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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.
Job Responsibility:
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
Requirements:
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
Nice to have:
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
What we offer:
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