Field Solution Architect III, AI Infrastructure, Google Cloud: Google

As a Field Solution Architect for AI Infrastructure, you will support Google Cloud sales teams to incubate, pilot, and deploy industry-leading AI/ML accelerators (TPU/GPU) for enterprise customers. You will act as a trusted advisor, identifying AI opportunities, running benchmarks, developing migration paths, and analyzing cost-to-performance to help clients leverage optimized infrastructure within their cloud strategy.

Responsibilities:

Become a trusted advisor to customers, helping them incorporate AI accelerators into their cloud strategy by designing training and inferencing platforms.

Demonstrate Google Cloud's differentiation by leading Proofs of Concept (POCs), showcasing features, and optimizing model performance through profiling and benchmarking.

Develop repeatable assets to enable customers and internal teams.

Influence Google Cloud strategy by advocating for enterprise customer requirements at the intersection of infrastructure and AI/ML.

Travel to customer sites and events as required.

Requirements:

Minimum Qualifications:

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

8 years of experience with cloud infrastructure (e.g., hardware shapes, auto-scaling, auto-provisioning).

Experience coding in Python, bash scripting, and using OSS frameworks such as TensorFlow, PyTorch, Jax, etc.

Experience building and operationalizing machine learning models.

Preferred Qualifications:

Experience with containerization, Kubernetes, and Kubernetes on the cloud.

Experience with running MLPerf benchmarks and using performance profiling tools (e.g., Tensorflow profiler, PyTorch profiler).

Experience designing and architecting AI compute clusters.

Ability to debug distributed training/inferencing code.

Experience training and fine-tuning models (e.g., image, language, recommendation) with accelerators.