Joining our group means working at the intersection of academia and industry, contributing to the development of new Artificial Intelligence solutions applied to real-world problems. We are a university industrial research team: we collaborate with companies to turn open questions into experiments, prototypes, and scientific results, while maintaining a focus on methodological rigor and the reproducibility of our work.
As an AI Research Engineer, you will start by actively taking part in ongoing projects from day one, supported by more experienced researchers, and within a few months you will gain autonomy over relevant technical components. The goal is to grow over time until you can design, implement, and lead applied research activities, also contributing to scientific output and to the operational coordination of projects and the team.
The environment is highly collaborative: each project stems from the integration of scientific and engineering expertise, and offers the opportunity to experiment with advanced technologies, interact directly with companies, and share knowledge through discussion and internal training sessions.
As an AI Research Engineer, you will start by actively taking part in ongoing projects from day one, supported by more experienced researchers, and within a few months you will gain autonomy over relevant technical components. The goal is to grow over time until you can design, implement, and lead applied research activities, also contributing to scientific output and to the operational coordination of projects and the team.
The environment is highly collaborative: each project stems from the integration of scientific and engineering expertise, and offers the opportunity to experiment with advanced technologies, interact directly with companies, and share knowledge through discussion and internal training sessions.
Growth Path
The milestones below describe the typical path of a Junior AI Research Engineer at AIRIC during the first few months, taking into account the specific nature of the projects and each person’s individual path.
3rd MONTH
Onboarding & First Months at AIRIC
- Complete onboarding activities and become confident with the tools (e.g., git, Docker, Python) and the group's working methodology (e.g., pull requests and code review, planning).
- Contribute operationally to an industrial research project under the guidance of a senior team member.
6th MONTH
Technical Autonomy
- Independently manage part of the assigned project, taking responsibility for its design and implementation.
- Take part in planning the activities of the assigned research project, proposing ideas and technical solutions.
12th MONTH
Professional growth through projects
- Take part in at least one direct interaction activity with companies (e.g., working groups, design thinking sessions, events), coordinated by senior team members.
- Contribute to at least one exploratory research initiative, under the supervision of a senior member.
- Collaborate on defining proposals for new industrial research projects together with senior team members and the professors who lead the group.
2nd YEAR
Responsibility & Mentoring
- Contribute to the operational management of an industrial research project, coordinating the work of junior colleagues.
- Contribute to at least one exploratory research initiative, under the supervision of a senior member.
- Lead the planning and technical monitoring of the activities of an industrial research project.
- Contribute to the growth of junior profiles through mentoring activities and by supervising their technical contributions (e.g., code review).
- Take part in meetings with new companies to define future research collaborations.
Essential Requirements
- Master's degree in AI-related or STEM disciplines.
- Basic knowledge of Machine Learning and Statistics.
- Experience with at least one programming language, preferably Python.
- Strong analytical aptitude and critical thinking, useful for understanding, structuring, and formalizing complex problems into rigorous models.
- Ability to work in a team and communicate effectively.
- Ability to independently tackle sub-problems, learning new tools and concepts, both mathematical and computational
A plus
- Research experience (thesis, internships, publications).
- Familiarity with tools and methodologies typical of AI research.
- Experience working in collaborative and multidisciplinary environments.
- Interest in scientific production and applied research.
Work Environment
- Flexible working arrangements and the possibility of hybrid work.
- Collaborative and multidisciplinary environment.
- Direct interaction with companies and institutional partners.
- Continuous training and discussion with professors and senior researchers
- Opportunity to contribute to scientific publications and research activities.
