Staff AI/ML Storage Systems Engineer — Edge & Cloud

Google Inc.; Kirkland (WA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google's AI Storage team within Google Distributed Cloud builds scalable storage systems for AI workloads at the edge and in air-gapped environments. The role focuses on delivering high-throughput, ultra-low-latency data access to keep GPUs and accelerators saturated while ensuring sovereignty and security.

As a Staff Software Engineer, you will own core storage components, collaborate across AI infra, compute, and networking teams, and contribute to a cloud-anywhere storage architecture across

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience with ML design and ML infrastructure.
• 5 years of experience in systems architecture, including building or maintaining distributed systems or large-scale storage architectures.
• 5 years of experience in systems programming (e.g., C++, Go, or Rust).

Responsibilities

• Design and develop scalable, distributed File and Object storage solutions that serve as the critical foundational backbone for complex AI/ML workloads within the GDC environment.
• Engineer advanced solutions optimized for massive throughput, specifically enabling high-frequency model checkpointing and the ultra-low latency data access required for AI training and inference.
• Drive technical execution with external partners to seamlessly integrate high-performance storage hardware with Google's distributed software ecosystem.
• Take full life-cycle responsibility for core storage services, ensuring security, data durability, and high availability across disconnected edge and on-premises environments.
• Partner with AI infrastructure, compute, and networking teams to architect system-wide improvements and deliver a unified 'cloud-anywhere' experience.

Skills

Software development

ML design & infrastructure

Distributed systems

Systems programming (C++, Go, Rust)

Education

Bachelor's degree or equivalent practical experience

Master’s degree or PhD preferred

Job description

Google's AI Storage team within Google Distributed Cloud builds scalable storage systems for AI workloads at the edge and in air-gapped environments. The role focuses on delivering high-throughput, ultra-low-latency data access to keep GPUs and accelerators saturated while ensuring sovereignty and security.

As a Staff Software Engineer, you will own core storage components, collaborate across AI infra, compute, and networking teams, and contribute to a cloud-anywhere storage architecture across