Machine Learning Engineer, Predictive Maintenance

About Our Client:
AssetWatch operates in the industrial manufacturing sector, focusing on predictive maintenance to improve manufacturing uptime. The organization addresses the challenge of machine downtime by delivering advanced condition monitoring solutions, leveraging expertise in engineering and business leadership. They aim to build future-forward predictive maintenance technologies and are experiencing rapid growth.
About the Opportunity:
The MACHINE LEARNING ENGINEER, PREDICTIVE MAINTENANCE, will develop and implement machine learning algorithms to diagnose and predict faults in critical machinery components. This role is essential for transforming sensor and machine data into actionable insights that enhance equipment reliability and uptime. The engineer will design end-to-end ML solutions, collaborate with cross-functional teams, and ensure scalable, production-ready deployments on cloud platforms.
Responsibilities:
Extract and preprocess sensor data including vibration, temperature, electrical, image, and machine context for diagnostic feature development.
Select and apply appropriate modeling techniques such as classical ML, neural networks, deep learning, and signal-processing methods.
Train, validate, and deploy predictive maintenance models targeting various machinery faults.
Develop time-domain, frequency-domain, and contextual features relevant to fault detection.
Define end-to-end ML solution architecture, including data management, execution strategy, and cost scalability.
Build and scale distributed data and feature pipelines using Spark, Athena, and related tools.
Design data mining and annotation workflows linking engineering and data science teams.
Maintain benchmark datasets with expert-verified ground truth and model acceptance criteria.
Conduct experiments comparing new algorithms with existing methods to assess performance and reliability.
Develop maintainable ML software with thorough testing and version control.
Utilize AI-assisted coding and agentic AI tools to enhance development efficiency.
Collaborate with research and engineering teams to refine models for accuracy, explainability, and scalability.
Partner with MLOps and Data Engineering teams to ensure robust deployment and monitoring.
Requirements:
Expertise in machine learning techniques including classical ML, neural networks, CNNs, RNNs, LSTMs, and attention mechanisms.
Experience in signal processing and predictive maintenance using IIoT sensor data.
Proficiency in developing and deploying ML solutions on AWS using services like SageMaker, S3, Athena, Glue, EMR/Spark, Lambda, and related tools.
Strong software engineering skills, including data and ML engineering at scale.
Knowledge of supervised/unsupervised learning, anomaly detection, feature engineering, and LLM-based AI applications.
Hands-on experience with Python programming and production-quality ML software development.
Pay Range and Compensation Package:
The pay range and compensation package for this role will be determined based on the candidate's experience, skills, and other relevant factors.
Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.
Note:
RemoteHunter is a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.

Work arrangement
Yes