Develop AI solution to analyze vibration data from rotating equipment to identify and diagnose issues
Gather, clean, and preprocess vibration data for AI algorithms
Extract features (frequency domain, time-domain statistics, time-frequency representations)
Experiment, train, and fine-tune machine learning and deep learning models for fault classification and severity assessment
Deploy trained models into user-facing interfaces and integrate with maintenance/monitoring systems
Continuously evaluate model performance and refine for accuracy and efficiency
Collaborate with subject matter experts and technology teams to implement solutions and improve equipment reliability
Requirements
Currently enrolled in an accredited college/university
Pursuing a degree in Data Science, Computer Science, Engineering, or related technical field
Legal authorization to work in the United States; sponsorship will not be provided
Junior or Senior year
Preferred: previous experience with data science and machine learning techniques
Preferred: knowledge of signal processing and vibration analysis
Preferred: experience in software development
Skills: data acquisition, data cleaning and preprocessing, feature engineering, model development (ML/DL), model deployment and integration, performance evaluation
Collaborative teamwork with subject matter experts and technology teams
Note: Individuals with temporary visas (E, F-1 including OPT/CPT, H-1, H-2, L-1, B, J, TN) are not eligible