Summer 2027 PhD ML Systems Research Engineering Intern

Develop and optimize infrastructure for distributed training, reinforcement learning, inference, and model optimization. Build scalable systems for experiment management, rollout generation, model serving, and evaluation, improving efficiency through parallelism, scheduling, checkpointing, caching, and performance tuning. Create tools integrating AI models with engineering systems, evaluation pipelines, and benchmarking frameworks, and support experiment tracking, logging, monitoring, and reproducibility. Analyze system performance and document designs and results.