Software Engineering Manager - Lead AI/ML & GPU Cloud

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

Benefits offered by this job

Health/Dental/Vision/Life/Disability

401(k) with company match

Paid time off 20 days

Sick time 40 hours/year (Seattle 69)

Maternity leave 28-30 weeks

Baby bonding leave 18 weeks

Holidays 13 paid days

Job summary

Google in Seattle seeks a Software Engineering Manager to lead the Cloud GPU team and guide engineers across major AI projects. You will shape technical strategy and ensure scalable infrastructure while mentoring teams and aligning with product goals.

You will collaborate with cross-functional partners, manage budgets, and oversee global deployments, driving reliability and performance of AI platforms.

Qualifications

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

Responsibilities

• Lead, mentor, and grow a team of software engineers and foster collaboration.
• Execute technical roadmaps for the GPU ecosystem and AI infrastructure.
• Oversee accelerator solution lifecycle and ensure fleet reliability.
• Collaborate with customers to translate feedback into platform enhancements.
• Author and review technical specs for architectural consistency.

Skills

Software leadership

ML design

ML infrastructure

Project strategy

Team mentoring

Education

Bachelor's degree or equivalent

Master's or PhD in CS/EE or related

Tools

Python

TensorFlow

ML tooling

Job description

Google in Seattle seeks a Software Engineering Manager to lead the Cloud GPU team and guide engineers across major AI projects. You will shape technical strategy and ensure scalable infrastructure while mentoring teams and aligning with product goals.

You will collaborate with cross-functional partners, manage budgets, and oversee global deployments, driving reliability and performance of AI platforms.