Predictive Maintenance Software Engineer (MWM Digital)
Caterpillar Inc. (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 12–22 LPA
Posted 3d ago
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Job description
Structured overview of role & requirements
About This Role
- Develop predictive maintenance and Remaining Useful Life (RUL) algorithms specifically for gas engines.
- Analyze large-scale machine and time-series data to detect failure patterns and degradation mechanisms.
- Collaborate with service engineers, product experts, and external partners to translate engine failure mechanisms into software requirements and continuously improve machine learning models.
Minimum Requirements
- Degree in Data Science, Computer Science, or a related field; knowledge of gas engines and failure analysis preferred.
- Proficient in Python (pandas, NumPy), SQL, and machine learning techniques including time series analysis and model development.
- Experience working with large-scale data platforms and cloud environments such as Azure or AWS.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Strong domain knowledge in gas engines and failure analysis to translate physical failure mechanisms into analytics solutions.
- Experienced in building and validating machine learning models for predictive maintenance using large-scale time-series data.
- Able to operate effectively in cross-functional teams, including working with service engineers and external partners, indicating collaborative and interdisciplinary project engagement.