Robotics AI Engineer: Real-World RL for Humanoid Robots

Auxo Talent; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Auxo Talent is seeking a Robotics AI Engineer to work at the intersection of learning and hardware on a humanoid platform. You will train and deploy policies that run on our client’s robots in the real world, iterating quickly when things break and closing the loop with hardware, firmware, and infrastructure teams.

You will design RL/IL policies for locomotion, manipulation, or whole-body control, run experiments on physical robots, and build data pipelines to support rapid iteration.

Qualifications

• Strong foundations in reinforcement learning or imitation learning with hands-on experience.
• Comfort working directly with robots, not just simulators.
• Proficiency in Python and familiarity with standard RL/ML frameworks.

Responsibilities

• Design and train RL and imitation learning policies for locomotion, manipulation, or whole-body control.
• Run experiments on physical hardware and close the sim-to-real gap through systematic debugging.
• Build and maintain simulation environments and data pipelines to support fast policy iteration.
• Instrument robot deployments and analyze failure modes to feed improvements back into training.
• Collaborate with hardware and firmware engineers to understand physical constraints and improve policy robustness.

Skills

Reinforcement learning

Imitation learning

Robotics

Python programming

Experimentation

Tools

PyTorch

TensorFlow

ROS

Gym

Job description

Auxo Talent is seeking a Robotics AI Engineer to work at the intersection of learning and hardware on a humanoid platform. You will train and deploy policies that run on our client’s robots in the real world, iterating quickly when things break and closing the loop with hardware, firmware, and infrastructure teams.

You will design RL/IL policies for locomotion, manipulation, or whole-body control, run experiments on physical robots, and build data pipelines to support rapid iteration.