Apptronik
Senior Reinforcement Learning Engineer
Austin, TX · Senior · Full-time · Posted Feb 26, 2026
- Experience
- 5+ years with RL frameworks and simulators; 2+ years of industry experience is strongly preferred.
- Education
- PhD or MS in Computer Science, Robotics, or a related field.
About the job
Develop and deploy reinforcement-learning systems for humanoid robot locomotion and manipulation, transferring policies from simulation to physical hardware.
What you'll do
- Implement, test, and deploy RL algorithms and optimize distributed training and simulation pipelines.
- Transfer and fine-tune policies on robots; collaborate with robotics and hardware teams to resolve system-level issues.
- Mentor engineers and develop motion-retargeting pipelines from human demonstration data.
What they ask for
- 5+ years of hands-on experience with RL frameworks and high-fidelity physics simulators.
- Mastery of Python and strong proficiency in C++.
- Experience building or using large-scale distributed training pipelines.
- Strong understanding of modern RL, robot dynamics, and controls, with experience deploying learned policies on physical robots.
Nice to have
- PhD or MS in Computer Science, Robotics, or a related field, with 2+ years of industry experience strongly preferred.
- Relevant publications (e.g., CoRL, RSS, ICRA) are a significant plus.
Tools
PyTorch, JAX, MuJoCo, IsaacGym, Python, C++
AI focus
Applies reinforcement learning, imitation learning, and sim-to-real transfer to humanoid robot locomotion and manipulation; includes motion retargeting from demonstrations and deployment on physical robots.
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