Senior AI Infrastructure Architect, Cloud & Data Center

Google; Sunnyvale (CA); On-site; USD 233,000 - 324,000; Full time

Benefits offered by this job

Health Insurance

401(k) with company match

Paid time off 20 days

Sick time 40 hours/yr

Maternity leave 28-30 weeks

Baby Bonding leave 18 weeks

13 holidays per year

Job summary

Google Cloud is seeking an AI Infrastructure Field Solution Architect in the United States to help incubate and roll out TPU and GPU hardware with clients ranging from startups to enterprises. You will guide discussions on network fabric, compute/storage integration, and onsite provisioning, shaping roadmaps with product and engineering teams.

You will evaluate cost-to-performance tradeoffs, migrate models, and integrate silicon into platform capabilities.

Qualifications

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• 10 years of experience with data center technologies, solutions and deployment.
• Experience with data center networking, such as routing, switching, DNS, and IP addressing; compute and storage concepts; and operations including power, cooling, and procedures.
• Experience with AI model training and inference, deploying OSS frameworks such as PyTorch, Jax, etc., and optimizing performance versus costs.
• Experience with scripting and coding in Python, YAML, and Kubernetes.

Responsibilities

• Act as a trusted advisor to customers, helping them understand and incorporate AI accelerators into their overall business strategy by designing training and inferencing platforms, and incorporating customers' existing data center technologies.
• Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on Proofs of Concept, demonstrating features, optimizing model performance, profiling, and benchmarking.
• Assist in production deployment of Google Cloud accelerators, troubleshoot integration issues with existing compute, networking, and storage solutions, and enable customers to operate their training and inferencing clusters successfully.
• Build repeatable assets to enable other customers and internal teams.
• Collaborate with the AI Infrastructure Dedicated Engineering Team in Google Compute Engine, and scale ML techniques and solutions broadly. Influence Google Cloud strategy at the intersection of infrastructure and AI by advocating for enterprise customer requirements.

Skills

Data center experience

AI infrastructure

Python

Kubernetes

Networking basics

Education

Bachelor's degree in STEM

Tools

PyTorch

Kubernetes

YAML

Job description

Google Cloud is seeking an AI Infrastructure Field Solution Architect in the United States to help incubate and roll out TPU and GPU hardware with clients ranging from startups to enterprises. You will guide discussions on network fabric, compute/storage integration, and onsite provisioning, shaping roadmaps with product and engineering teams.

You will evaluate cost-to-performance tradeoffs, migrate models, and integrate silicon into platform capabilities.