Researcher in Artificial Intelligence applied to Predictive Maintenance

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Researcher in Artificial Intelligence applied to Predictive Maintenance, Aviles

Client:

Location: Aviles, Spain

Job Category:

Other

EU work permit required:

Yes

Job Views:

1

Posted:

19.04.2025

Expiry Date:

03.06.2025

Job Description:

ArcelorMittal is the world’s largest steel producer. We use the most innovative technology to create the steels tomorrow’s world will be made of. Every day over 190,000 of our talented people, located in over 60 countries, push the boundaries of digitalization and use advanced technology to create a world that is stronger, faster and smarter. To help make this possible, they know they can depend on the support and training that a company of our scope and scale can provide.

The Digitalization team is part of the ArcelorMittal R&D Spain Lab and it provides worldwide service within the ArcelorMittal Group. We are a team of more than 50 researchers working on Digitalization and Artificial Intelligence applied to a wide range of activities (manufacturing, product development, environmental, decarbonization, supply chain, commercial, planning & scheduling, etc.). This multidisciplinary team covers a wide variety of scientific and business areas with highly qualified researchers (engineers, mathematicians, physicists, etc.), all of them with deep expertise in combining Science and Business know-how. Their enthusiasm and commitment create an incredible working atmosphere for those that want to enjoy the experience of researching and applying breakthrough ideas in the real industrial world.

We are looking for a researcher with knowledge of Artificial Intelligence applied to predictive maintenance. Currently, the main research lines go through developing intelligent solutions based on analysis of vibrations, currents, voltages or temperatures. Thus, the development of algorithms using Machine Learning techniques is mandatory. Also, basic knowledge of electrical machines, motors, pumps, drives, etc. and/or demonstrable experience in maintenance works in industrial facilities would be desirable. Finally, knowledge and experience in signal processing (sensors, data acquisition systems, signal conditioning and signal processing) is also highly desirable.

Your role

• Develop models for anomaly detection, time series forecasting, remaining useful life estimation and/or signal processing problems.
• Support the deployment of those models in production.
• Manage projects related to the application of Predictive Maintenance in our industrial facilities.
• Analyze deeply each case to identify the best technical approach to be applied (signals, sensors, modeling approach, etc.)
• Ensure proper and fluid communication with the maintenance teams in our plants.
• Promote new innovative practices to enhance the operations of our Predictive Maintenance lab.
• Stay up-to-date with emerging trends and technologies in Predictive Maintenance.

Your profile
Requirements:

• Master degree in quantitative field: Mathematics, Physics, Engineering, Computer Science, Operations Research or other related field.
• 2+ years experience as data scientist.
• Experience with Condition Monitoring/Predictive Maintenance projects would be desirable.
• Experience and solid background in applying Machine Learning/Deep Learning in anomaly detection, time series forecasting, remaining useful life and/or signal processing problems.
• Knowledge of probabilistic models, stochastic processes and generative models desirable.
• Proficiency in at least one object-oriented programming language (desirable Python).
• Experience with data wrangling.
• Desirable experience with Git, Docker, SQL and NoSQL databases, data visualization, Spark and/or cloud computing platforms (Azure, Databricks, AWS, Google Cloud).
• Initiative, adaptability, analytical competencies, results-oriented, teamwork and project management skills.
• Advanced English and Spanish levels.

Desirable knowledge:

• Familiarity with big data technologies like Spark, Kafka, and NoSQL databases, emphasizing their integration into secure DevOps pipelines.
• Exposure to the Data Mesh architecture and modern data stack, enhancing the integration of security practices within data-centric environments.
• Understanding of data warehousing concepts and experience with ETL/ELT tools, ensuring data integrity and security throughout the process.
• Understanding of machine learning concepts and techniques, enabling collaboration with data science teams on secure machine learning deployments.
• Familiarity with data visualization and dashboarding tools such as Grafana, Tableau and Power BI, facilitating data presentation and analysis.
• Knowledge of monitoring and logging tools, aiding in the proactive identification and remediation of issues within the infrastructure.

What we will offer

Integration in a highly qualified group of researchers with the possibility of pursuing a career in the scientific area in the R&D organization of the world's largest steel producer.

According to ArcelorMittal Global R&D values:
- You agree to comply with health and safety rules.
- You are respectful, transparent, honest and empathetic in your relationships. You honor your word and your commitments to others.
- You agree to behave consistently with the highest level of integrity.
- You strive to question your practices with high expectations of yourself and others, striving for a high level of quality and reliability in everything you do.
- You recognize that diversity, varied skills and fresh ideas make a group exponentially better in the pursuit of a common goal.
- You know that learning changes minds and lives, so you are committed to learning throughout your professional career and continually achieving the skills required and essential to your success.
- You are open to ideas that challenge conventions and stimulate innovation.

Join us and you will see that your work will help create renewable energy, impact major industries and boost economies. At ArcelorMittal, we'll help you create your world.

Attractive remuneration with stimulating career prospects in which eminent scientists and engineers evolve in a multicultural environment.