Senior ML Engineer — Anomaly Detection

Role overview Own the development and improvement of a machine-learning pipeline that detects anomalies in industrial sensor time series. The work combines model architecture improvements with research into ensemble tuning and feature engineering for signals such as vibration, temperature, and electrical measurements.

Responsibilities - Maintain and improve the anomaly detection pipeline from end to end. - Refine an LSTM autoencoder architecture for the detection task. - Tune how model ensemble outputs are weighted. - Research and test feature engineering approaches for industrial sensor data.

Requirements - At least 4 years of machine-learning engineering experience. - Strong experience with PyTorch or TensorFlow. - Experience with time-series anomaly detection. - Familiarity with industrial sensor signals, such as vibration, thermal, or electrical data.

Benefits and work setup - Full-time, remote role.