Robotics Engineer, Singapore



Full time

    *Compensation package will be commensurate with experiences.    


  • Design and implement software for robot control, including real-time motion control and sensor data processing.
  • Develop algorithms for path planning and trajectory generation.
  • Create software for integrating various sensor to enable perception and navigation capabilities for robots.
  • Implement computer vision and machine learning algorithms for object recognition and localization.
  • Develop algorithms for autonomous navigation and obstacle avoidance.
  • Ensure robots can safely and efficiently navigate in complex environments.
  • Work with robotics middleware frameworks, such as ROS (Robot Operating System), to develop software components.
  • Integrate sensors, actuators, and other hardware with the middleware.
  • Utilize simulation tools to test and validate the software in a virtual environment.
  • Conduct real-world testing and debugging of robotic software.
  • Collaborate with hardware engineers and robotics experts to ensure seamless integration of software and hardware components.
  • Develop interfaces and APIs for intercommunication between different parts of the system.
  • Maintain and update the software as needed, addressing bugs and adding new features.
  • Document software design, architecture, and usage guidelines.
  • Optimize software for resource-constrained robotic platforms, such as embedded systems and mobile robots.


  • Minimum Degree in Computer Science, AI, Robotics, Electrical Engineering, or a related field.
  • Excellent communication and documentation skills.
  • Proficiency in programming languages commonly used in robotics, such as C/C++, Python, and ROS or ROS2 experience..
  • Basic theoretical knowledge on control theory and path planning algorithms.
  • Practical hands-on experience with Motion control and path planning for mobile robots.
  • Strong understanding of software development principles, including object-oriented design and software architecture.
  • Knowledge of real-time and embedded systems programming.
  • Experience with version control systems (e.g., Git) and collaborative development.
  • Familiarity with sensor integration, computer vision, and machine learning.

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