Our company is actively hiring for a Humanoid Robot Reinforcement Learning Algorithm Engineer, offering exceptional employment opportunities in cutting-edge robotics research. We are looking for talented professionals to develop advanced RL algorithms and VLA models for humanoid robot control and task planning. This position provides the chance to work on full-stack development from simulation to real-world deployment while collaborating with cross-functional teams. If you're searching for impactful careers in robotics AI, this represents one of the most exciting job openings in the industry.

The ideal candidate should meet the following requirements:

1. Including but not limited to computer, information engineering, pattern recognition, artificial intelligence, automation, software engineering, electronic engineering, statistics, applied mathematics, signal and information processing and other majors；
2. In-depth understanding of reinforcement learning theory, familiar with mainstream algorithms such as Q-learning, PPO, DDPG, GRPO, etc., and rich experience in the development of reinforcement learning models; in-depth understanding and research of VLA models; familiar with large-model training, fine-tuning, deployment and other technologies；
3. Extra points: Have experience in simulation environment and application on real robots, be able to skillfully use robot simulation tools such as Isaac Sim, Mujoco, etc., be familiar with ROS or other robot development frameworks, and have experience in development and debugging on real robot platforms (such as industrial robots, mobile robots, service robots, etc.)；
4. Bonus 2: Familiar with the deployment process of end-side machines, proficient in Python and C++, have good code development and debugging capabilities, familiar with TensorFlow Lite, ONNX Runtime or other lightweight frameworks, and have the ability to optimize and deploy enhanced learning algorithms on embedded devices or low-computing platforms.；

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