Senior Software Engineer, RL Post-Training Frameworks
This role involves designing and building scalable reinforcement learning (RL) post-training infrastructure that supports the full lifecycle of training, inference, and rollout across heterogeneous hardware. You'll contribute to open-source RL frameworks, optimize distributed systems for performance and fault tolerance, and collaborate with AI researchers, infrastructure teams, and hardware engineers to enable next-generation AI capabilities. The work spans deep integration with PyTorch, Kubernetes, and distributed runtimes like Ray and Monarch, focusing on real-world challenges in large-scale RL deployment.