Machine Learning Engineer
Pubblicato il 05-09-2026 - Tenova Advanced Technologies in Castellanza
We are looking for a Machine Learning Engineer willing to join our Data Science and IoT Platform Team. The role involves building, training, deploying ML models, and collaborating on AI based applications to boost production efficiency and to enable predictive maintenance. It is also significantly involved in our digital transformation process and energy transition journey, offering the opportunity to influence them daily with creativity and innovative strength.
Per essere preso/a in considerazione per un colloquio, la preghiamo di assicurarsi che la sua candidatura sia pienamente in linea con le specifiche del lavoro riportate di seguito.
Key Responsibilities
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- Work across the end-to-end machine learning lifecycle, from problem definition and data preparation to model development, deployment, and monitoring
- Build, together with our Software engineers, AI based applications deployed on industrial machinery to boost production efficiency, reduce unplanned downtime and enable predictive maintenance
- Work with colleagues from different Product Lines to help them create and bring innovative solutions to the market
What We Ask For
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- STEM Degree (Science, Technology, Engineering and Mathematics)
- In depth experience with Python and knowledge of ML libraries (e.g. pandas, sklearn, keras/ pytorch)
- Hands-on experience developing and deploying machine learning models
- Good Knowledge of English (written and spoken)
Nice to have
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- Experience with building and deploying LLM models
- Experience with ML Computer Vision models
- Knowledge of Agile methodology and SCRUM
- Knowledge of Microsoft Azure. We use Synapse and ML Workspace
What We Offer
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- The opportunity to contribute to Upstream&TAT; - RAID activities with a direct impact on business performance
- A dynamic and international environment where ideas are valued and innovation is encouraged
- Continuous learning opportunities through training, exposure to new technologies and cross-functional collabora