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Senior Staff/ Principal Research Scientist – Dexterous Manipulation

ChinaChina·Shenzhensenior
Data ScientistResearch ScientistDataData & AI
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Quick Summary

Overview

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing ( eVTOL ) aircraft, and robotics.

Key Responsibilities

Design, implement, and deploy advanced manipulation algorithms for humanoid robot dexterous hands, spanning teleoperation, force control, and reinforcement learning .

Requirements Summary

Hands-on experience with mainstream reinforcement learning or imitation learning frameworks. Proven ability to build complex simulations using Isaac Gym/Isaac Lab or similar platforms.

Technical Tools
cppdockerpythonlinuxmachine-learning

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.

Key Responsibilities:
  • Design, implement, and deploy advanced manipulation algorithms for humanoid robot dexterous hands, spanning teleoperation, force control, and reinforcement learning.
  • Develop and maintain high-fidelity simulation environments for robot kinematics, dynamics, sensor emulation, and physical interaction.
  • Research and innovate on state-of-the-art reinforcement learning algorithms to solve complex robotic manipulation tasks.
  • Diagnose and tackle core technical challenges that arise during specific robot task execution.
 
Basic Qualifications:
  • M.S. or Ph.D. in Robotics, Computer Science, Artificial Intelligence, or a related field.
  • Strong foundation in robot dynamics, kinematics, and optimal control, with excellent mathematical skills.
  • Proficiency in Linux, Docker, C++, and Python. Experience with git and a commitment to writing clean, maintainable code.
  • A collaborative mindset, intellectual curiosity, and humility in a fast-paced team environment.
  • Demonstrated ability to independently research and master new algorithms and technologies.
 
Preferred Qualifications:
  • Hands-on experience with mainstream reinforcement learning or imitation learning frameworks.
  • Proven ability to build complex simulations using Isaac Gym/Isaac Lab or similar platforms.
  • Experience with tactile sensing and its integration in dexterous manipulation.
  • Practical experience in sim2real transfer for robotics.
  • Experience in controlling multi-joint robotic systems.
  • Publications in top-tier robotics or AI conferences (e.g., RSS, ICRA, IROS, CoRL, NeurIPS, CVPR) or journals (e.g., IJRR, TRO, T-RO, RA-L).

 

What do we provide:
  • A fun, supportive and engaging environment.
  • Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving.
  • Opportunity to work on cutting edge technologies with the top talent in the field.
  • Competitive compensation package.
  • Snacks, lunches and fun activities.

 

We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

Location & Eligibility

Where is the job
Shenzhen, China
On-site at the office
Who can apply
CN
Listed under
China

Listing Details

Posted
April 23, 2026
First seen
April 23, 2026
Last seen
May 26, 2026

Posting Health

Days active
31
Repost count
0
Trust Level
23%
Scored at
May 24, 2026

Signal breakdown

freshnesssource trustcontent trustemployer trust
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Senior Staff/ Principal Research Scientist – Dexterous Manipulation