Research Scientist / Engineer – Training Infrastructure

You'll build the distributed systems that train Luma's large-scale multimodal models across thousands of GPUs, so researchers can focus on innovation on top of reliable, efficient, scalable infrastructure.

This is hard PyTorch, CUDA, and distributed-systems work — advanced parallelism, training stability, and utilization across massive clusters. It fits an engineer who's solved real problems training foundation models at scale. If you haven't worked at the level of FSDP and multi-node training, this is the wrong depth.

• Design, implement, and optimize efficient distributed training systems for models across thousands of GPUs.