About the job
As the SDM for the LLM Inference Model Enablement team, you will lead a team of expert AI/ML engineers to onboard and optimize state-of-the-art open-source and customer LLMs, both dense and MoE, for inference on Neuron and Trainium and Inferentia 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.
Responsibilities
You will work with your senior management and technical leaders to define the model enablement and performance optimization for the latest SOTA LLMs, build and deliver them to customers.
Meanwhile, lead the team to continue improving the model onboarding experience, as well as enhancing inference usability and quality for Neuron-supported models.
You will manage changing priorities as new models and new technologies emerge, and you adapt your team’s work to manage them. You will dive deep to help your team solve technical challenges.
Qualifications
Minimum
3+ years of engineering team management experience
7+ years of working directly within engineering teams experience
3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
Experience partnering with product or program management teams
Preferred
A strong background in LLM model architectures, model performance optimizations, and inference techniques, such as delivering high-performance models using distributed inference libraries. Capable of managing demanding, fast-changing priorities. Strong technical ability to understand and deliver as part of a vertically integrated system stack consisting of the PyTorch inference library, Neuron compiler, runtime, and collectives.