Machine Learning Engineer

Tenova S.p.A.; Varese; In loco; EUR 30.600 - 37.400; Tempo pieno

Vantaggi offerti da questo lavoro

Hybrid work model

14th-month salary

Performance bonus

Supplementary healthcare

Annual welfare benefits €250

Discounts on transport, sports, travel

Descrizione del lavoro

Tenova S.p.A. is seeking a Machine Learning Engineer to drive end-to-end ML projects for industrial machinery in Castellanza (VA). You will deliver data-driven solutions to boost production efficiency, reduce downtime, and enable predictive maintenance.

The role involves collaborating with software engineers and product lines to translate AI concepts into field-ready applications, with a focus on hands-on ML model development, deployment, and monitoring. English proficiency is required.

Competenze

• 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)

Mansioni

• 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

Conoscenze

Python

ML libraries

Model deployment

English proficiency

Formazione

STEM Degree

Strumenti

Azure

Synapse

ML Workspace

Descrizione del lavoro

Overview

Tenova, a Techint Group company, is a worldwide partner for sustainable, innovative and reliable solutions in the metals and mining industries. Tenova leverages a workforce of over 2,500 professionals located in 18 countries across 5 continents, who design technologies and develop services that help companies reduce costs, save energy, limit environmental impact and improve working conditions.

Your role in Tenova: Machine Learning Engineer

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 work on innovative AI-driven projects with real business impact.
• A dynamic and international environment where ideas are valued
• Continuous learning (training, exposure to new technologies, cross-team collaboration)
• The applicable collective labor agreement is CCNL per Industria Metalmeccanica Privata e della Installazione di Impianti
• Hybrid working model (6-8 days)
• 14th-month salary

• Performance bonus linked to business results
• Performance Management: continuous development process with multi-source feedback and defined development actions

• Annual welfare benefits worth €250
• Savings & leisure: access to discounts on transport, sports, travel, and cultural activities
• Supplementary healthcare coverage
• Well-being initiative

Hybrid working model (6-8 days), and the starting gross annual salary will be from €34,000. The final offer is determined based on the candidate’s seniority, experience, and skills, as well as the outcome of the selection process.

Workplace: Castellanza (VA)