Remote ML Engineer: Predictive Maintenance & Industrial AI

ProducePay; United States; Remote; USD 151,000 - 175,000; Full time

Benefits offered by this job

Stock options

Flexible work schedule

Comprehensive benefits

Job summary

AssetWatch seeks an experienced Machine Learning Engineer with strong signal processing and predictive maintenance expertise. You will extract features from IIoT sensors, build end‑to‑end ML solutions on AWS, and collaborate with MLOps to deploy scalable fault-diagnosis models.

The role emphasizes deep learning, time-series analysis, and practical software engineering to deliver production‑ready systems across distributed assets.

Qualifications

• Advanced degree in Mechanical/Electrical Engineering or Computer Science/Engineering.
• Strong background in predictive maintenance and signal processing techniques.
• Proven experience building production ML solutions on AWS.

Responsibilities

• Extract and preprocess sensor data from vibration, temperature, electrical signals, and context data.
• Develop, validate, and deploy ML models for fault diagnosis and prognosis.
• Design end‑to‑end ML pipelines including data access, feature computation, training, inference, and monitoring.
• Build scalable data pipelines using Spark/EMR or SageMaker Processing.
• Collaborate with MLOps and Data Engineering to productionize solutions.

Skills

Signal processing

ML model development

Python

AWS SageMaker

Distributed data processing

Education

MS/PhD in a related field

Tools

SageMaker

Spark/EMR

S3/Athena

Job description

AssetWatch seeks an experienced Machine Learning Engineer with strong signal processing and predictive maintenance expertise. You will extract features from IIoT sensors, build end‑to‑end ML solutions on AWS, and collaborate with MLOps to deploy scalable fault-diagnosis models.

The role emphasizes deep learning, time-series analysis, and practical software engineering to deliver production‑ready systems across distributed assets.