Predictive Maintenance Engineer
Predictive Maintenance Engineer
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1 Vacancy
Job Description
As a Predictive Maintenance Engineer (AI) you will develop and implement AIdriven predictive maintenance models to monitor and optimize equipment health and performance. This role requires a deep understanding of machine learning data analytics and industrial systems allowing you to predict and prevent failures before they occur thus ensuring operational efficiency and reducing downtime.
Responsibilities
- Design develop and deploy predictive maintenance algorithms using machine learning and AI techniques to identify potential equipment failures.
- Collect clean and preprocess data from IoT devices sensors and industrial equipment to create accurate predictive models.
- Analyze historical data to discover failure patterns trends and triggers improving accuracy and reliability in predictions.
- Work closely with engineering teams to implement predictive maintenance solutions across production and manufacturing environments.
- Continuously monitor and refine predictive models based on realtime data enhancing their performance and adapting to new insights.
- Collaborate with stakeholders to understand equipment performance requirements and identify opportunities for improving uptime and productivity.
- Document processes and findings creating reports and presentations to communicate maintenance insights to technical and nontechnical teams.
Required Qualifications
- Education: Bachelors degree in Engineering Data Science Computer Science or a related field (Masters or Ph.D. preferred).
- Experience: 3 years of experience in predictive maintenance data science or AI preferably in industrial or manufacturing settings.
- Technical Skills:
- Proficiency in Python R or MATLAB for data analysis and model development.
- Familiarity with machine learning frameworks such as TensorFlow PyTorch or ScikitLearn.
- Strong understanding of timeseries analysis anomaly detection and statistical modeling.
- Experience with industrial IoT platforms sensor data and data visualization tools (e.g. Tableau Power BI).
- Knowledge of cloud platforms (e.g. AWS Azure) for deploying and scaling predictive models.
- Domain Knowledge: Understanding of industrial equipment manufacturing processes and maintenance procedures.
Preferred Skills
- Experience with edge computing and realtime data processing.
- Familiarity with reliability engineering and root cause analysis.
- Knowledge of SCADA systems and industrial automation protocols.
- Strong problemsolving skills and an analytical mindset for addressing complex equipment issues.
Employment Type
Full Time
