Embodied AI Robotics Engineer (ROS2, Industrial Automation)

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

A*STAR RESEARCH ENTITIES in Singapore seeks an Embodied AI Engineer to develop robotics intelligence that tightly fuses perception, planning and embodiment across ROS2 and modern simulation environments.

You will design experiments, build prototypes, and apply machine learning techniques to improve robot control and adaptability in real‑world manufacturing settings, collaborating with researchers and engineers.

Qualifications

• Bachelor or Master degree in Robotics, CS, Mech/EE, AI or related field.
• At least 2 years of experience in robotics or AI.
• Strong foundational knowledge in kinematics, dynamics, motion planning, and control.
• Proficiency in programming, especially Python and/or C++.
• Hands-on experience with ROS/ROS2 and simulation tools (Gazebo, Isaac Sim).
• Familiarity with PyTorch or TensorFlow is advantageous.
• Good communication skills for teamwork and documentation.

Responsibilities

• Support R&D in robotic manipulation for advanced manufacturing.
• Design and conduct experiments to collect, process, and analyse data.
• Apply ML/DL techniques to improve robot control and decision-making.
• Develop and test ROS-based prototypes for manufacturing applications.
• Enhance ROS-Industrial capabilities for manipulation and embodied intelligence.
• Integrate perception tools (vision, force/torque) for better interaction.
• Collaborate with cross-functional teams to meet project milestones.

Skills

Python

C++

ROS/ROS2

Machine learning

Deep learning

Motion planning

Robot control

Perception

Education

Bachelor's or Master's degree in Robotics, CS, or related field

Tools

ROS/ROS2

Gazebo

Isaac Sim

Job description

A*STAR RESEARCH ENTITIES in Singapore seeks an Embodied AI Engineer to develop robotics intelligence that tightly fuses perception, planning and embodiment across ROS2 and modern simulation environments.

You will design experiments, build prototypes, and apply machine learning techniques to improve robot control and adaptability in real‑world manufacturing settings, collaborating with researchers and engineers.