Senior Applied Machine Learning Engineer, Asset Intelligence

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About this role

Senior Applied Machine Learning Engineer, Asset Intelligence San Francisco (Remote) MaintainX is the world's leading mobile-first Asset and Work Intelligence platform for industrial and frontline environments. We're a modern, IoT-enabled, cloud-based solution that powers maintenance, safety, and operations on physical equipment and facilities. We help 12,000+ organizations-including Duracell, Univar Solutions, Titan America, McDonald's, Brenntag, Cintas, Xylem, and Shell-achieve operational excellence and reliability at scale. Following our $150 million Series D led by Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures, and Ridge Ventures, MaintainX has raised a total of $254 million, valuing the company at $2.5 billion. As we enter our next phase of growth, we're investing deeply in AI/ML, LLMs, and Industrial IoT to transform how frontline teams operate-predicting failures before they happen, automating workflows, and embedding intelligence into every asset and procedure. The Role We are seeking a highly skilled and motivated Senior Applied Machine Learning Engineer to guide the technical direction and architecture of our Predictive Maintenance and Asset Intelligence initiatives. You'll combine deep ML expertise with strong software engineering and leadership skills-mentoring engineers, scaling systems, and driving the roadmap for AI-enabled maintenance intelligence across thousands of industrial sites. This role sits at the intersection of ML architecture, IoT data systems, and product impact, shaping the foundation for MaintainX's predictive and generative AI strategy. What you'll do: - Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products. - Architect end-to-end ML systems-from data ingestion and feature engineering to model training, deployment,

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