Figure AI

AI Engineer focused on developing core model architectures and learning approaches for humanoid robot autonomy, spanning perception, reasoning, and action across multimodal inputs. The role involves designing, training, and deploying models, with a focus on advancing multimodal learning and generalization for embodied AI systems.

Figure AI is seeking a Helix AI Engineer specializing in Reinforcement Learning to develop learning systems for humanoid robots. This role involves designing, implementing, and training RL algorithms for embodied agents in both simulated and real-world environments, focusing on improving policy performance, robustness, and long-horizon decision-making. The engineer will work on reward modeling, credit assignment, exploration, and integrating RL into the full autonomy stack, while also building scalable training systems and evaluation frameworks.

AI Engineer focused on post-training of large AI models for humanoid robotics, involving fine-tuning, optimization, evaluation, and safety, with a secondary focus on integrating these models into agentic systems for real-world applications.