Internships

System Intern (Robotics Direction)

Beijing

Internship

Robotics System Direction

Undergraduate/Master's student

Job Description

We hope you will participate in the development, experimentation, and research support work related to robotic systems. This position leans more towards "truly putting research into systems," and is suitable for students interested in robotics, engineering practice, hardware-software collaboration, and implementing research. You will work with the team to advance system construction, experimental verification, and iterative optimization on real robotic platforms.

Participate in the construction, debugging, maintenance, and iteration of robotic systems, supporting the daily progress of research projects and experimental platforms.
Engage in hardware-software collaboration, assisting in the integration between computing platforms, sensors, actuators, communication links, and software modules.
Collaborate with algorithm colleagues to deploy, test, and validate models and algorithms in real robotic systems, promoting the establishment of experimental closed loops.
Participate in the development and optimization of modules related to ROS, low-level communication, data links, and task scheduling to improve system stability and experimental efficiency.
Participate in on-site debugging, problem localization, and boundary issue investigation on the real robot platform, supporting continuous system improvement.
According to project needs, participate in the implementation of certain equipment control, kinematics/dynamics related modules, or lightweight control frameworks.

Strong learning ability, with a sustained interest in algorithms, mathematics, and robotics, able to quickly get into new research and engineering problems.
Possess a solid foundation in programming and basic software engineering skills, capable of independently completing development, debugging, and problem diagnosis.
Has certain research or engineering practice experience in robotics, and has been exposed to real robotic platforms, hardware systems, or related experimental environments.
Possess certain experience in mathematical modeling, have participated in mathematical modeling competitions, research training, or have modeling practice of equivalent intensity.
Familiar with modern AI-assisted development workflows, with practical experience using tools such as Codex, Claude Code, and Gemini CLI.
Basic understanding of embodied AI; familiarity with models or frameworks such as VLA and OpenVLA; ability to read related papers, code, and experiment configurations; and awareness of deployment requirements in real systems.
Have a basic understanding of common modules in robotic systems, such as ROS, ZMQ, CAN, multithreading/multiprocessing, Linux environment debugging, control and communication links, etc., and have had actual experience with at least some of them.
Possess strong hands-on skills and a sense of teamwork, able to accept system integration, experimental troubleshooting, and repeated iterations.

Personally built a complete robot or a complete robotic system, rather than just participating in one particular module of it.
Has experience in publishing papers, writing technical reports, or producing relatively complete scientific research outputs.
Have participated in robotics competitions such as RoboMaster (RM), and have taken on core roles in system integration, debugging, or implementation.
Has long-term debugging, experimentation, and iteration experience on real robot platforms, not just experience in simulation environments.

Submit your application below and our team will review your resume shortly.