern - AiSPRY

(2025-02 - 2025-06)

• Developed electricity price forecasting model using XGBoost and feature engineering achieving 22% RMSE improvement over baseline
• Built wind turbine failure prediction classifier achieving 89% F1-score for predictive maintenance use cases

B.E. - Electrical & Electronics Engineering - Saranathan College of Engineering (2024)

Professional Program - Data Science & AI - 360DigiTMG (2024-08 - 2025-01)