Machine Learning Engineer, Predictive Maintenance

MaintainX-posted about 1 month ago
Full-time • Mid Level
San Francisco, CA
501-1,000 employees
Publishing Industries
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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.

  • Develop and train machine learning models for fault detection and classification based on time-series sensor data; including vibration, temperature, pressure, flow etc.
  • Perform exploratory data analysis (EDA) on vibration, OT and time-series data to uncover insights and identify patterns indicative of faults or anomalies.
  • Experiment with and evaluate various algorithms, including time-series modeling, signal processing, and statistical methods, to optimize model performance.
  • Collaborate with domain experts to validate findings and ensure alignment with real-world applications.
  • Document workflows, experiments, and methodologies to ensure reproducibility and knowledge sharing across the team.
  • On-call duties
  • Strong foundational knowledge in machine learning, data science, and statistical modeling.
  • Familiarity with time-series modeling techniques and feature engineering.
  • Experience in deploying machine learning models on real-world use cases and continuously improving the model performance with feedback.
  • 3+ years of proven programming skills using standard ML tools such as Python, PyTorch, Tensorflow etc.
  • Master's or Ph.D. in Computer Science, Data Science, Mechanical Engineering, Electrical Engineering, or a related field with a focus on condition monitoring or machine learning applications.
  • Hands-on experience developing models for OT and vibration analysis, condition monitoring, and fault detection or classification.
  • Familiarity with signal processing techniques (e.g., Fourier transforms, wavelet analysis) and their application to OT and vibration data.
  • Competitive salary and meaningful equity opportunities.
  • Healthcare, dental, and vision coverage.
  • 401(k) / RRSP enrollment program.
  • Take what you need PTO.
  • A high impact Culture:
  • You'll work with Smart, Humble Optimists across the globe.
  • Meritocratic environment where ideas and outcomes are publicly celebrated.
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