Example Research Directions You may work on one or more of the following areas, depending on background and project fit: Distributed Training, Post-Training, and RL Systems Study the systems challenges behind large-scale model development pipelines, including communication bottlenecks, cluster efficiency, scheduling, checkpointing, rollout infrastructure, and resource orchestration for RL and post-training workloads. Storage, Networking, and Observability for AI Workloads Develop system designs for high-performance storage, cluster networking, observability, fault localization, and root cause analysis in large-scale AI environments where training and serving workloads operate under tight performance constraints.