Tech Stack

Description

You will conduct research on reinforcement learning for robotics and autonomous systems, focusing on large-scale closed-loop RL and VLA post-training for dexterous manipulation. You will publish at top conferences and collaborate with engineers to deploy algorithms into real-world products.

Requirements

• Strong research record in RL and VLA post-training for robotics and autonomous systems
• Publications in top-tier conferences or journals in computer vision, machine learning, and robotics
• MSc or PhD in machine learning and computer vision with autonomy and robotics applications or closely-related fields
• Passion for next-generation, scalable autonomy and robotics for real-world systems
• Technical experience in Python, PyTorch, computer vision, robotics systems, and distributed machine learning model training

Responsibilities

• Conduct research on reinforcement learning related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation
• Dive into fundamental and relevant topics on RL with broader applications
• Work closely with other research scientists and interns on research publications for submission to top-tier conferences
• Collaborate with research engineers and engineering teams to test and deploy algorithms to autonomy and robotics products