Engineering internship
Engineering Internship
Your entry-level start in computer vision, data and LLMs, or frontend: work on a real project, coached by one of our engineers, and build something useful that can go into production.
The opportunity
The role
An internship at UUG.AI is a focused engineering project, not a collection of side tasks. Together we will choose a track in computer vision, data and LLMs, or frontend engineering, then define a problem with a useful outcome for the platform.
You will have a dedicated engineer as your coach, regular feedback, access to the wider team, and room to investigate before you build. The scope will match the length of your internship and what you want to learn.
Your impact
What you will work on
- Turn an agreed problem into a clear project plan with milestones, risks, and a definition of done.
- Learn the relevant part of our stack and document the decisions you make along the way.
- Build and test a working solution using the same engineering practices as the rest of the team.
- Share progress regularly, ask for feedback early, and adjust the scope when evidence changes.
- Demonstrate the result to the team and leave the project in a state others can understand and continue.
- Where the result is ready, work with your coach to integrate or deploy it in a production path.
About you
You may thrive here if
- You are studying or recently completed a relevant technical programme, or can show equivalent self-directed work.
- You have foundations in the track you choose: Python and ML, data and LLMs, or TypeScript and frontend development.
- You can explain a project you built, what went wrong, and what you learned from it.
- You are curious, communicate when you are blocked, and are willing to test assumptions instead of hiding uncertainty.
- You can work regularly from our Ghent office as part of a hybrid arrangement.
You do not need to match every point. If the work sounds like a strong fit, tell us what you would bring and where you want to grow.
Useful additions
Helpful experience
- A portfolio, GitHub project, thesis, hackathon, or substantial course project
- Docker, Git, automated tests, or a first deployment
- Computer vision, multimodal AI, data analysis, or interactive visualisation
- Writing technical notes or presenting project results
- Working in a team on a shared codebase
How we work
Our core principles
Skills differ by role. These are the behaviours we expect from everyone building UUG.AI.
- 01
Strong communication
Share context, decisions, and concerns clearly. Ask questions early, listen carefully, and adapt the message to the people involved.
- 02
Disciplined and honest
Do what you say, work with care, and be direct about uncertainty or mistakes. We value evidence and transparency over appearances.
- 03
Team player and owner
Help the team succeed while taking responsibility for the outcome. Collaborate openly, follow through, and leave the work better than you found it.
A clear start
What to expect in your first months
The exact pace depends on the role and your experience. We use these steps to align on support, ownership, and useful outcomes.
- 01
Shape the project
Start with your coach by refining the question, exploring the stack, and agreeing on a realistic project plan.
- 02
Build with feedback
Work in small steps, review progress regularly, and use tests or evaluations to show whether the approach works.
- 03
Deliver a useful result
Finish with a documented implementation and team demo, with a production path when the result is ready for it.
How we hire
A practical conversation, both ways.
We want you to understand the work, the team, and our expectations before making a decision.
- 01
Application
Send your CV or profile and a short note about relevant work.
- 02
Intro conversation
Discuss what you are looking for and get context on UUG.AI and the role.
- 03
Practical deep dive
Complete a focused take-home exercise, then present and discuss your approach with the team in person at our Ghent office.
- 04
Team and expectations
Meet future colleagues and align on scope, ways of working, and next steps.
Build with us
Ready to start the conversation?
Tell us what caught your attention and show us the work you are proud of.