Deep Learning Algorithms Specialist

Unitree Robotics - HangZhou YuShu TECHNOLOGY CO.,LTD

Location

China

Vacancy for

Human

Employment type

Full-time

Necessary education

Not matter

Employer provided salary

840000¥ per year

Posted at 18.10.2025

Description

Requirements

1. Familiar with cutting-edge developments in the field of learning-based control；

2. Understanding the dynamics of multi-degree-of-freedom underdrive robots；

3. Familiar with the use of programming languages such as C++ and Python, familiar with mainstream deep learning frameworks such as pytorch/tensorflow, and understand frameworks such as ROS；

4. Familiar with mainstream robot simulation software, such as NVIDIA Isaac Sim, mujoco, raisim, gazebo, pybullet, vrep, etc.；

5. Understand commonly used deep reinforcement learning algorithms (PPO, SAC, DQN, DDPG, A3C, etc.)；

6. Experience in in-depth intensive learning research projects applied to robots；

Needed key skills

  • Algorithms
  • Artificial Intelligence (AI)
  • C/C++
  • Engineering
  • Problem-solving skills
  • Programming skills
  • Python
  • Research skills
  • Technology trend awareness

Bonuses

- Participation in cutting-edge research and development in the field of deep reinforcement learning and robotics - Hands-on experience with real-world robotic systems, including two-legged and four-legged bionic robots - Opportunity to work with advanced simulation platforms, such as NVIDIA Isaac Sim, Mujoco, Raisim, Gazebo, PyBullet, and V-REP - Exposure to state-of-the-art deep learning frameworks, including PyTorch and TensorFlow - Involvement in high-impact AI projects with applications in intelligent control and autonomous decision-making - Collaboration with leading experts in robotics, control systems, and artificial intelligence - Opportunity to contribute to top-tier academic publications in AI and robotics (e.g., RSS, ICRA, IROS, CoRL, RAL) - Dynamic and research-driven work environment within a dedicated R&D department - Professional growth through interdisciplinary collaboration

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