Vision Software Engineer
Pubblicato il 06-08-2026 - Lean Six Sigma Black Belt in Italia
About the Company
ACMA is a leading organization headquartered in Bologna, Italy.
As a key player in the consumer goods industry for over 100 years, we specialize in manufacturing packaging machines for a range of sectors, including Food, Personal Care, Home Care, Chemicals and E-Commerce.
Our business portfolio encompasses a wide range of innovative tailor‑made packaging machinery solutions, by working hand‑in‑hand with customers and partners.
We strive to continuously expand our offerings and enhance our capabilities to meet the evolving needs of our customers.
For more detailed information about ACMA and its comprehensive business landscape, please visit
ACMA is part of Coesia, a group of innovation‑based industrial and packaging solutions companies operating globally, headquartered in Bologna, Italy. Coesia operates in 34 countries with 20 different companies and employs over 8,000 people as of 2023.
About the Role
We are looking for a Machine Vision Engineer to join our Automation & Digital Innovation team.
The role will contribute to the development of advanced vision systems and our Industrial IoT ecosystem, supporting key initiatives in process control, quality assurance, predictive maintenance, and data‑driven manufacturing.
Main Responsibilities
- Develop, validate, and industrialize machine vision applications from prototype to full‑scale production.
- Collaborate with cross‑functional teams—Automation, Quality, Production—to integrate vision solutions into manufacturing processes.
- Conduct proof‑of‑concept activities for new vision technologies, architectures, and suppliers.
- Select and integrate hardware components, including sensors, industrial controllers, lenses, lighting systems, and cameras.
- Work with commercial vision platforms such as Omron and Cognex .
- Contribute to the design and evolution of the company’s IoT ecosystem, ensuring seamless data flow from edge devices to cloud infrastructure.
- Support the implementation of predictive maint