Senior Reinforcement Learning Engineer - Apptronik

Key Responsibilities

• Design, implement, and evaluate reinforcement‑learning pipelines for high‑dimensional robot control tasks.
• Integrate learning algorithms with ROS‑based perception and control stacks on the humanoid platform.
• Develop realistic simulation environments and domain‑randomization techniques to bridge the sim‑to‑real gap.
• Collaborate with hardware, safety, and product teams to ensure algorithms meet real‑world safety and reliability standards.
• Optimize code for performance on embedded compute resources using C++ and Python.

Requirements

• 5+ years of experience in reinforcement learning or advanced machine‑learning research applied to robotics.
• Strong programming skills in Python and C++, with hands‑on experience in ROS.
• Proficiency with deep‑learning frameworks such as TensorFlow or PyTorch.
• Demonstrated ability to build and tune high‑fidelity simulation environments (e.g., Gazebo, Isaac Sim).
• Track record of publishing or delivering production‑grade RL solutions in complex, safety‑critical systems.