Software Engineering Manager, GPU Reliability
Seattle, WA, USA · Manager · Full-time · Posted Oct 12, 2026
- Experience
- 8 years in software development; 5 years in technical project strategy, ML design, and ML infrastructure optimization; 3 years testing, maintaining, or launching software products; 1 year in software design and architecture; 3 years technical leadership; 2 years people management, supervision, or team leadership.
- Education
- Bachelor's degree or equivalent practical experience.
About the job
Leads engineers building and maintaining Google Cloud’s GPU infrastructure, with responsibility for accelerator reliability and the platform supporting AI training and inference.
What you'll do
- Lead, mentor, and develop a team of software engineers.
- Execute technical roadmaps for the GPU ecosystem and oversee accelerator lifecycle, root-cause analysis, and production reliability.
- Work with customers and cross-functional partners to resolve critical issues and improve the platform.
What they ask for
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience in technical project strategy, ML design, and optimizing ML infrastructure.
- 3 years in a technical leadership role and 2 years in people management, supervision, or team leadership.
Nice to have
- Master's degree or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
- Experience with data science, large-scale data processing, reliability metrics, runtimes, Firmware, GPU drivers, embedded systems, or real time systems.
Pay
$207000 - $300000 (USD) (base salary)
Tools
Machine Learning (ML), GPU drivers, Firmware, embedded systems, embedded processors, real time systems
AI focus
Builds and maintains GPU infrastructure for AI training and inference, including optimizing ML infrastructure and advancing Google Cloud’s AI platform.
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