Demo

Predictive Maintenance Engineer

Jobvous Staffing Solutions, LLC
Houston, TX Full Time
POSTED ON 1/19/2025
AVAILABLE BEFORE 3/21/2025

As a Predictive Maintenance Engineer (AI) , you will develop and implement AI-driven 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 real-time 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 non-technical 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 Scikit-Learn.
  • Strong understanding of time-series 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 real-time data processing.
  • Familiarity with reliability engineering and root cause analysis.
  • Knowledge of SCADA systems and industrial automation protocols.
  • Strong problem-solving skills and an analytical mindset for addressing complex equipment issues.
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