Robotics Engineer

ROBOSPEC PTE. LTD.

Singapore

On-site

SGD 70,000 - 110,000

Full time

5 days ago
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Job summary

ROBOSPEC PTE. LTD. is seeking a hands-on Robotics Engineer to deploy embodied AI on physical robotic arms.

You will transform intelligent models into real-world actions, focusing on deploying control systems on cobots such as Franka and UR. The role involves integrating perception, manipulation, and sensing into reliable hardware pipelines. Responsibilities include design and debug of ROS 2-based control, collaboration with AI teams for VLA/VLM models, and using simulation tools for policy

Qualifications

  • Bachelor’s degree in robotics or related field.
  • Hands-on experience programming and controlling real robotic arms (Franka, UR).
  • Deep experience with ROS 2 and robotics fundamentals (kinematics, dynamics, control).
  • High proficiency in Python for real-time applications.

Responsibilities

  • Real-Arm Deployment & Control: design, implement, maintain ROS 2 control systems on cobots.
  • Embodied AI & Policy Integration: deploy VLA/VLM models and imitation learning on real hardware.
  • Full-Stack Robotics Integration: integrate perception, manipulation, and control into a unified system.
  • Hardware Debugging & Optimization: debug and optimize low-level robot control loops on hardware.
  • Simulation Support: use Isaac Sim/Gazebo for policy training and testing.

Skills

C++
Python
ROS 2
Robot arms control
Real-time systems

Education

Bachelor’s degree in Robotics or related field

Tools

Isaac Sim
Gazebo

Job description

We are looking for a hands-on Robotics Engineerwith a passion for bringing AI to physical hardware. In this role, you will beat the core of our Embodied AI (Physical AI) pipeline, focusing ontransforming intelligent models into real-world robot actions.

Your primary responsibilitywill be programming, control, and real-world deployment on physicalmanipulator arms (such as Franka or UR). If you love working with realhardware, setting up cameras, and making mechanical arms move precisely andintelligently in the physical world, this is the role for you.

Key Responsibilities
  • Real-Arm Deployment & Control:Design, implement, and maintain ROS 2-based control systems directly deployedon physical collaborative robots (cobots), specifically Franka, UR, orsimilar robotic arms.
  • Embodied AI & Policy Integration:Develop core robot manipulation and behavior components using C++ and Python.Collaborate with the AI team to deploy VLA/VLM (Vision-Language-Action)models and imitation learning policies on real hardware.
  • Full-Stack Robotics Integration:Integrate perception (e.g., cameras, sensors), manipulation primitives, andcontrol modules into a unified, reliable real-world system.
  • Hardware Debugging & Optimization:Debug, profile, and optimize low-level robot control loop performance, addressreal-world latency, and solve sim-to-real gaps directly on the hardware.
  • Simulation Support (Secondary): Utilizesimulation tools (e.g., Isaac Sim/Gazebo) as needed for basic policy trainingor initial behavioral testing before full-scale real-world deployment.
Required Skills & Qualifications
  • Education: Bachelor’s degree orhigher in Robotics, Computer Science, Computer Engineering, MechanicalEngineering, or a related technical discipline. (Strong personalportfolio/projects will be highly valued).
  • Hands-on Robot Experience: Strong, proventrack record of programming and controlling real robotic arms (Franka,Universal Robots, etc.).
  • Robotics Frameworks: Deep experience withROS 2 and a solid foundation in robotics fundamentals (kinematics,dynamics, control paths, trajectories, and sensing).
  • Programming: High proficiency in Pythonfor real-time or near-real-time applications.
Preferred (Bonus) Skills
  • Robot Learning: Experience with imitationlearning (e.g., Diffusion Policy, ACT), reinforcement learning, or behaviorcloning applied to physical robots.
  • Sim-to-Real Expert: Prior experiencenavigating the challenges of sim-to-real transfer, including domainrandomization or gap adaptation.
  • End-to-End Delivery: Experiencedelivering end-to-end robotics applications (e.g., advanced picking, assembly,or machine apprenticeship tasks).
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