MAIN DUTIES AND RESPONSIBILITIES:

• Collect data from condition monitoring sensors and other sources, then analyze and interpret the data to identify potential equipment issues and predict maintenance requirements;
• Generate detailed reports and maintenance recommendations based on predictive maintenance findings;
• Machine Learning Algorithm Development: Drive the development and deployment of machine learning algorithms that leverage IIoT data for predictive maintenance, enabling more accurate and proactive failure predictions.
• Administrate all condition monitoring sensors and network infrastructure including servers and adaptors, ensuring sensors are calibrated and maintained, and data communication networks are secure and reliable.
• Utilize various predictive maintenance technologies such as (AI, GenAI, IIoT, ML) and traditional vibration analysis, thermography, ultrasound, and oil analysis to monitor the health of critical plant equipment.

REQUIREMENTS:

• Bachelor's degree in Engineering or a related field;
• Excellent English proficiency, both written and spoken;
• Excellent problem-solving skills and ability to work independently and within a team;
• Experience in Machine learning development and predictive maintenance or condition-based monitoring;
• Proficiency in using predictive maintenance technologies and data analysis tools;
• Certification in maintenance reliability or predictive maintenance (advantage);
• Experience with SAP (advantage).

TO APPLY: Please send us your CV and a copy of your university diploma by 01.12.2024 and if you meet our criteria, we will contact you to invite you to an interview. CONTACT: Konstantina Petrova (HR Specialist) - mobile: +359 885 70 08 66. NOTE: Only candidates who have submitted the full set of required documents will be eligible to continue in the selection process. Collected documents will be processed in full confidentiality in accordance with the requirements of GDPR.