Field Solutions Architect IV, AI Infrastructure, Google Cloud

• 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.

Minimum 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.

Preferred qualifications:

• Experience training and fine tuning large models with accelerators.
• Experience with performance profiling and benchmarking tools (i.e., MLPerf, PyTorch profiler, Tensorboard).
• Experience deploying compute, network and storage solutions in data centers.
• Experience deploying TPU clusters.
  

• 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.