Lead Automation Engineer, Tesla — AI-driven computer vision anomaly detection
Led computer-vision driven predictive maintenance using equipment anomaly detection with AI. This involved preparing and using labeled visual data to train or validate detection performance on industrial images/video. The work focused on identifying visual anomalies associated with equipment faults to reduce production downtime. • Computer vision anomaly detection for predictive maintenance • Training/validation dataset refinement with labeled defect/anomaly examples • Performance evaluation driving reduced assembly line downtime • Integration into operational robotics/IoT workflows