About the job
Join MaintainX, the premier mobile-first Asset and Work Intelligence platform tailored for industrial and frontline settings. Our cutting-edge, IoT-driven, cloud-based solution optimizes maintenance, safety, and operational efficiency for physical assets and facilities.
We empower over 12,000 organizations, including industry leaders like Duracell, Univar Solutions, Titan America, McDonald’s, Brenntag, Cintas, Xylem, and Shell, to achieve unparalleled operational excellence and reliability.
Following a successful $150 million Series D funding round led by Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures, and Ridge Ventures, MaintainX has raised a total of $254 million, positioning the company with a valuation of $2.5 billion.
As we embark on our next growth phase, we are heavily investing in AI/ML, LLMs, and Industrial IoT to revolutionize frontline operations—anticipating failures before they occur, automating workflows, and integrating intelligence into every asset and process.
Key Responsibilities:
- Design and train machine learning models for fault detection and classification using time-series sensor data, including vibration, temperature, pressure, and flow.
- Conduct exploratory data analysis (EDA) on various data types to extract insights and identify fault patterns.
- Experiment with and assess different algorithms, including time-series modeling, signal processing, and statistical methods, to enhance model performance.
- Work alongside domain experts to validate results and ensure practical application alignment.
- Document processes, experiments, and methodologies for reproducibility and knowledge sharing within the team.
- Participate in on-call duties as required.

