Machine Learning Engineer

15 ago - Castellanza
Tenova Advanced Technologies

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.

Legga la panoramica di questa occasione per capire quali competenze sono richieste, incluse le soft skill pertinenti e la padronanza di pacchetti software.
Key Responsibilities
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
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
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
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 collaboration. xysqume
Hybrid working model according to company policy and

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