Build and maintain simulation environments for mobile robotic perception and navigation
Develop and integrate robotic behaviours and learning pipelines for reinforcement learning and motion planning in complex outdoor environments
Collaborate with cross-functional teams to validate robotic algorithms in simulated environments
Optimize simulation performance for large-scale training and testing including cloud-based deployments

Bachelor’s or master's degree in Robotics, Computer Science, Mechanical Engineering or related fields
Experience with the ROS2 framework
Experience with ROS2 navigation stack including RTAB-MAP, NAV2, ROS Control, behaviour tree
Proficiency in Python and C++
Solid understanding of mobile robotic systems including kinematics, dynamics and control
Experience in creating digital twins and simulation using IsaacSim, Gazebo, MuJoCo, CoppeliaSim or Unity
Experience in creating simulated sensors in digital twins including GNSS/GPS, cameras, IMU, wheel odometry and others
Familiarity with simulation-based testing and validation of robotic algorithms and bridging the gap between simulation and the real world

Experience with OpenUSD (Universal Scene Description) and Omniverse extension development
Hands on experience with non-mobile robots such as industrial robots including Universal Robots, KUKA, Denso or others, or humanoid robots
Background in reinforcement learning or machine learning for computer vision robotics including tasks such as visual odometry, feature extraction, loop closures and segmentation with example libraries Pytorch, TensorFlow, Keras
Experience with CI/CD pipelines and simulation automation including setting up the HIL robotics testing
Familiarity with cloud platforms such as AWS or Azure for distributed simulation

Build and maintain simulation environments for mobile robotic perception and navigation
Develop and integrate robotic behaviours and learning pipelines for reinforcement learning and motion planning in complex outdoor environments
Collaborate with cross-functional teams to validate robotic algorithms in simulated environments
Optimize simulation performance for large-scale training and testing including cloud-based deployments

Bachelor’s or master's degree in Robotics, Computer Science, Mechanical Engineering or related fields
Experience with the ROS2 framework
Experience with ROS2 navigation stack including RTAB-MAP, NAV2, ROS Control, behaviour tree
Proficiency in Python and C++
Solid understanding of mobile robotic systems including kinematics, dynamics and control
Experience in creating digital twins and simulation using IsaacSim, Gazebo, MuJoCo, CoppeliaSim or Unity
Experience in creating simulated sensors in digital twins including GNSS/GPS, cameras, IMU, wheel odometry and others
Familiarity with simulation-based testing and validation of robotic algorithms and bridging the gap between simulation and the real world

Experience with OpenUSD (Universal Scene Description) and Omniverse extension development
Hands on experience with non-mobile robots such as industrial robots including Universal Robots, KUKA, Denso or others, or humanoid robots
Background in reinforcement learning or machine learning for computer vision robotics including tasks such as visual odometry, feature extraction, loop closures and segmentation with example libraries Pytorch, TensorFlow, Keras
Experience with CI/CD pipelines and simulation automation including setting up the HIL robotics testing
Familiarity with cloud platforms such as AWS or Azure for distributed simulation

Robotics Engineer

Skills