Machine Learning Engineer, Predictive Maintenance
Core
Develop and deploy end-to-end ML solutions for predictive maintenance, extracting diagnostic features from IIoT sensor data to diagnose and predict faults in critical machinery components.
Role type
Senior IC machine learning engineer (predictive maintenance & signal processing)
Builds
Production ML models for anomaly detection, health assessment, and fault prognosis on AWS
Domain
Industrial IoT, Predictive Maintenance, Signal Processing
Deliverable
production ML models (via careerplan.io/jobs/4738709005-machine-learning-engineer-predictive-maintenance-at-assetwatch)
Required skills
Signal processing (FFT, Wavelet Transform, Envelope Analysis), Deep Learning (CNN, RNN, LSTM, Attention), Time-series modeling, Feature engineering, AWS MLOps, Python, Distributed data processing (Spark)
Preferred skills
LLMs and agentic AI, Classical ML algorithms, Domain expertise in mechanical/electrical engineering
Technologies
AWS (SageMaker, S3, Athena, Glue, EMR/Spark, Lambda, Timestream, Aurora/RDS, Bedrock), Python, Docker, Terraform/CloudFormation
Responsibilities
Extract and preprocess data from IIoT sensors (vibration, temperature, electrical, images) to identify fault signatures; Design end-to-end ML architectures and data pipelines; Train and deploy models for bearing, gearbox, and motor fault detection; Build distributed feature pipelines using Spark; Collaborate with domain experts to establish ground truth and model acceptance criteria; Optimize model performance and explainability in production environments.
Seniority
Senior, hands-on IC with solution-architect responsibilities