Embodied AI Research Engineer

HUMMINGBIRD BIOSCIENCE PTE. LTD.; Singapore; On-site; SGD 150,000 - 210,000; Full time

Job summary

HUMMINGBIRD BIOSCIENCE PTE. LTD. in Singapore seeks a hands-on Embodied AI Research Engineer to develop and integrate intelligent robotic systems in simulation and on physical robots, including Unitree G1 humanoid and robotic arms.

This is an individual-contributor role for an experienced robotics engineer with broad knowledge of the stack. You will work on world models, robot memory, planning, locomotion, manipulation, and multimodal robot intelligence, translating research ideas into working

Qualifications

• 3+ years in robotics, robot learning, RL, control, embodied AI, or autonomous systems.
• Hands-on experience with sim-to-sim and sim-to-real transfer.
• Experience with MuJoCo, Isaac Sim, Isaac Lab or similar simulators.
• Experience in robotic planning, learned dynamics, sequential decision-making; hierarchical control.
• Proficient with ROS 2; strong Python and practical C++ skills.
• Ability to translate research into working implementations; strong testing and debugging.

Responsibilities

• Develop task-planning, hierarchical-planning, and motion-planning for complex robotic tasks.
• Integrate perception, planning, robot interfaces, and task execution into complete systems.
• Build simulation, testing, and evaluation environments using MuJoCo, Isaac Sim, Isaac Lab, or similar.
• Transfer systems between simulation environments and to physical robots.
• Integrate and test software humanoid robots or robotic arms and other platforms.
• Research and prototype world models, robot-memory architectures.
• Reproduce and evaluate methods from robotics and embodied-AI research.
• Debug issues across software, simulation, and hardware.
• Build maintainable robotics software, benchmarks, and automated experiment infrastructure.
• Use AI coding agents and agentic development workflows to accelerate research.

Skills

Robotics

Reinforcement learning

Python

C++

ROS 2

Planning

Sim-to-real transfer

Hardware debugging

Software testing

Experimentation

Tools

MuJoCo

Isaac Sim

Isaac Lab

ROS 2

Job description

The Role

We are seeking a hands-on Embodied AI Research Engineer to develop and integrate intelligent robotic systems in simulation and on physical robots.

This is an individual-contributor role for an experienced robotics engineer with broad knowledge of the robotics stack and particular strength in planning, system integration, and sim-to-real deployment.

You will work on world models, robot memory, planning, locomotion, manipulation, and multimodal robot intelligence. Prior expertise in every one of these areas is not expected. The ability to understand complete robotic systems, implement new research ideas, and make them work on physical robots is more important.

You will work across platforms including the Unitree G1 humanoid and robotic arms.

Responsibilities

• Develop task-planning, hierarchical-planning, and motion-planning systems for complex robotic tasks.
• Integrate perception, planning, robot interfaces, and task execution into complete robotic systems.
• Build simulation, testing, and evaluation environments using MuJoCo, Isaac Sim, Isaac Lab, or similar.
• Transfer systems between simulation environments and from simulation to physical robots.
• Integrate and test software humanoid robots or robotic arms, and other physical robot platforms.
• Research and prototype world models, robot-memory architectures,
• Reproduce and evaluate promising methods from recent robotics and embodied-AI research.
• Debug issues across software, simulation, and hardware.
• Build maintainable robotics software, internal benchmarks, and automated experiment infrastructure.
• Use AI coding agents and agentic development workflows to accelerate research and engineering.

Required Qualifications

• At least three years of relevant professional / industry experience in robotics, robot learning, reinforcement learning, control, embodied AI, or autonomous systems
• Practical experience with sim-to-sim and sim-to-real transfer.
• Experience with MuJoCo, Isaac Sim, Isaac Lab, or another robotics simulator.
• Experience in robotic planning, learned dynamics, sequential decision-making. hierarchical control
• Experience with ROS 2.
• Strong Python skills and practical C++ experience.
• Ability to translate research papers and ideas into working implementations.
• Strong software engineering, experimentation, testing, and debugging skills.
• Willingness to work directly with physical robots and troubleshoot across software, simulation, and hardware.
• Familiarity with AI-assisted coding tools and agentic development workflows.

Preferred Qualifications

• Experience with quadrupeds, humanoids, robotic arms, or other autonomous systems.
• Experience with world models, robot memory, predictive models, or model-based reinforcement learning.
• Experience with motion-planning or control libraries.
• Evidence of strong applied work through robot demonstrations, open-source projects, publications, patents, or deployed systems.
• Additional useful experience includes VLA training, JEPA-style models, sensor fusion, whole-body control, dexterous manipulation, domain randomization, and large-scale training infrastructure.

What We Value

We are looking for someone who is curious, experimental, and comfortable challenging assumptions. You should be able to move between reading research, writing software, running simulations, and testing on physical robots without becoming attached to one technical approach before the evidence supports it.

Success will be measured primarily by successful deployment on physical robots, performance against internal benchmarks, research iteration speed, and demonstrated improvements in robot autonomy, planning, locomotion, or manipulation.