Lead Physical AI Engineer, Multi-Robot Swarm Systems

St Engineering; Singapore; On-site; SGD 180,000 - 240,000; Full time

Benefits offered by this job

Cutting-edge projects

Hands-on testing

Flexible culture

Job summary

Singapore Technologies Engineering Ltd is seeking a Principal Physical AI Engineer focused on Multi-Robot & Swarm Systems to advance real-time planning, coordination, perception, and infrastructure for autonomous robot teams in complex environments.

The role involves developing MRS modules, integrating sensors and simulators, and collaborating across controls, perception, and AI/planning teams to deliver production-ready autonomy stacks.

Qualifications

• Master's or PhD in CS, Robotics, Mechatronics, EE or related field.
• 10-15 years of experience building multi-robot or swarm systems.
• Deep knowledge of distributed autonomous systems and swarm algorithms.
• Familiarity with SLAM, localization, planning, and control loops.

Responsibilities

• Develop and maintain multi-robot collaboration modules.
• Integrate hardware drivers, sensors, and simulators.
• Design real-time data pipelines for robot-to-robot and robot-to-cloud messaging.
• Contribute to ROS2 nodes, services, actions, and MRS stacks.
• Prototype in simulation and validate on physical robots.
• Collaborate with cross-functional robotics engineers.
• Define technical solutions to meet customer requirements.
• Advise on emerging MRS/Swarm technologies.
• Lead strategic capability development for MRS/Swarm.
• Collaborate on R&D projects for new capabilities.

Skills

Python/C++

ROS2

Distributed systems

Prototyping

Education

Masters/PhD in CS/Robotics/Mechatronics/EE

Tools

Gazebo

Ignition

Webots

Isaac Sim

ROS2 tooling

Job description

Singapore Technologies Engineering Ltd is seeking a Principal Physical AI Engineer focused on Multi-Robot & Swarm Systems to advance real-time planning, coordination, perception, and infrastructure for autonomous robot teams in complex environments.

The role involves developing MRS modules, integrating sensors and simulators, and collaborating across controls, perception, and AI/planning teams to deliver production-ready autonomy stacks.