Accelerate customer time-to-value on the largest AI Infrastructure and High Performance Computing (HPC) workloads in Google Public Sector.

Build a trusted advisory relationship with customer architects, engineering leadership, and research teams. Identify customer priorities, technical objections and design strategies focused on Google AI Infrastructure and HPC ecosystem to deliver business value and resolve blockers.

Provide domain expertise around hardware accelerators (GPU/TPU), prevailing ML Frameworks (Py Torch, Keras, JAX), and model building techniques.

Make recommendations on GPU/TPU hardware, framework selection, benchmarks, and model building required to successfully implement a complete solution.

Manage the holistic research engineering relationship with customers by collaborating with specialists, product management, technical teams, and more.

Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.

10 years of experience with cloud native architecture in a customer-facing or support role.

Experience with frameworks for deep learning (e.g. Py Torch, Tensor Flow, Jax, Ray, etc.), AI accelerators (e.g. TPUs, GPUs), model architectures (e.g. encoders, decoders, transformers), and using machine learning APIs.

Ability to travel up to 20% of the time as required.

Must possess an Active Top Secret/SCI US Government Security Clearance with polygraph.