We’re looking for an experienced roboticist to join a team building and maintaining a production-grade robotics platform that combines autonomous systems, teleoperation, and fleet-level coordination. You’ll work across a range of technical areas including robot control, teleoperation interfaces, motion planning, and optimisation of distributed robotic systems operating in real-world environments.

Qualifications / Requirements

  • 5+ years software engineering experience, including 3+ years in robotics, aerospace, or other physical/real-world systems domains
  • Proven experience leading engineering teams and delivering production software for real hardware systems
  • Strong proficiency in C++ and Python
  • Experience with containerised deployment (e.g. Docker)
  • Experience with real-time or near-real-time control systems and hardware–software integration
  • Strong understanding of modern software engineering practices including Git, code review, automated testing, and CI/CD pipelines (e.g. GitHub Actions, GitLab CI, Jenkins)
  • Experience working with sensor data pipelines (e.g. stereo/RGB cameras, LiDAR, IMUs, force/torque sensors)
  • Experience with ROS / ROS 2
  • Strong Linux development experience

Nice to haves

  • Experience profiling and optimising C++/Python systems for constrained compute or memory environments
  • Experience with robotics simulation environments (e.g. Gazebo, Isaac Sim, or similar)
  • Experience building low-latency networking or communication systems for teleoperation
  • Background in computer vision, perception, machine learning-based detection, pose estimation, or SLAM
  • Experience in early-stage, fast-paced R&D or startup environments, including mentoring or hiring engineers

You’re someone who enjoys staying hands-on in the code while helping unblock and guide a team. You’re comfortable influencing technical direction through collaboration and engineering judgment rather than top-down control, and you thrive in environments where systems are complex, evolving, and closely tied to real-world performance.