Robotics Engineering Intern: Real Hardware & AI Testing

Flexion Robotics; Zürich; Vor Ort; CHF 20.000 - 31.000; Teilzeit

Benefits dieser Stelle

Competitive compensation

Front-row seat at one of Europe's most

Energetic, collaborative team with a -

Zusammenfassung

Flexion Robotics in Zürich, Switzerland, invites you to join as a Robotics Engineering Intern to test our software on real humanoid robots. You will run end-to-end tests, debug hardware-software issues, and help keep our robot fleet and test infrastructure in good shape.

You'll work closely with our AI engineers to close the loop between models and machines, gaining practical experience deploying learning-based software on physical systems while building robust test pipelines and documentation.

Qualifikationen

• Must be enrolled in MSc in Robotics, Electrical, CS, or Mechanical Engineering.
• Hands-on experience with robotic systems and debugging across the full stack.
• Proficient in C++ with ability to test on real hardware.

Aufgaben

• Conduct full-stack tests of Flexion software on hardware fleets.
• Debug issues surfaced during hardware testing across software/hardware boundary.
• Maintain readiness of robot fleet and test infrastructure for reliable experimentation.
• Document test results and fixes to share learnings with the team.
• Support AI engineers by translating needs into repeatable test setups.
• Assist with designing tests to validate learning-based software on real robots.

Kenntnisse

C++

Robotics debugging

Autonomous working style

English proficiency

Python scripting

Ausbildung

MSc in Robotics

MSc in Electrical Engineering

MSc in Computer Science

MSc in Mechanical Engineering

Tools

ROS/ROS 2

Git

Linux (Ubuntu)

Jobbeschreibung

Flexion Robotics in Zürich, Switzerland, invites you to join as a Robotics Engineering Intern to test our software on real humanoid robots. You will run end-to-end tests, debug hardware-software issues, and help keep our robot fleet and test infrastructure in good shape.

You'll work closely with our AI engineers to close the loop between models and machines, gaining practical experience deploying learning-based software on physical systems while building robust test pipelines and documentation.