Driven by intelligence for a better future,
gathering talents at Noetix Robotics

1. Responsible for the research and application of quadruped/wheeled motion control algorithms based on reinforcement learning;

2. Implement, modify and optimize algorithms according to actual project requirements to solve practical problems;

3. Research cutting-edge robot reinforcement learning and imitation learning algorithms.

1. Familiar with programming languages such as Python, Pytorch and familiar with Linux operating systems;

Familiar with deep learning (MLP, CNN, RNN, transformer, etc.) algorithms and have knowledge of reinforcement learning (Q-Learning, PPO) algorithms;

2. Understanding of mainstream robot simulation platforms like IsaacGym, Isaaclab, Mujoco, Pybullet, etc.;

3. Good communication skills, excellent learning ability, strong analytical and practical problem-solving skills, hands-on ability and interest in motion control;

4. 0-2 years of work experience.

Preferred: Experience in robot control tasks based on reinforcement learning and imitation learning; having papers in top conferences or journals in the robot/learning field.

1. Responsible for the development of biped motion control algorithms based on reinforcement learning and exploring algorithmic performance limits (potential for nurturing from 0 to 1);

2. Analyze robot structures using knowledge of robotics kinematics, dynamics and control theory and propose improvement suggestions;

3. Implement, modify and optimize algorithms based on actual project requirements;

4. Continuously research the latest reinforcement learning and imitation learning algorithms.

1. Background in robotics, mechanical automation, electronic information or related fields, with a master's degree or higher;

2. Mastery of robotics dynamics, optimization theory, convex optimization, variational methods, numerical computing and related knowledge;

3. Familiar with traditional control (PID, LQR, impedance control, etc.), optimal control (MPC, etc.);

4. Proficient in C++/Python, familiar with ROS/ROS2, Pinocchio, CasADi and other ecological tools;

5. Knowledgeable in robot simulation environments such as MuJoCo, Isaac Gym, Gazebo and PyBullet;

6. Experience in robot control tasks based on reinforcement and imitation learning is preferred.

1. Responsible for dynamic modeling and parameter identification of various components of humanoid robots, verifying and correcting robot model files;

2. Based on the corrected robot model, conduct dynamic modeling and optimal control resolution, collaborating with colleagues on robot motion control algorithms for model validation on actual platforms;

3. Construct and write robot control-related SDKs for internal colleagues or clients;

4. Provide improvement suggestions for the mechanical and electrical design of robots based on dynamic model validation results and participate in tuning.

1. Master's degree or higher in robotics, mechanical, control, automation, computer science, or related fields;

2. More than 2 years of relevant work experience, with experience in the development of serial robotic arms or legged robots;

3. Proficient in robotics, multi-body dynamics, parameter identification and force-position hybrid control, familiar with simulation modeling to evaluate kinematic and dynamic indicators, including dynamic response performance, torque, tracking accuracy and error compensation, with relevant project experience;

4. Mastery of nonlinear optimization, convex optimization and other optimal control theories, having used related solvers to solve robotic control problems;

5. Proficient in classical control theory and modern control theory, familiar with ROS-based C/C++ programming and Python programming;

6. Skilled in using physical simulation platforms such as Gazebo, MuJoCo, Simulink for robot simulation and modeling and have validated algorithms.

1. Responsible for the research and optimization of motion planning algorithms for six-axis or seven-axis robotic arms;

2. Identify and resolve technical issues encountered during algorithm development, providing constructive suggestions and improvement directions for the collaborative design of the body and algorithms based on the motion characteristics of the robotic arm.

1. Master's degree or higher in Control, Robotics, Mechatronics, or related fields; experience in developing algorithms related to well-known robotic arm SDKs, with rich practical debugging experience, preferably with over 2 years of development experience;

2. Familiarity with at least one solver library such as Pinocchio, KDL, IF-Fast, TRAC-IK;

3. Understanding of singularity avoidance techniques for redundant robotic arms and commonly used iterative methods for forward kinematics;

4. Familiarity with common communication methods for robotic arms, such as UDP, ZMQ, LCM, DDS, etc., at least one;

5. Proficient in C++ and ROS1/2 framework;

6. Familiar with the principles of motor control for robotic arms, knowledge of trajectory planning, Kalman filtering, PID control, gravity compensation and familiarity with parameter identification and vibration suppression techniques is a plus;

7. Possesses good teamwork spirit and communication skills.

1. Responsible for the software development of control algorithms for brushless/brushed motor drivers, including model simulation, algorithm design, functional design, software coding and debugging;

2. Develop test plans and test specification documents and complete testing work;

3. Analyze and resolve issues raised during the R&D, testing, production and after-sales phases of new products and optimize solutions.

1. Bachelor's degree or higher in Electronic Engineering, Automation, Electrical Engineering, or related fields;

2. Familiar with C language and STM32 microcontrollers, understanding the ARM architecture of Cortex M cores;

3. Knowledge of motor control theories and methods, including PID control, vector control and direct torque control;

4. Familiar with MATLAB/Simulink simulations, capable of modeling and simulating motor drive control;

5. Over 3 years of experience in motor control algorithm development, with a preference for experience in robotics and automation equipment;

6. Familiarity with industrial bus protocols such as Ethercat and CAN is a plus;

7. Experience in integrated joint module project development is preferred.

1. Deeply understand product requirements, complete software framework design and integration for the product;

2. Design and develop SDKs and solutions for embedded products;

3. Develop applications for the Linux system to meet the product's functionality, performance and power consumption requirements;

4. Solve difficult issues in the system, including but not limited to: stability, performance, power consumption, etc.;

5. Have a thorough understanding of the product and participate in the entire lifecycle of product development, including requirement definition, design, implementation, testing, production, maintenance, etc.

1. Bachelor's degree or higher in EE, CE, CS, or a related field, with over 3 years of embedded software development experience;

2. Proficient in C/C++ programming, with independent design and development capabilities, good at solving difficult problems;

3. Familiar with Linux operating systems, understand operating system principles and have application development experience;

4. Familiar with Linux debugging tools, memory management, threading, task scheduling and experience in concurrent programming;

5. Familiar with software development for sensors such as Camera/Lidar/remote control;

6. Knowledge of classical control principles and practical experience, familiar with embedded control system development, proficient in STM32 and C language;

7. Familiar with the ROS2 framework;

8. Understanding of EtherCAT and CAN communication protocols, with relevant project experience.