Helix AI Engineer, Reinforcement Learning
Core
Developing core AI systems for autonomous humanoid robots using reinforcement learning to enable skill acquisition through interaction and experience.
Role type
Senior IC reinforcement learning engineer (robotics)
Builds
Embodied AI systems capable of perceiving, reasoning, and acting in the real world
Domain
Robotics + Reinforcement Learning
Deliverable
production ML models
Required skills
Reinforcement learning algorithms, policy optimization, value methods, model-based RL, Python, PyTorch, distributed training systems, large-scale experimentation, software engineering, system scalability
Preferred skills
Robotics control systems, offline RL, imitation learning, reward modeling, human-in-the-loop learning, simulation infrastructure, publication record in RL/robotics
Technologies
PyTorch, Python, simulation environments
Responsibilities
Design and implement RL algorithms for embodied agents in real-world and simulated environments; Train policies learning from interaction and large-scale experience; Develop reward modeling and exploration strategies for long-horizon behaviors; Improve policy robustness to noise and partial observability; Work across online and offline RL settings with logged robot data; Build scalable training systems including distributed rollouts and simulation infrastructure; Design evaluation frameworks for policy performance and generalization
Seniority
Senior, hands-on IC