Research Software Engineer for Translational Biomedical AI

Build the science that shapes the future of human health.

Application closing date: 15.09.2026

Join a place where ambitious science thrives

Human Technopole is a rapidly expanding life science institute in Milan, where international researchers and cutting-edge technologies converge to accelerate biomedical discovery. Our mission is to transform bold scientific ideas into advances that improve human health.

Within this mission, the Health Data Science Centre develops advanced computational and machine learning approaches to analyse complex biomedical and clinical data. The Centre works at the interface of data science, machine learning, computational biology, epidemiology, and clinical research, with the goal of transforming research models into tools that can support biomedical discovery and healthcare innovation.

We are seeking a motivated Research Software Engineer to help translate research prototypes into robust, usable, and transferable software tools. We welcome candidates at different levels of seniority. Depending on the selected candidate’s experience, the position may be shaped as either a Junior or as a Senior Software Engineer.

This role sits at the interface between software engineering, machine learning and clinical translation. The successful candidate will work closely with data scientists, computational biologists, clinicians, ICT experts, and hospital partners to develop software systems that make advanced research models usable in real-world biomedical and healthcare settings. This position is funded by the European Union EU4H-2026-SANTE-PJ-04 – Project: European Cardiovascular Health data and AI Network (CHAIN), GA 101314833.

Your mission

As a Research Software Engineer for Translational Biomedical AI, you will work closely with data scientists, computational biologists, clinicians, ICT experts, and external collaborators to make biomedical machine learning models easier to use, test, and share across research environments.

You Will Help Researchers Turn Prototype Code, Trained Models, And Analysis Pipelines Into Software That Is More Maintainable, Reproducible, Documented, And Portable. You Will Contribute To Software Tools That Can

• Transform research code into maintainable and documented software.
• Package trained models and inference pipelines for deployment in external organizations.
• Enable hospitals and collaborators to test models locally on their own data without transferring sensitive patient-level information.
• Support reproducible model evaluation across sites.
• Provide usable interfaces, APIs, dashboards, or command-line tools depending on project needs;
• ensure that software tools are robust, secure, documented, and maintainable.
  
  

The role is not primarily a machine learning research position, but the candidate should have enough understanding of machine learning workflows to work effectively with researchers developing predictive, generative, and analytical models for biomedical and clinical data.

Grow Your Skills

You will enhance your professional skills by contributing to:

Research software engineering for biomedical AI

• Refactoring and modularising scientific Python code.
• Turning research prototypes into robust, reusable, and documented software.
• Supporting reproducible model training, validation, inference, and reporting.
• Working with researchers to translate scientific requirements into software tools.
• Developing tools that allow researchers, clinicians, and collaborators to interact with biomedical AI models in a controlled and usable way.
  
  

Machine learning model packaging and deployment

• Packaging trained models, preprocessing pipelines, configuration files, metadata, and evaluation scripts into portable software artifacts.
• Developing containerized model environments using Docker and related technologies.
• Building reproducible inference pipelines that can be transferred to hospitals or external research organizations.
• Supporting privacy-aware validation scenarios where models are tested locally without transferring sensitive data.
• Build CICD pipelines to support the software and AI models development life cycle, from development to testing and deployment.
  
  

Human Technopole supports career development through training, mentoring, and dedicated learning opportunities.

What You’ll Bring

Essential

• Degree in Computer Science, Software Engineerin