About the role
AI summarisedSenior research scientist role focused on embodied AI for industrial robotics. Leads development of AI-driven robotic capabilities including perception, manipulation, and reinforcement learning for manufacturing environments. Combines research with practical implementation using ROS, simulation tools, and production software development.
ResearchOnsite
Key Responsibilities
- Pioneer and lead research or translation of research into industrial robotics applications, focusing on AI for robotics
- Develop novel algorithms and models for manipulation, navigation, and adaptive autonomy in complex manufacturing environments
- Build and refine high-fidelity simulation environments using tools such as Isaac Sim, Gazebo, or custom simulators
- Apply machine learning and deep learning techniques to improve robot control, adaptability, and decision-making in real-world scenarios
- Architect and collaborate with engineers to develop proof-of-concept software solutions and demonstrators based on research outcomes using languages like C++ and Python and libraries such as ROS
- Support integration of perception tools (e.g., vision, force/torque) to enable better object handling and environmental interaction
- Drive application-oriented robotic research towards industrial automation
- Publish research findings in top-tier robotics/AI venues and develop technical documentation
Requirements
- PhD degree in Robotics Engineering, Software Engineering, Computer Engineering, Electrical Engineering or Computer Science
- Min. years of experience: 3-5 years
- Strong proficiency in C++ and Python
- Experience with ROS and its ecosystem (ROS/ROS2)
- Expertise in AI/ML model development, including reinforcement learning or imitation learning
- Basic familiarity with deep learning frameworks such as PyTorch or TensorFlow is advantageous
- Experience with Isaac Sim, Gazebo, Webots, or equivalent robotics simulators
- Familiarity with Git, collaborative code workflows, and the software development lifecycle
- Demonstrated ability to pioneer research or translate research findings into practical software prototypes or applications
- Understanding of the Software Development Lifecycle (SDLC) and proficiency with Git version control
- Experience with CI/CD and containerization (e.g., Docker, Kubernetes)
- Experience with software systems integration, architecture, communication protocols, and networked systems
- Experience managing research projects or leading technical initiatives
- Experience working with industry partners and presenting technical work
- Prior experience in using/operating humanoids or working in semicon equipment sector is an added advantage