Internship – AI & Engineering Knowledge Systems

Company Description Wren Aerospace B.V. is a Dutch start-up developing patented high-altitude pseudo-satellites (HAPS), unmanned aircraft designed for advanced connectivity and sensing. Operating autonomously at around 20 kilometers in the stratosphere, the Wren HAPS system bridges the gap between satellites and conventional unmanned aircraft, providing resilient high-bandwidth communications and persistent surveillance. Its hydrogen–solar propulsion enables long-endurance, year-round operations for critical missions. The company collaborates with telecommunications providers, satellite operators, and government users to deliver services such as disaster-recovery connectivity and persistent Intelligence, Surveillance and Reconnaissance (ISR), including rapid restoration of direct-to-device coverage when ground networks fail. Wren Aerospace is incubated at the European Space Agency Business Incubation Centre Noordwijk and co-funded by the European Union, offering a dynamic environment at the intersection of aerospace, connectivity, and innovation.

Role Description This is a full-time, on-site internship role based in Noordwijk-Binnen. The Internship – AI & Engineering Knowledge Systems focuses on developing and maintaining AI-driven tools and knowledge systems to support engineering, design, and operations for HAPS platforms. Day-to-day tasks may include collecting and structuring technical documentation, building and refining knowledge bases, and assisting with machine learning models that help engineers access and reuse critical information. The intern will support data preprocessing, experiment tracking, and integration of AI tools into existing workflows, while collaborating closely with aerospace, software, and systems engineering teams. The role also involves preparing clear documentation, contributing to process improvement, and participating in technical discussions to ensure knowledge systems remain accurate, usable, and secure.

Qualifications

• Strong foundation in computer science, engineering, or related field, with knowledge of algorithms, data structures, and software development practices.
• Experience or coursework in AI, machine learning, or data science, including model training, evaluation, and basic MLOps concepts.
• Skills in structuring and managing technical information, such as building knowledge bases, ontologies, or documentation systems.
• Proficiency in programming (e.g., Python) and familiarity with tools for data processing, scripting, and automation.
• Ability to analyze complex engineering problems, translate them into data or knowledge system requirements, and propose practical solutions.
• Strong written and verbal communication skills, with attention to detail and a focus on clarity in technical documentation.
• Collaborative mindset, ability to work in interdisciplinary teams, and readiness to contribute in a fast-moving start-up environment.
• Current enrollment in a relevant bachelor’s or master’s program; prior exposure to aerospace, telecommunications, or embedded systems is a plus.