Lead Reinforcement Learning Engineer - Humanoid Robotics

Figureai; San Jose (CA); On-site; USD 200,000 - 350,000; Full time

Job summary

Figureai in San Jose, CA is seeking a Reinforcement Learning Engineer to develop and train algorithms for the control of humanoid robots. You will work on improving performance and ensuring robust control systems through innovative RL techniques.

The ideal candidate should have experience in dynamics, control, and robotics, along with the ability to mentor others. A competitive salary between $200,000 and $350,000 annually is offered for this role.

Qualifications

• Strong background in dynamics and control, ideally of legged robots.
• Experience with reinforcement learning algorithms for robotics: PPO, SAC, etc.
• Experience tuning hyperparameters and cost functions for these RL algorithms.
• Familiarity with common RL techniques such as domain randomization and reward shaping.

Responsibilities

• Develop, train, and deploy reinforcement learning algorithms for whole body control.
• Determine observations, actions, and model types for maximum performance.
• Identify and close important sim-to-real gaps.
• Define, test, and evaluate performance metrics for learned policies.
• Harden the control stack for robustness.

Skills

Dynamic systems control

Reinforcement Learning algorithms

Hyperparameter tuning

Mentoring

Job description

Figureai in San Jose, CA is seeking a Reinforcement Learning Engineer to develop and train algorithms for the control of humanoid robots. You will work on improving performance and ensuring robust control systems through innovative RL techniques.

The ideal candidate should have experience in dynamics, control, and robotics, along with the ability to mentor others. A competitive salary between $200,000 and $350,000 annually is offered for this role.