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Open nowPosted 14 days ago

Engineer, Embodied AI

MyCareersFuture94,028 open roles

Pay
SGD 5,800 – SGD 8,000 a month
Where
West, Singapore
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Your applicationOpen nowEngineer, Embodied AIMyCareersFuture · West, Singapore

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Share of postings closed within
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  2. 3.3%3 days
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  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 14 days ago

The posting

We are looking for an Embodied AI / Robot Intelligence R&D Engineer to develop next-generation robot intelligence systems that bridge large AI models with real-world robotic perception, planning, decision-making, and control. The role will focus on building a modular robot brain architecture combining LLM/VLM/VLA, world models, task planning, spatial intelligence, robot skills, physical verification, and ROS 2-based execution.

Key Responsibilities

  • Develop embodied AI algorithms for robotic perception, reasoning, task planning and autonomous execution.
  • Research and integrate LLM, VLM and VLA models into real-world robotic systems.
  • Develop hierarchical robot planning architectures, including LLM-based planning, task planning, skill planning and execution.
  • Build and maintain robot skill/capability models, task graphs and reusable skill libraries.
  • Research world models, spatial intelligence and persistent robot memory for long-horizon robotic tasks.
  • Develop semantic-geometric representations combining visual semantics, 3D geometry and robot/environment states.
  • Conduct simulation and real-robot experiments on mobile robots, quadruped robots, manipulators and other robotic platforms.
  • Track and evaluate state-of-the-art research in embodied AI, robot foundation models, VLA, world models and autonomous robotics.

Required Qualifications

  • Master’s degree or above in Robotics, Artificial Intelligence, Computer Science, Automation, Electrical Engineering, Mechanical Engineering, or a related field.
  • Strong programming skills in Python and/or C++.
  • Solid understanding of robotics fundamentals, including at least several of the following: robot perception; task planning; SLAM/navigation; robot manipulation; reinforcement learning.
  • Experience with ROS/ ROS 2.
  • Good understanding of modern deep learning architectures such as Transformer, VLM, LLM or generative models.
  • Ability to independently implement and evaluate research ideas on real robotic systems.

Experience with real-world robot deployment, publications, patents, or open-source robotics projects will be an advantage.

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