Helix AI Engineer Reinforcement Learning
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Figure is an AI robotics company developing general-purpose humanoid robots and its Helix vision-language-action AI system.
San Jose, United States
Funding history
About Figure
Figure develops and deploys general-purpose humanoid robots for commercial and household tasks. Its current Figure 03 robot is powered by Helix, an onboard generalist vision-language-action model; the company also operates the Index data-collection service.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design, implement, train, and evaluate reinforcement learning systems for embodied agents in simulated and real-world environments. You will improve policy robustness, reward modeling, exploration, distributed training, and evaluation frameworks.
Requirements
- Experience developing and applying reinforcement learning algorithms in complex environments
- Understanding of policy optimization, value methods, and model-based reinforcement learning
- Experience training policies in simulation or real-world systems
- Proficiency in Python and PyTorch
- Experience with large-scale experimentation and distributed training systems
- Experimental rigor in diagnosing and improving learning systems
- Software engineering skills for scalable, reliable systems
Responsibilities
- Design and implement reinforcement learning algorithms for embodied agents
- Train policies using interaction, feedback, and large-scale experience
- Develop reward modeling, credit assignment, and exploration strategies
- Improve policy robustness to noise, partial observability, and environment variability
- Work across online and offline reinforcement learning settings
- Build scalable distributed rollout, simulation, and experiment-management systems
- Design evaluation frameworks for policy performance, stability, and generalization