GPU Reliability Engineering Manager – AI Platform Leader

Google; Seattle (WA); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Health, dental, vision, life, and long

Disability insurance

401(k) with company match

Paid Time Off: 20 days/yr

Sick Time: 69 hours/year (Seattle)

Job summary

Google Cloud is hiring a Software Engineering Manager to guide multiple teams of software engineers, shaping project goals, contributing to product strategy, and developing the people on your team. You will help your engineers optimize code and drive technical leadership across AI and large-scale systems.

The role spans collaboration with cross‑functional partners, managing a large product budget, and overseeing deployment of GPU offerings from launch to reliable operation across sites.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years leading technical project strategy, ML design, and ML infrastructure optimization.
• 3 years testing, maintaining, or launching software products, and 1 year in software design/architecture.
• 3 years in a technical leadership role.
• 2 years in people management/leadership.

Responsibilities

• Lead, mentor, and grow a team of software engineers.
• Execute technical roadmaps for the GPU ecosystem.
• Oversee accelerator solution lifecycle and fleet reliability.
• Collaborate with customers as a technical advocate to resolve challenges.
• Author and review technical specifications for architecture and maintainability.

Skills

Software development

Technical leadership

Machine Learning design

ML infrastructure optimization

People management

Cross-functional collaboration

Education

Bachelor's degree or equivalent practical experience

Master's or PhD in CS/EE (preferred)

Tools

GPU drivers

Embedded systems

Job description

Google Cloud is hiring a Software Engineering Manager to guide multiple teams of software engineers, shaping project goals, contributing to product strategy, and developing the people on your team. You will help your engineers optimize code and drive technical leadership across AI and large-scale systems.

The role spans collaboration with cross‑functional partners, managing a large product budget, and overseeing deployment of GPU offerings from launch to reliable operation across sites.