Applied Machine Learning Intern

Role Overview

• Process, clean, and structure large-scale audio/time-series datasets
• Align data with ground truth and validate data quality
• Develop and evaluate modeling approaches for predictive maintenance
• Design and run structured experiments, analyze results, and document findings
• Improve data workflows and evaluation pipelines

Requirements

• Pursuing a degree in Computer Science, Electrical Engineering, Data Science, or related field
• Strong Python skills
• Experience with ML frameworks (PyTorch, TensorFlow, or scikit-learn)
• Comfortable working with real-world, noisy datasets
• Strong analytical and documentation skills
• MS or PhD candidate in a relevant technical field (preferred)
• Experience with audio processing or time-series feature engineering (preferred)
• Familiarity with anomaly detection (preferred)
• Exposure to signal processing concepts (FFT, spectrograms, filtering) (preferred)
• Experience designing and evaluating structured ML experiments (preferred)
• Self-driven and comfortable operating in an early-stage environment (preferred)

Tech Stack

• Python
• PyTorch
• Scikit-Learn
• Tensorflow