• Develop and train machine learning models for fault detection and classification based on time-series sensor data; including vibration, temperature, pressure, flow etc. • Perform exploratory data analysis (EDA) on vibration, OT and time-series data to uncover insights and identify patterns indicative of faults or anomalies. • Experiment with and evaluate various algorithms, including time-series modeling, signal processing, and statistical methods, to optimize model performance. • Collaborate with domain experts to validate findings and ensure alignment with real-world applications. • Document workflows, experiments, and methodologies to ensure reproducibility and knowledge sharing across the team. • On-call duties