Design, implement, and test learning-based algorithms, and deploy them on complex robots (e.g., humanoids, robotic arms, robotic hands) to perform manipulation tasks in kitchen environments.
Design and maintain a scalable deep learning pipeline for training large-scale robotic datasets, ensuring the system is efficient, stable, and flexible.
Collaborate with cross-functional teams to develop and continuously improve the full autonomy stack.
Engage in cutting-edge research to bring innovative insights to the team and help solve various complex issues in deployment.
Requirements
Master’s or Ph.D. degree in robotics, computer science, or related fields, or equivalent industry experience.
Proficiency in programming languages such as Python, with practical experience using machine learning frameworks like TensorFlow, PyTorch, or JAX.
Hands-on experience in developing, tuning, and evaluating ML models.
Experience training and deploying reinforcement learning or imitation learning algorithms on high-degree-of-freedom robots.
Familiarity with GPU acceleration technologies such as CUDA, TensorRT, model quantization, and compression.
Proficient in mainstream robot simulation tools (e.g., Isaac Sim, Mujoco, Drake, Gazebo) and their use in development workflows.
Bonus Qualifications
Experience with ROS / ROS2 development or similar robotic framework.
Practical experience in developing and deploying algorithms on high-DOF robots.
Familiarity with the use and integration of multimodal sensors (e.g., force, tactile, visual sensors).
Experience with robotic motion planning and trajectory optimization algorithms.
Preference given to candidates who have published papers or obtained patents in relevant international conferences (e.g., RSS, ICRA, IROS).
Benefits
Located in the center of the city: Just across the street from Dongmen MRT Station exit 6.
Competitive salary: Compensation packages aligned with global Tier-1 cities.
Incentives: Long term incentive plans currently under development. Coming soon.
Performance bonuses: Awarded based on annual company performance and individual contribution.
Insurance coverage: Labor, health, pension, occupational injury... etc.
Flexible hours: Flexible start and end times to support work-life balance.
Hybrid work: Option to work remotely 2 days a week.
Legal benefits coverage: Includes labor insurance, national health insurance, pension contributions, occupational injury protection, special leave, and marriage leave.
Learning support: Tuition subsidies available for approved external training or professional development programs.
In-house culinary workshops: Team cooking sessions for fun and learning the way of the wok.
