VinMotion

Key Responsibilities:

• Design, implement, test, and deploy manipulation algorithms for humanoid robots with high degree of freedom, highly dexterous hands, including grasping, picking and placing, bimanual manipulation, visual and tactile servoing, and assembly
• Train deep learning models for manipulation that are robust to uncertainty, sensor noise, and partial information
• Collaborate with other team members to develop toward a full autonomy stack
• Define performance metrics, test learned policies, and evaluate their effectiveness in real-world scenarios.

Requirements:

• Bachelor’s or Master’s, PhD’s degree in computer science, AI, Mechatronics, Control Engineering – Automation, or a related field
• Proficiency in writing production-quality code using PyTorch/Tensorflow/JAX.
• Familiarity with online and offline RL algorithms, such as PPO and SAC.
• Familiarity with simulation technologies (e.g., IsaacGym, IsaacLab, Mujoco)
• Experience in tuning hyperparameters, reward engineering, and optimizing RL training processes.
• Understand both traditional and machine learning approaches to robot manipulation, and the tradeoffs between various techniques
• Understanding of the latestest development and framework in RL for manipulation

Preferred Qualifications:

• Hands-on experience with manipulation tasks and project
• Experience with deploying real world robot manipulation solutions
• Publication in related field