Mô tả công việc
1. Job Responsibilities
Develop and integrate ROS2 systems for robots (navigation, SLAM, sensor fusion, control, etc.).
Design, implement, and optimize image processing, machine vision, and image recognition algorithms.
Build and deploy machine learning / deep learning models for robotics applications (object detection, classification, segmentation...).
Program using Python and C++ for AI/robotics modules.
Work with sensors such as camera, LiDAR, IMU and integrate them into ROS2.
Evaluate system performance and improve/optimize algorithms.
Prepare technical documentation, perform code reviews, and collaborate closely with the Japan team.
Yêu cầu
2. Must-have Requirements
Bachelor's degree in Computer Science, Robotics, AI, Mechatronics, Electronics, or related fields.
1-3+ years of hands-on experience with ROS / ROS2.
Proficiency in Python and/or C++ in robotics environments.
Experience in one or more of the following areas:
- Image processing: OpenCV, image processing pipeline
- Deep learning: TensorFlow / PyTorch
- Computer vision: object detection, segmentation, tracking
Good understanding of robotic systems: SLAM, navigation, motion planning, control.
Ability to read and understand technical documents in English.
3. Nice-to-have
Experience with NVIDIA Jetson, CUDA, or AI acceleration.
Knowledge of Docker, Linux, and CI/CD pipelines.
Experience working on real robotics projects (AGV, AMR, robotic arms, etc.).
Having a GitHub, personal projects, or simulations.
Quyền lợi
4. Benefits
Competitive salary based on market standards.
Opportunity to work on international projects using advanced Robotics/AI technologies.
Direct training and mentorship from Japanese experts.
Flexible working environment with a clear technical career path.
Thông tin khác
Thời gian làm việc
Thứ 2 - Thứ 6 (từ 08:00 đến 17:00)
Thông tin chung
Nơi làm việc
- - Hồ Chí Minh: Tầng 02, số 07 đường Lý Tự Trọng, Phường Sài Gòn
Cách thức ứng tuyển
Ứng viên nộp hồ sơ trực tuyến bằng cách bấm nút Ứng tuyển bên dưới:
Hạn nộp: 04/01/2026
