Reinforcement Learning Engineer Humanoid Robotics Autonomy

Figureai; San Jose (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Figureai, based in San Jose, CA, is seeking a Helix AI Engineer with expertise in Reinforcement Learning to advance humanoid robot autonomy. The role involves designing and implementing RL systems that enable robots to learn and improve through interaction and experience.

Responsibilities include algorithm development across simulated and real-world environments, ensuring robust policy performance. Ideal candidates should have a strong background in RL and relevant software engineering skills, and be prepared to work collaboratively in an office setting.

Qualifications

• Experience developing and applying reinforcement learning algorithms in complex environments.
• Strong understanding of RL fundamentals like policy optimization and value methods.
• Experience training policies in simulation and/or real-world systems.
• Proficiency in Python and deep learning frameworks such as PyTorch.

Responsibilities

• Design and implement reinforcement learning algorithms for embodied agents.
• Train policies that learn from feedback and large-scale experience.
• Develop reward modeling and credit assignment strategies.
• Improve policy robustness to real-world challenges.

Skills

Reinforcement Learning

Python

Deep Learning Frameworks

Experimental Rigor

Software Engineering Skills

Job description

Figureai, based in San Jose, CA, is seeking a Helix AI Engineer with expertise in Reinforcement Learning to advance humanoid robot autonomy. The role involves designing and implementing RL systems that enable robots to learn and improve through interaction and experience.

Responsibilities include algorithm development across simulated and real-world environments, ensuring robust policy performance. Ideal candidates should have a strong background in RL and relevant software engineering skills, and be prepared to work collaboratively in an office setting.