Remote ML Engineer - Predictive Maintenance & Diagnostics

AssetWatch, Inc.; United States; Remote; USD 151,000 - 175,000; Full time

Benefits offered by this job

Stock options

Retirement plan match

Remote-first culture

Unlimited PTO

Career growth

Job summary

AssetWatch, Inc. is seeking a Machine Learning Engineer focused on predictive maintenance and signal processing. You will develop algorithms to diagnose, predict, and monitor machinery health using IIoT sensor data, images, and metadata, building end-to-end ML solutions on AWS.

The role demands experience with CNNs/RNNs/LSTMs, attention mechanisms, and scalable ML pipelines, with close collaboration with MLOps and Data Engineering teams to ensure production readiness and cost efficiency.

Qualifications

• Master's or Ph.D. in Mechanical Engineering, Electrical Engineering, Computer Science/Engineering, or a related field.
• Proven experience in Predictive Maintenance and Condition Monitoring with signal processing techniques.
• Strong foundations in ML and model development including supervised/unsupervised learning, CNNs, RNNs/LSTMs, and attention mechanisms.
• Hands-on experience architecting and delivering production ML solutions on AWS (SageMaker, S3, Athena, Glue, EMR, Lambda, Step Functions, ECS).
• Experience with distributed data processing (Spark/PySpark) and large time-series datasets.
• Proficiency in Python and building modular, testable production code; CI/CD for ML environments.

Responsibilities

• Extract, preprocess, and analyze data from multiple sensor sources to identify diagnostic features and fault signatures.
• Determine appropriate modeling techniques, including classical ML, neural networks, and time-series methods.
• Train, validate, and deploy predictive maintenance models to detect and predict machinery faults.
• Develop and evaluate time-domain, frequency-domain, and contextual features for fault analysis.
• Act as solution architect for ML initiatives: end-to-end data contracts, storage layouts, and cost/scalability tradeoffs.
• Build and scale distributed data pipelines over large historical sensor datasets using Spark and Parquet-based layouts.
• Design experiments and compare new algorithms against existing production methods across machines and conditions.
• Develop robust, modular ML software in Python with tests, CI/CD, and reproducible workflows.
• Collaborate with MLOps/Data Engineering to ensure production deployment and monitoring in AWS.

Skills

Signal Processing

Predictive Maintenance

Time-series Modeling

Python

Distributed ML

Education

Master's or Ph.D. in Mechanical / Electrical / CS

Tools

SageMaker

Spark

Athena

ECS/Fargate

S3

Job description

AssetWatch, Inc. is seeking a Machine Learning Engineer focused on predictive maintenance and signal processing. You will develop algorithms to diagnose, predict, and monitor machinery health using IIoT sensor data, images, and metadata, building end-to-end ML solutions on AWS.

The role demands experience with CNNs/RNNs/LSTMs, attention mechanisms, and scalable ML pipelines, with close collaboration with MLOps and Data Engineering teams to ensure production readiness and cost efficiency.