Sr. Machine Learning Engineer, Predictive Maintenance
AssetWatch, Inc.
About this role
A Senior Machine Learning Engineer at AssetWatch advances predictive maintenance for industrial systems by building interpretable, production-grade machine learning solutions. The role emphasizes deep domain expertise in vibration analysis and condition monitoring to improve asset uptime and reliability. The position is a senior individual contributor role that helps set technical standards and works with cross-functional teams to deliver robust industrial solutions.
Skills
Qualifications
About AssetWatch, Inc.
assetwatch.comAssetWatch is an industrial condition‑monitoring platform that helps manufacturers protect assets and prevent unplanned downtime. Combining sensors, data collection, and AI-driven analytics, it turns raw signals into prescriptive insights and recommended actions to build a reliability program that scales across plants. The platform is designed for plant operators and maintenance teams who need faster detection, prioritized remediation, and measurable reductions in failures and downtime.
Recent company news
AssetWatch Secures $75M in Series C Funding
Apr 30, 2025
AssetWatch secures US$75M Series C funding round
May 1, 2025
Westerville startup's predictive maintenance tech for manufacturers nets substantial VC investment
May 1, 2025
Wilson Sonsini Advises AssetWatch on $75 Million Series C Financing
May 1, 2025
AssetWatch® Raises Series B Funding Round to Accelerate Innovation in Predictive Maintenance
Mar 16, 2025
About AssetWatch, Inc.
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Leadership Team
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
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View leadership team, funding history,
and employee contacts for AssetWatch, Inc..
Salary
$86k – $118k
per year
More jobs at AssetWatch, Inc.
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