About the role
AI summarisedMid-level robotics software engineer role focused on developing AI-driven robotic intelligence for advanced manufacturing. The position involves applied R&D in robotic manipulation, integrating perception, planning, and control using ROS 2 and industrial platforms. Work spans from research to deployment in manufacturing environments like remanufacturing and smart manufacturing.
ResearchOnsite
Key Responsibilities
- Support applied R&D in robotic manipulation, focusing on robotics technologies for advanced manufacturing
- Assist in designing and conducting experiments to collect, process, and analyse experiment data
- Apply machine learning and deep learning techniques to improve robot control, adaptability, and decision-making in real-world scenarios
- Contribute to developing and testing functional prototypes and ROS-based robotics solutions for manufacturing applications
- Participate in the development and enhancement of ROS-Industrial capabilities for manipulation and embodied intelligence
- Support integration of perception tools (e.g., vision, force/torque) to enable better object handling and environmental interaction
- Stay updated with emerging robotics and AI methodologies, and assist in implementing state-of-the-art approaches to boost performance
- Work closely with cross-functional teams, including hardware/software engineers and researchers, to meet project milestones
- Support technical discussions, documentation, and engagement with industry stakeholders
Requirements
- Bachelor or Master degree in Robotics, Computer Science,Mechanical/Electrical Engineering, Artificial Intelligence, or a related field
- Strong foundational knowledge in robotics fundamentals, including kinematics, dynamics, motion planning, and control
- Interest or exposure to robot learning, Learning from Demonstration, imitation learning, reinforcement learning, or Embodied AI concepts
- Proficiency in programming, especially Python and/or C++
- Hands-on experience or strong interest in ROS/ROS2, simulation tools (e.g., Gazebo, Isaac Sim), and robotic hardware platforms
- Basic familiarity with deep learning frameworks such as PyTorch or TensorFlow is advantageous
- Understanding of sensors (vision, force/torque) and perception techniques is a plus
- Experience or interest in industrial automation, manufacturing environments, or contact-rich manipulation is highly desirable
- Good communication skills for teamwork, documentation, and presenting ideas/findings
- Passion for robotics, strong problem-solving mindset, and eagerness to learn and tackle real-world technical challenges in a collaborative, innovative environment