Senior Professional Officer in Robotics and Embodied AI

About the role

The Singapore Institute of Technology (SIT) is hiring a Senior Professional Officer (and above) in Robotics and Embodied AI within its Professional Officers Division. The role sits in the Punggol Digital District campus, a living lab for robotics test-bedding, and focuses on applied research in embodied AI, simulation and digital twins, cybersecurity, robot operations and related areas. Academic staff will work with industry partners and government agencies to solve practical deployment challenges and train the next generation of robotics talent.

Key responsibilities

• Lead or co-lead applied research and industry collaboration projects with industry partners and government agencies.
• Design, develop and teach laboratory sessions and practice-based modules in Robotics and Embodied AI.
• Secure and manage research grants to support applied research.
• Supervise and mentor students in applied research projects, capstone projects and the Integrated Work Study Programme.
• Manage laboratory facilities, equipment and technical resources, ensuring compliance with laboratory safety policies.
• Contribute to applied AI capabilities, learning resources and curriculum support, working with faculty and internal stakeholders.

Required profile

• Bachelor's, Master's or PhD degree in Robotics, Mechanical/Electronics Engineering, Computer Science or a related field, with demonstrated embodied AI research or application experience.
• At least 8 years of relevant industry experience, preferably in a technical role within an organisation driving research and innovation outcomes.
• Demonstrated interest and capability in supporting research and academic projects, and strong supervisory and mentoring skills.
• Commitment to continuous learning; managerial or team leadership experience may be required for senior appointments.

Required skills

• Robotics control: imitation/reinforcement learning, generative policies, residual learning, cross-embodiment generalisation.
• Robotics data engineering: data capture, synchronisation, calibration, evaluation harnesses and simulation pipelines.
• Foundation models and world models for robotics, including VLA grounding and planning interfaces.
• State estimation, perception and sensor fusion, including 3D scene understanding and active perception.
• ROS2 system integration, safety and field deployment engineering.
• Swarm robotics, multi-agent systems, fleet management and remote operations.
• Cyber-physical security, threat modelling, incident response, AI ethics and data privacy.