Embodied AI Engineer - Humanoid Robots in Action

YY CIRCLE (SG) PRIVATE LIMITED; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Hands-on robotics

Real-world deployment

Career growth

Job summary

YY CIRCLE (SG) PRIVATE LIMITED in Singapore seeks an Embodied AI Engineer to develop and deploy intelligent behaviors on physical humanoid robots. You will own end-to-end AI development from data collection to real-robot deployment, across perception, planning, and embodied decision-making.

The role is hands-on and cross-disciplinary, with opportunities to work on data collection, model training, system integration, and continuous performance improvement in both simulation and real environments.

Qualifications

• Master's degree or higher in Robotics, Computer Science, AI, Engineering or related field.
• Hands-on experience with robotic systems including integration, calibration, or teleoperation.
• Comfortable working across AI, robotics, hardware, data collection, testing and operations.

Responsibilities

• Develop, integrate, and fine-tune robot foundation models for perception, mapping, task planning, and embodied decision-making.
• Own the development cycle from data collection and model training to physical-robot deployment and validation.
• Test and analyze system failures, then improve performance through targeted data collection, model retraining, and iterative validation in simulation and real-world environments.
• Track key performance metrics such as task success rate, completion time, intervention rate, repeatability, and safety.

Skills

Robot learning

Imitation learning

Reinforcement learning

Diffusion policies

Education

Master's degree or higher

Job description

YY CIRCLE (SG) PRIVATE LIMITED in Singapore seeks an Embodied AI Engineer to develop and deploy intelligent behaviors on physical humanoid robots. You will own end-to-end AI development from data collection to real-robot deployment, across perception, planning, and embodied decision-making.

The role is hands-on and cross-disciplinary, with opportunities to work on data collection, model training, system integration, and continuous performance improvement in both simulation and real environments.