Engineer, Embodied AI

BLACK SESAME TECHNOLOGIES (SINGAPORE) PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

BLACK SESAME TECHNOLOGIES (SINGAPORE) PTE. LTD. seeks an Embodied AI / Robot Intelligence R&D Engineer to bridge large AI models with real-world robot perception, planning and control.

You will build modular robot brain architectures and ROS 2-based execution to enable autonomous execution on diverse platforms. The role focuses on integrating LLM/VLM/VLA models, world models, and spatial intelligence with hierarchical planning and reusable skill libraries, driving state-of-the-art ​​robot

Qualifications

• Master’s degree or above in Robotics, AI, CS, automation, electrical or mechanical engineering or related field.
• Strong Python and/or C++ programming skills and solid robotics fundamentals.
• Experience with ROS/ROS 2 and modern deep learning architectures (Transformers, VLM/LLM).
• Ability to implement and evaluate research ideas on real robotic systems.

Responsibilities

• Develop embodied AI algorithms for robotic perception, reasoning, planning and autonomous execution.
• Research and integrate LLM, VLM and VLA models into real-world robotics.
• Build hierarchical robot planning architectures including LLM-based planning.
• Develop world models, spatial intelligence and persistent robot memory.
• Conduct simulations and real-robot experiments on mobile robots and manipulators.

Skills

Python

C++

Robotics fundamentals

SLAM / Navigation

Reinforcement learning

ROS 2

Transformer / VLM / LLM

Education

Master’s degree or above

Tools

ROS 2

Job description

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.