Senior RL Engineer – Humanoid Robotics, Sim-to-Real

The Robot Age; Sunnyvale (CA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Apptronik in Sunnyvale, CA is seeking a senior reinforcement learning engineer to advance learned locomotion and manipulation on the Apollo humanoid platform.

You will build and deploy RL policies, run sim-to-real loops, and mentor teammates while improving training pipelines and high-throughput simulation.

This role emphasizes hands-on implementation and collaboration across autonomy, controls, and hardware teams.

Qualifications

• Senior-level experience with reinforcement learning for robotics.
• Strong sense of sim-to-real transfer and hardware testing constraints.
• Ability to build reliable model-training and evaluation pipelines.
• Collaborative mindset across autonomy, controls, and hardware teams.

Responsibilities

• Build and deploy reinforcement learning policies for humanoid robot behavior.
• Run the loop from simulation experiments to physical hardware results.
• Improve distributed training and high-throughput simulation workflows.
• Mentor teammates working on embodied learning problems.

Skills

Reinforcement learning

Robotics

Collaboration

Mentoring

Job description

Apptronik in Sunnyvale, CA is seeking a senior reinforcement learning engineer to advance learned locomotion and manipulation on the Apollo humanoid platform.

You will build and deploy RL policies, run sim-to-real loops, and mentor teammates while improving training pipelines and high-throughput simulation.

This role emphasizes hands-on implementation and collaboration across autonomy, controls, and hardware teams.