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FiltersDevelop 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 to optimize model performance.
We are looking for highly capable engineers who thrive in high-ownership environments and can independently build complex systems that power next-generation AI agents. This role blends deep backend engineering, full-stack problem-solving, and hands-on work with reinforcement learning environments used by leading AI research teams.
Explore and propose new ideas using your knowledge and experience in deep learning, neural networks and large foundation models in autonomous driving. Work on the entire life cycle of machine learning projects from data analysis, model experimentations to performance metrics verifications, and understand the entire workflow in great detail. Be exposed to many cross-team projects and collaborate with other teams.