This role is for a software engineer in the Distributed Training team for AWS Neuron. This role is responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive scale multi-modal large language models like Llama, Qwen, gpt-oss, DeepSeek and beyond, as well as multi-modal generation models such as Stable Diffusion, Flux, WAN, and many more.

This role will help lead efforts to optimize distributed training performance on Trainium, with a primary focus on maximizing training throughput, model flops utilization, and efficiency across the Neuron software stack. You will work across PyTorch, JAX, and the Neuron compiler and runtime to enable and tune large-scale training workloads on the latest Trainium instances.