We’re hiring a Machine Learning Engineer to work on predictive maintenance with sensor and time-series data. This role is for someone who likes messy real-world data, understands that models are only part of the job, and can build things that engineers can actually use. The work includes data ingestion, feature extraction, anomaly and degradation detection, model training, evaluation, and turning results into practical tools for engineering teams. What we’re looking for: * B.Sc. or M.Sc. in Computer Science, Electrical Engineering, Mechanical Engineering, Data Science, Applied Mathematics, Physics, or a related field * Strong Python and applied machine learning experience * Experience with time-series data, sensor data, signal processing, anomaly detection, forecasting, or degradation modeling * Ability to work with noisy or partially labeled data * Experience building ML workflows beyond notebooks * Clear technical communication * Flexibility to travel domestically and internationally when needed for customer meetings, field work, or integration activities Nice to have: * Experience in predictive maintenance, condition monitoring, diagnostics, prognostics, or RUL * Work with vibration, acoustic, temperature, pressure, current/voltage, or other industrial sensor data * Experience with MLOps, dashboards, APIs, or edge deployment * Background in hardware, industrial, aerospace, automotive, or defense systems
