ICEYE Engineering Intern Lab 2027

ICEYE Engineering Intern Lab 2027

Get paid to build the future of space.

Join ICEYE, the company operating the world’s largest Synthetic Aperture Radar (SAR) satellite constellation, for a fully paid, onsite internship where AI meets real-world engineering. The ICEYE Engineering Internship Program (“The ICEYE Intern Lab”) is designed for talented students in computer science, engineering, hardware, data science, and AI who want to apply their skills to meaningful challenges in earth observation, sensor technology, and intelligent systems.

With a flexible term of 3–6 months, interns work onsite at ICEYE’s engineering offices (Finland, Spain or Poland), collaborating directly with hardware, software, and operations teams on mission-driven projects. We seek Master’s and Bachelor’s students with strong AI tool fluency, curiosity, and a hands-on builder mindset.

You’ll be embedded in one of ICEYE’s engineering teams as a contributing team member for the duration of the program, contributing to real satellite and analytics projects (not simulations) that advance ICEYE’s mission to make the world safer and more resilient through persistent monitoring.

This second cohort officially launches in May 2027, with opportunities for early placement available.

Application Deadline : December 21, 2026

Decision Timeline : Offers to be made on a rolling basis with final decisions made by February 15, 2027

Cohort start date : May 2027

Qualifications:

Education

• Currently enrolled as a Bachelor's student (3rd year or later) or Master's student in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Electrical Engineering, Mechanical Engineering, Aerospace, or a closely related field.

• Recent university graduates are also eligible.

• Must be eligible to work onsite in Finland, Spain or Poland (EU/EEA citizen, or able to secure an appropriate visa with the support of ICEYE).

Technical Skills

Our teams and projects span many different disciplines, but they are all highly technical and hands-on. Here is an example of technical skills needed in certain areas:

• For software engineering roles : strong programming proficiency in Python, Go, Rust, and/or C++

• For data science roles : computer vision, LLM, and/or classical machine learning experience. Python as a key programming language; data processing, analysis, or visualization tools (e.g., NumPy, Pandas, Matplotlib)

• All: Deep experience using AI coding assistants (e.g., Claude Code, Devin, Cursor, etc.) to enhance productivity, especially learning how to use agentic workflows.

• All: Understanding of software development practices: version control (Git), testing, debugging, and documentation.

AI Mindset

• AI development tool literacy (e.g. AI IDE or coding agents)

• Demonstrated curiosity about how AI can accelerate real-world engineering.

• Comfortable experimenting with AI-first workflows and prompt-based problem solving.

• Willingness to learn new tools quickly and apply them to open-ended technical challenges

You …

• have strong communication skills and ability to work in multidisciplinary teams (hardware, software, operations).

• are not afraid to ask a lot of questions.

• are proactive, resourceful, and a hands-on problem solver.

• are able to manage time effectively in a fast-paced, high-impact environment.

• are comfortable giving and receiving feedback, and presenting work during weekly reviews and demo days.

ICEYE Gives …

• Salary 1 000 - 3 300€ /month based on location and years of study

• Flights/transportation to your ICEYE office location

• Housing

• Work visa (if needed)

Recruitment process

• Application: Submit your CV and answer a few short questions instead of a cover letter (about 30 minutes).

• Peer Interview (30 min): A conversation with a former ICEYE intern about how you work, learn and collaborate.

• Team matching: We match you with the engineering team that best fits your skills and interests.

• Technical Interview with your future team (60 min): A short problem-solving exercise and a conversation with the team lead. We care more about how you approach the problem than about getting a perfect answer.

• Decisions and offer