Software and DevOps Engineer


Work Location: Lainate (MI) – Italy – Via Cristoforo Colombo 1



  • Contribute to the R&D team by designing and developing software prototypes for AI-powered medical devices, ensuring innovation and efficiency.
  • Collaborate closely with machine learning engineers and other stakeholders to seamlessly integrate software components into the overall system architecture.
  • Effectively communicate with the Engineering team to facilitate a seamless transfer from prototype software to production-ready deployment.
  • Design, implement, and maintain a robust CI/CD pipeline and test suite tailored for the R&D codebase, aligning with industry best practices.
  • Demonstrate proficiency in Python and C++, focusing on crafting clean, modular, and efficient code.
  • Leverage strong expertise in object-oriented programming and design patterns for scalable and maintainable code.
  • Establish and maintain best DevOps practices within the R&D team, actively participating in code reviews, troubleshooting, and optimization efforts.
  • Create and maintain comprehensive documentation for software architecture, design, deployment processes, and CI/CD pipelines, ensuring clear and accessible records.



  • Bachelor’s or higher degree in Computer Science, Software Engineering, or a related field.
  • Proven experience in software development using Python and C++.
  • Strong understanding of DevOps principles with hands-on experience in CI/CD pipelines and code versioning software.
  • Expertise in object-oriented programming and design patterns.
  • Experience with containerization technologies (Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP).
  • Excellent problem-solving and communication skills.


Preferred Qualifications:

  • Contributions to open-source projects or a robust GitHub profile.
  • Background in statistics and experience defining metrics and KPIs for machine learning and computer vision tasks.
  • Experience with MLops (Machine Learning Operations) practices and tools.
  • Proficiency in the Scientific Python stack (Numpy, SciPy, etc.).
  • Familiarity with PyTorch, TensorFlow, and Scikit-Learn.
  • Background in Network Communication and Information Systems.
  • Advanced degree or certifications in relevant fields.
  • Previous experience in deploying software for online real-time applications.
  • Knowledge of machine learning concepts and frameworks.

We support equal opportunities, without any discrimination.

The research complies with Legislative Decree 198/2006



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