AssetWatch® · 5 days ago
Sr. Machine Learning Engineer, Predictive Maintenance
United States
Full-time
Remote
Senior Level
5+ years expAssetWatch serves global manufacturers by powering manufacturing uptime through unparalleled condition monitoring. They are seeking a Senior Machine Learning Engineer to advance predictive maintenance across industrial systems by building interpretable, production-grade machine learning solutions in collaboration with reliability engineers and data scientists.
Big DataIndustrial AutomationInternet of ThingsMachine LearningPredictive Analytics
Responsibilities
Develop interpretable machine learning models for anomaly detection, fault classification, and failure prediction using industrial sensor data
Apply time-domain and frequency-domain signal processing techniques to extract physically meaningful features from vibration signals
Embed condition monitoring and reliability domain knowledge into feature engineering and modeling decisions
Partner with reliability engineers to validate model outputs against known failure modes
Design and maintain scalable data processing pipelines for ingesting, cleaning, transforming, and validating large-scale time-series data
Build and refine interpretable machine learning models, leveraging classical methods and domain-informed approaches alongside modern techniques where appropriate
Optimize models for reliable operation in production environments, including performance monitoring, drift detection, and retraining strategies
Partner with MLOps and platform teams to integrate models into scalable, maintainable production systems
Define evaluation frameworks and metrics that reflect both predictive accuracy and practical utility in maintenance decision-making
Create dashboards and alerts that provide actionable intelligence to stakeholders
Set best practices for modeling, data processing, and experimental rigor within the team
Document system behavior and modeling decisions for internal stakeholders
Provide technical mentorship and guidance through design and code reviews
Qualification
Required
Master's or Ph.D. in Mechanical Engineering, Electrical Engineering, Computer Science, or a related field preferred. Equivalent industry experience is strongly considered
Significant experience (typically 5+ years) applying signal processing techniques to noisy sensor data
Strong experience (typically 4+ years) building and deploying machine learning models for time-series analysis, anomaly detection, or diagnostics, with a strong emphasis on interpretability
Strong experience (typically 4+ years) designing and maintaining data processing pipelines for large-scale sensor or time-series data, including data quality and validation
Significant (typically 5+ years) professional Python experience
Proven experience in vibration analysis and fault detection of industrial systems and equipment (e.g., rotating machinery such as pumps, gearboxes, or electric motors)
Experience deploying and supporting ML models in production environments
Familiarity with cloud platforms (AWS), Docker, and SQL databases
Demonstrated ability to independently drive complex technical initiatives end to end
Strong written and verbal communication skills for cross-functional collaboration
Ownership mindset aligned with a senior individual contributor role
Benefits
Competitive compensation package including stock options
Flexible work schedule
Comprehensive benefits including retirement plan match
Opportunity to make a real impact every day
Work with a dynamic and growing team
Unlimited PTO
Company
AssetWatch®
Predictive Maintenance Simplified.
51-200 employees
Funding
Current Stage
Growth StageTotal Funding
$166.14MKey Investors
Viking Global InvestorsWellington ManagementG2 Venture Partners
2025-04-30Series C· $75M
2024-02-21Series B· $38M
2022-06-27Series A· $9M
Leadership Team
Will Zell
Co-Founder & Executive Chairman
Recent News
2025-07-04
2025-05-02
Company data provided by crunchbase