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Research Engineer (Robotics Algorithms) - LYB1

SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)

Singapore

On-site

SGD 60,000 - 80,000

Full time

Today
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Job summary

A leading educational institution in Singapore is seeking a Robotics Software Engineer to enhance applied research in robotics. The ideal candidate will have robust experience in learning-based control and mobile manipulation, and will focus on algorithm development and deployment in real-world robotic systems. Key qualifications include a Bachelor's degree in a related field and proficiency in Python and C++. This role offers an engaging environment working closely with industry demands.

Qualifications

  • At least 2 years of experience in robotics project development (research or industry).
  • Experience deploying algorithms on mobile manipulators or articulated robot arms.
  • Knowledge of control / motion planning frameworks such as MoveIt.

Responsibilities

  • Develop, implement, and optimize algorithms for contact-based mobile manipulation.
  • Integrate learned policies with the robot control stack in ROS / ROS2.
  • Conduct simulation-to-real deployment, including data collection, model training, and policy testing.

Skills

Hands-on experience with deep learning frameworks
Proficient in Python
Proficient in C++
Experience with ROS or ROS2
Working knowledge in reinforcement learning
Familiarity with simulation tools

Education

Bachelor’s degree in Robotics, Computer Science, Mechanical Engineering, Control Engineering

Tools

PyTorch
TensorFlow
Gazebo
Isaac Sim
MuJoCo
Job description
Offer Description

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.

We are seeking a Robotics Software Engineer with strong experience in learning-based control and mobile manipulation. The successful candidate will work on algorithm development for contact-rich robotic manipulation, integrating perception, planning, and control within a real-world robotic system.

  • Develop, implement, and optimize algorithms for contact-based mobile manipulation.
  • Apply reinforcement learning, imitation learning, and motion / manipulation skill learning to real robot tasks.
  • Integrate learned policies with the robot control stack in ROS / ROS2 environments.
  • Develop perception and state representation pipelines using RGB-D / 3D sensing.
  • Conduct simulation-to-real deployment, including data collection, model training, and policy testing.
  • The staff to to communicate with any relevant internal or external stakeholders to ensure project deliverables can be met.
  • Any other ad-hoc duties assigned by supervisor.
  • Bachelor’s degree or above in Robotics, Computer Science, Mechanical Engineering, Control Engineering, or related fields.
  • Hands‑on experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Experience with ROS or ROS2 for real robot software integration.
  • Proficient in Python and C++, with experience in writing production‑level code.
  • At least 2 years of experience in robotics project development (research or industry).
  • Working knowledge in reinforcement learning, imitation learning, or learning‑based control.
  • Experience deploying algorithms on mobile manipulators or articulated robot arms.
  • Familiarity with simulation tools (e.g., Gazebo, Isaac Sim, MuJoCo).
  • Knowledge of control / motion planning frameworks such as MoveIt or whole‑body control libraries.
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