Software Engineer for Humanoid Robot Programming

FRONTIER FORCE TECHNOLOGY PTE LTD; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

FRONTIER FORCE TECHNOLOGY PTE LTD in Singapore seeks a Software Engineer for Humanoid Robot Programming to advance robots in our factory lab. You will work on real hardware, integrate ROS 2, Nav2, and perception modules, and collaborate with hardware teams.

Applicants should have a degree in robotics or related field and hands-on experience with humanoid robot software, including Python and C++ on Ubuntu, Git workflows, and ROS 2. This is a full-time on-site role at the Singapore facility.

Qualifications

• Degree in robotics, CS, mechatronics or related field is required.
• Minimum 2 years of professional robot software experience with real hardware.
• On-site full-time work in a factory lab with hands-on robotics work.

Skills

Python

C++

Ubuntu Linux

Git

ROS 2

Nav2

AprilTag

ArUco

PyTorch

Unitree SDK

YOLO/Segmentation

Jetson/TensorRT

Cyclone DDS

Education

Degree in Robotics, Computer Science, Mechatronics or related field

Tools

unitree_sdk2

unitree_sdk2py

Jetson

TensorRT

Cyclone DDS

Job description

Software Engineer for Humanoid Robot Programming

Requirements:

• Degree in Robotics, Computer Science, Mechatronics or related field.
• At least 2 years of professional experience programming mobile or legged robots that ran on real hardware — not simulation-only.
• Willing and able to work on-site at the factory lab full-time, including handson time with the robot and factory equipment.
• Strong Python and C++ on Ubuntu Linux; git-based workflow.
• ROS 2 (Humble or newer): nodes, actions, launch files, TF, DDS configuration (Cyclone DDS / Fast DDS).
• Nav2: costmaps, behavior trees, waypoint/fixed-route following, recovery behaviors, indoor localization.
• Fiducial docking: April Tag/ArUco detection, camera calibration, closed-loop terminal alignment.
• Imitation-learning manipulation: training and deploying ACT / Diffusion Policy style policies in PyTorch, teleop data collection, dataset curation, on-robot evaluation.
• REST/WebSocket API integration between factory systems and the robot.
• Practical hardware debugging: joint states, IMU,RGB-D cameras, Wi-Fi reliability, power.
• Strongly preferred Hands-on experience with Unitree G1/H1 and unitree_sdk2 / unitree_sdk2py, including its Python-version and Cyclone DDS constraints.
• Humanoid locomotion tuning and safe load-carrying gait.
• Object classification on-robot (magazine type identification) with YOLO/segmentation or VLM-based methods, deployed on Jetson/TensorRT