Distributed Training Engineer for Large-Scale GPU Clusters

Luma seeks an engineer to build and optimize distributed training systems for multimodal models across thousands of GPUs. You will tackle advanced parallelism, training stability, and utilization across massive clusters to empower researchers with reliable, scalable infrastructure.

This role focuses on real problems at scale, including FSDP, multi-node training, and efficient communication. You will develop monitoring tools and automation to keep large runs stable and productive.