Staff Robotics Engineer: Hybrid & Flexible Hours

Hexagon Robotics; Zürich; Hybrid; CHF 110.000 - 170.000; Vollzeit

Benefits dieser Stelle

Flexible hours

Hybrid work model

Mobility credit CHF 500

Pension contributions

Relocation support

Training opportunities

Team events

International culture

Zusammenfassung

Hexagon Robotics, based in Zürich, is seeking a Staff Robotics Engineer to design and develop robust software on embedded Linux for our humanoid robots. The role involves close hardware collaboration and cross-functional teamwork to take our prototype to production.

You will lead the development of state-of-the-art planning and control algorithms, with hands-on implementation and testing on robots, and you’ll build scalable training pipelines for reinforcement learning in a fast-paced,

Qualifikationen

• PhD or MSc in robotics, computer science, or related field.
• 5+ years creating planning and control algorithms for robotic products.
• Expertise in planning/control methods: sampling-based, optimization-based, ML-based.
• Strong Python and C++ programming skills.
• Familiarity with robotics frameworks like ROS2 and Omniverse.

Aufgaben

• Guide the team in applying state-of-the-art whole-body control algorithms for humanoid robots.
• Hands-on implementation and testing of whole-body controllers on robots.
• Develop scalable training pipelines for reinforcement/imitation learning.
• Collaborate across multi-disciplinary teams to move from prototype to serial production.
• Participate in an R&D culture with startup spirit to solve real-world robotics problems.

Kenntnisse

Python

C++

ROS2

Omniverse

Whole-body control

Ausbildung

PhD/MSc in Robotics

Tools

Hardware interfacing

Jobbeschreibung

Hexagon Robotics, based in Zürich, is seeking a Staff Robotics Engineer to design and develop robust software on embedded Linux for our humanoid robots. The role involves close hardware collaboration and cross-functional teamwork to take our prototype to production.

You will lead the development of state-of-the-art planning and control algorithms, with hands-on implementation and testing on robots, and you’ll build scalable training pipelines for reinforcement learning in a fast-paced,