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Process Engineer

Pubblicato il 23-09-2026 - ALBELISSA in Torino

Job Title

Process Engineer

Job
ID

27700695

Location

Chivasso, Torino (Turin), IT

Other Location

Description
Siamo alla ricerca di un Process Engineer da inserire in importanti progetti in ambito biomedicale.Responsabilità:Responsible for design and qualification of manufacturing processes (mechanical/electrical/software/IO data), critically revising components and external processes in a global DFM logicResponsible for development/optimization/upgrade of manufacturing processes, relative test plan validation strategy, from inception, identifying appropriate technology, through to startup and certification including periodical re-validation need strategy and need evaluationResponsible for Validation strategy execution and tech documentation preparationResponsible for manufacturing flow Process Failure Mode and Effect Analysis from inception to startup,



root cause analysis and update in the frame of continuous improvementResponsible for change proposal review and standardization and relative implementation based on design transfer rulesResponsible for Continuous Improvements identification within the plant aimed to maintain and improve processes performancesResponsible to define requirements for new manufacturing equipment and tool validating the intended use with the better compromise of quality/costResponsible for day by day problem solving and CAPA processesRequisiti richiesti:Minimum 5 years of experience in process or product industry's technical teamsMaster degree in Mechanical, Biomedical, Industrial Production or Aerospace Engineering or Mechatronic Technical DiplomaProcess validation methodology - Intermediate level Manufacturing know how - Intermediate level as minimumPrototyping technology - Basic level Critical approach - Intermediate level Self- time management - Intermediate level Communication based on proactive and synthetic exchangeUse of informatics tool - Intermediate level as minimumEnglish language - Intermediate level as minimumStatistical

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