AI Studio · Long-term · Part-time

AI & Software Engineering Intern.

Build something you can explain. Explore AI, write code and turn a small problem into a working prototype, with guidance.

Apply for the internship

Current university studentsPaid, part-timeNo previous experience required

Plan work around your studies

Keep studying. Keep building.

A paid, long-term AI and software internship on a part-time schedule. Plan your own working days and hours around your timetable, share your availability with the team and coordinate meetings, feedback and delivery dates.

There is no fixed weekly hour requirement or advertised duration. Adjust around exams and class changes — just let the team know in advance. Pay, duration, location and agreed hours are confirmed in writing before you start.

A mandatory internship requirement is not needed to apply. We confirm the right contractual and insurance arrangements before the placement begins.

What you could work on

Small scope. Clear learning goals.

Understand a business problem and map its inputs, workflow and expected outputs.
Design prompts, compare responses and build a small evaluation set to check accuracy.
Build a simple AI-assisted application or automation using code and APIs.
Explore Git, basic testing, documentation and a suitable cloud sandbox.
Present a working demo, explain your decisions and improve it with feedback.

Your assignment will match your level and the approved internship scope. You will have a designated supervisor and regular feedback; owning client delivery on your own is not expected.

Who should apply

Curiosity with a technical foundation.

Studying at Istanbul Technical University (İTÜ), particularly Mathematics Engineering or Computer Engineering, and able to manage a part-time schedule alongside your studies.
English good enough to read documentation, write short notes and explain your approach.
Basic programming: variables, conditions, functions and data flow in at least one language.
Familiarity with software products and interest in how applications, APIs and databases work together.
A willingness to ask questions, try unfamiliar tools and check AI-generated output.

No professional experience or previous internship is required. Coursework and self-directed learning count.

Helpful, not required

Show us what you have tried.

A university project, hackathon or personal experiment you can explain.
Exposure to Python or JavaScript/TypeScript, Git, JSON or HTTP APIs.
Trying Azure, AWS, Google Cloud or another deployment platform.
Experience using an AI assistant, coding tool or automation tool.

A public portfolio and cloud certifications are not required. We care about your contribution and how you learn.

The application process

Get to know the work and the team.

1Apply in English with your studies, weekly availability, preferred dates and an optional CV or project link.
2Selected applicants discuss a project or learning exercise, including a short conversation in English.
3We may explore a brief fictional problem together. AI tools are welcome; explain what you checked.
4Before confirming, we review your proposed schedule and agree the training plan, supervisor, pay and dates, then the contract and insurance.

This internship does not guarantee a later employment offer. Graduates can apply to the Graduate AI Solutions Engineer talent pool.

Long-term · part-time application

Bring your questions. Start building.

Please apply in English. Tell us your university, department, year, available days and time windows, estimated weekly hours, earliest start, expected duration and exam-period constraints.

Describe your English level and one project or learning exercise, including your own part in it. Please don't upload identity documents or sensitive records at this stage.