Backed by Entrepreneur First.
About the role
We are looking for an engineer who will own the full locomotion and whole-body control stack for our humanoid robot. Your work will directly shape the robot’s ability to walk, balance, and move safely and smoothly in the real world. This is a highly hands-on role. You will spend your time building training pipelines in simulation, iterating on RL and IL policies, transferring them to hardware, and debugging behavior on real robots.
What they're looking for
- Reinforcement Learning
- Isaac Lab , Isaac Gym, MuJoCo, or similar physics simulators
- Building training pipelines with PyTorch
- Deploying policies on embedded or GPU-accelerated systems (C++/Python/JAX/etc)
- Whole-body control, locomotion control, or quadruped/humanoid robotics
- Working with real robots — debugging hardware, evaluating behavior, collecting rollouts
More about this role
We are looking for an engineer who will own the full locomotion and whole-body control stack for our humanoid robot. Your work will directly shape the robot’s ability to walk, balance, and move safely and smoothly in the real world.
This is a highly hands-on role. You will spend your time building training pipelines in simulation, iterating on RL and IL policies, transferring them to hardware, and debugging behavior on real robots.
Develop, train, and evaluate RL and IL policies for whole-body control and locomotion.
Build and optimize training pipelines in Isaac Lab and real-time inference pipelines on robot hardware.
- Drive sim-to-real transfer , including domain randomization, curriculum design, and iterative policy refinement.
- Work directly with hardware to diagnose failures, tune controllers, gather datasets, and improve stability and performance.
- Own experiments end-to-end: from idea → prototype → simulation → real robot deployment.
- Collaborate on motion, control, perception, and high-level planning systems as we scale capabilities.
We’re looking for someone who is both a strong RL engineer and a practical roboticist—someone who enjoys seeing their work running on a...
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