AI Infrastructure Field Solutions Architect — Cloud Accelerators

Google; New York (NY); On-site; USD 233,000 - 324,000; Full time

Benefits offered by this job

Health, dental, vision, life, anddisab

401(k) with company match

Paid Time Off: 20 days per year

Sick Time: 40 hours/year (increased to

Maternity Leave & Baby Bonding Leave

Holidays: 13 paid days per year

Job summary

Google Cloud hires an AI Infrastructure Field Solution Architect to support commercial teams deploying TPU/GPU hardware for enterprises and startups, enabling faster innovation with hardware and software solutions.

You will lead discussions on network topology, fabric architecture, and compute/storage integration, including on-site facility visits during deployment, while partnering with product and engineering to remove roadblocks and shape future 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 their 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.

Skills

Data center networking experience

AI model training & inference

Python

YAML

Kubernetes

PyTorch

Jax

Education

Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience

Tools

PyTorch

Jax

Job description

Google Cloud hires an AI Infrastructure Field Solution Architect to support commercial teams deploying TPU/GPU hardware for enterprises and startups, enabling faster innovation with hardware and software solutions.

You will lead discussions on network topology, fabric architecture, and compute/storage integration, including on-site facility visits during deployment, while partnering with product and engineering to remove roadblocks and shape future platform capabilities.