Machine Learning Engineer, Predictive Maintenance
Assetwatch · United States
About this role
**Machine Learning Engineer, Predictive Maintenance** **About the Role** AssetWatch is seeking an experienced Machine Learning Engineer with specialized expertise in Signal Processing and Predictive Maintenance. You'll develop and deploy advanced ML algorithms for diagnosing and predicting machinery faults across bearings, gearboxes, shafts, motors, pumps, fans, belts, and more. **Key Responsibilities** • Extract and analyze data from IIoT sensors (accelerometers, temperature, electrical signals) and contextual machine data • Design end-to-end ML solutions from data access through production monitoring • Develop time-domain, frequency-domain, and contextual features for fault detection • Train and deploy predictive models using CNNs, RNNs, LSTMs, and attention-based architectures • Build distributed data and feature pipelines using Spark, Athena, and AWS services • Collaborate with Condition Monitoring Engineers on data annotation and labeling workflows • Establish benchmark datasets and model acceptance criteria with domain experts **Required Skills** • Classical Machine Learning, Deep Learning (CNN, RNN, LSTM, attention mechanisms) • Supervised/unsupervised learning, anomaly detection, and feature engineering • AWS expertise: SageMaker, S3, Athena, Glue, EMR/Spark, Lambda, Step Functions, Timestream, Aurora/RDS • Strong software engineering fundamentals and distributed processing experience • Signal processing and vibration analysis knowledge • Experience with LLMs and agentic AI **About AssetWatch** A global leader in manufacturing uptime, powered by world-renowned engineers and distinguished business leaders united by the mission to build the future of predictive maintenance.
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