About this role
We develop AWS Neuron, the complete software stack for Trainium, Amazon's custom cloud-scale machine learning accelerators. Join us to optimize the latest models to run really fast on the Trainium hardware. As a Software Development Engineer on the Inference Model Enablement team, you will onboard and optimize state-of-the-art open-source and customer LLMs, both dense and MoE, for inference on Trainium accelerators. You will also drive improvements in model enablement speed and experience, while advancing inference usability and quality through inference features, infrastructure optimization, tools, and automation. Key job responsibilities * Deliver high-performance models using distributed inference libraries * Drive technical excellence in performance optimization and system reliability across the Neuron ecosystem * Mentor team members and provide technical leadership across multiple work streams * Drive architectural decisions that impact the entire Neuron serving stack * Collaborate with customers, product owners, and engineering teams to define technical strategy * Author technical documentation, design proposals, and architectural guidelines A day in the life You'll lead critical technical initiatives while mentoring team members. You'll collaborate with cross-functional teams of applied scientists, system engineers, and product managers to architect and deliver state-of-the-art inference capabilities. Your day might involve: * Leading design reviews and architectural discussions * Debugging complex performance issues across the stack in collaboration with the compiler and runtime teams * Mentoring junior engineers on system design and model optimization across model enablement teams * Driving technical decisions that shape the future of Neuron's inference stack About the team The inference model enablement team releases its models in the vLLM Neuron plugin: https://github.com/vllm-project/vllm-neuron