Apptronik
Senior Reinforcement Learning Engineer
$230K–$260K
Sunnyvale, CA +1 · Senior · Full-time · Posted Aug 12, 2026
- Location
- Sunnyvale, CA
Austin, TX - Experience
- 5+ years with RL frameworks and simulators; 2+ years of industry experience is strongly preferred.
- Education
- A PhD or MS in Computer Science, Robotics, or a related field.
About the job
Develop and deploy reinforcement-learning policies for humanoid locomotion and manipulation, transferring them from simulation to physical robots and mentoring junior engineers.
What you'll do
- Implement and deploy RL algorithms for locomotion and manipulation on physical hardware; transfer and fine-tune policies from simulation.
- Scale RL training infrastructure and develop motion-retargeting pipelines using human demonstration data.
- Collaborate with robotics and hardware teams, analyze results, and mentor junior engineers.
What they ask for
- 5+ years of hands-on expertise 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 reinforcement learning, robot dynamics, and controls.
Nice to have
- PhD or MS in Computer Science, Robotics, or a related field, with 2+ years of industry experience strongly preferred.
- Strong publication record in relevant conferences or journals (e.g., CoRL, RSS, ICRA).
Pay
$230,000 - $260,000 USD annual compensation; base salary or total pay not specified.
Tools
PyTorch, JAX, MuJoCo, IsaacGym, Python, C++
AI focus
Apply reinforcement learning to humanoid locomotion and manipulation, including imitation learning, model-based RL, sim-to-real transfer, and learning from human demonstrations.
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