We develop AWS Neuron, the complete software stack for Trainium, Amazon's custom cloud-scale
machine learning accelerators. Join us to optimize LLMs to run really fast on the Trainium hardware.
As an 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 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.
The ideal candidate will have a strong background in LLM model architectures, model performance optimizations, and inference techniques, such as delivering high-performance models using distributed inference libraries. You should be capable of managing demanding, fast-changing priorities. You should have a 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.
Key job responsibilities
* Management and execution against project plans and delivery commitments
* Manage the day-to-day activities of the engineering team
* Management of resources, staffing, mentoring, and maintaining a best-of-class engineering team
* Report on status of development, quality, operations, and model performance to management
A day in the life
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.
