Lead the design, training, evaluation, and deployment of large-scale machine learning models, including LLMs, diffusion models, and GNNs. Own distributed training pipelines, dataset interfaces, optimization strategies, model evaluation, serving, and lifecycle management. Collaborate with data, infrastructure, and scientific teams while providing technical leadership through architecture reviews, mentorship, and cross-functional decision-making.

Lead design, training, and deployment of large-scale ML models (LLMs, diffusion, GNNs). Own end-to-end training pipelines, distributed training, evaluation, and inference architecture. Collaborate with data and infra teams, drive reproducible model development, and provide technical leadership and mentorship from research through production.