TotalEnergies is a multi-energy company that produces and markets energy on a global scale: oil and biofuels, natural gas and green gas, renewables, and electricity. Our 105,000 employees are committed to making energy more affordable, cleaner, reliable, and accessible to as many people as possible. Present in over 130 countries, TotalEnergies places sustainable development in all its dimensions at the heart of its projects and operations to contribute to the well-being of people TotalEnergies has been present in Italy for over 70 years. Its activities span the entire energy sector value chain, operating through various companies located throughout the country.

At TotalEnergies, we invest in people and developing their talent. We consider safety, health, and respect for human rights our priorities. Hence, we are committed to ensuring a safe, inclusive, and innovative professional environment where collaboration and listening are part of our model. We place people at the center, ensuring a balance between work and private life, promoting flexibility and well-being, company welfare, and meal vouchers, within a culture that celebrates success and shares moments of conviviality.

TotalEnergies will review the received applications, giving care and attention to the values of Diversity and Inclusion.

The Predictive Maintenance Engineer is responsible for developing and implementing predictive maintenance strategies aimed at improving plant reliability and reducing unplanned downtime. The main goal is to anticipate potential failures through continuous data analysis, enabling timely and targeted interventions that deliver significant benefits in operational efficiency, cost reduction, and minimal environmental impact.

 This role involves analyzing data from PLCs (Programmable Logic Controllers), smart sensors, IoT devices, laboratory tests, and CMMS systems to detect early signs of equipment failure and initiate corrective actions before breakdowns occur. The activity relies on real-time condition data and leverages machine learning algorithms to perform condition monitoring and prognostic analysis without disrupting plant operations.

Main responsibilities:

• Develop predictive models for various equipment and plant units based on criticality assessments (e.g., gas chromatography in oil-filled transformers, process conditions, tg delta on electrical insulation, mechanical vibration and mode analysis, etc.);
• Collect, monitor, and analyze operational and IoT data to identify potential or early-stage failure modes;
• Design and update predictive maintenance programs based on data analysis and machine learning techniques;
• Collaborate with technical teams to integrate new sensors and monitoring technologies, and to plan scheduled maintenance interventions;
• Define and monitor key performance indicators (KPIs) to assess equipment performance (reliability and availability);
• Plan and coordinate preventive and corrective maintenance activities;
• Work closely with the production team to manage operating hours planning.

• Master’s degree in Mechanical, Process, or Electrical Engineering
• Minimum of 2 years’ experience in roles related to predictive modelling
• In-depth knowledge of monitoring systems and sensor technologies
• Strong skills in data analysis and trend interpretation
• Fluency in both English and Italian