About the role
AI summarisedThis role is for a Robotics Software Engineer at ARTC, focusing on embodied AI and ROS-Industrial for advanced manufacturing. The engineer will develop robotic intelligence integrating AI-driven perception, planning, and behavior with real-world robot platforms, supporting applied R&D and deployment in manufacturing environments.
ResearchFull-time
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.