Robotics Engineer Intern - Spatial AI & Intelligent Robotics

Do you want to dive in the fast-growing industry of drones and get a rewarding experience in a dynamic scale-up environment? 

At Flyability, we believe that robots should be sent into hazardous places and dangerous environments instead of humans. To support our belief, we created Elios, the world’s first collision-tolerant flying robot that can safely enter, survey, and inspect confined spaces so that people don’t have to. With more than 130 employees, Flyability is the pioneer in the UAS indoor inspection industry. Joining Flyability is not just taking on a new job; it is seizing the opportunity to improve the lives of millions of people and contribute to the future of robotics.

To complete our creative and dynamic team in Lausanne, we are seeking a:

Robotics Engineer Intern - Spatial AI & Intelligent Robotics (100%)
Ideal starting date: 01.08.2026

Your role:
In this role, you’ll work at the intersection of robotics, AI, and spatial understanding to help advance how autonomous systems perceive, represent, and reason about complex environments. Working directly on our production-grade drone platform, the Elios 3, you will research, develop, and validate AI-driven capabilities that bridge state-of-the-art research with real-world robotic applications.

Working directly on the Elios 3 platform, you will bridge state-of-the-art AI research with real-world robotics and contribute to future human-robot interaction capabilities for industrial drones.

What you will own: 

• Spatial Representation: Research, design, and implement methods for representing and organizing information about complex environments and their structure.
• Knowledge Integration: Investigate approaches for combining perception outputs with contextual and domain-specific information to support intelligent system behavior.
• AI for Robotics: Develop methods that enable AI systems to interpret and reason about environmental information to support autonomous robotic operation.
• System Integration & Evaluation: Integrate your work into an existing robotics stack and evaluate performance through simulation and experimental validation.
• Performance Analysis: Define and assess metrics related to system performance, robustness, efficiency, and overall behavior.

Requirements

• Currently pursuing a Master’s degree in Robotics, Computer Science, or a related engineering field
• Previous experience in robotics, machine learning, spatial AI, semantic mapping, scene graphs or related fields
• Strong programming skills in Python
• Familiarity with modern AI approaches such as vision-language models, LLMs fine tuning, retrieval systems (RAG), graph-based representations, semantic mapping, or deep learning frameworks
• Experience with robotics hardware is a plus
• Comfortable reading and implementing ideas from scientific literature
• Hands-on mindset with strong analytical skills and curiosity for solving open-ended research challenges
• Fluent in English. French or other languages are a plus
  

Flyability is a Swiss company with over 10 years of experience that values independent thinking combined with a collaborative spirit. Every day, you will have the opportunity to share your ideas and contribute to solving problems. We all work together, and each voice is considered as we collaborate to achieve our goals.

Ready to join?
We know the confidence gap and impostor syndrome can get in the way of meeting spectacular candidates, so please don't hesitate to apply —regardless of your past experience or resume, we'd love to hear from you.

Automated Screening Notice: Please note that Flyability uses automated eligibility questions as part of our initial screening process. If your application does not meet these mandatory requirements, it will be automatically excluded from further consideration. If you submit an application and believe it was incorrectly excluded by the system, you have the right to request a manual review. Please reach out to our HR team at jobs@flyability.com to request human intervention.