Senior AI Infrastructure Architect

Socket.dev; Sunnyvale (CA); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Equity

Job summary

Google’s Sunnyvale-based engineering teams seek software engineers to advance AI/ML infrastructure and repair automation. You will contribute to long-term roadmaps, leading diagnostic systems design using Generative AI and collaborating across platforms to integrate hardware into scalable automation workflows.

Ideal candidates have 8+ years in software, 5+ in testing/launching products, and strong ML design experience, with a proven ability to influence engineering practices and drive safety

Qualifications

• Bachelor’s degree or equivalent practical experience is required.
• 8 years of software development experience.
• 5 years testing and launching software products, plus 3 years in design/architecture.
• 5 years in one or more: speech/audio tech, RL, ML infra, or other ML field.
• 5 years in ML design and ML infrastructure, including deployment and data processing.

Responsibilities

• Define long-term repair automation goals for AI/ML infrastructure.
• Lead design of agentic diagnostic systems using Generative AI for network diagnoses.
• Collaborate with platform teams to integrate new hardware into the automation ecosystem and repair workflows.
• Lead safety initiatives like automated anomaly detection to protect fleet health.
• Mentor junior and senior engineers and standardize automation and safety practices across teams.

Skills

Software development

Product testing and launch

ML design & infrastructure

Generative AI integration

Leadership potential

Education

Bachelor’s degree or equivalent practical experience

Master’s degree or PhD in Engineering / CS

Tools

SQL Pipelines

Plx Scripts

Generative AI Agents

Job description

Google’s Sunnyvale-based engineering teams seek software engineers to advance AI/ML infrastructure and repair automation. You will contribute to long-term roadmaps, leading diagnostic systems design using Generative AI and collaborating across platforms to integrate hardware into scalable automation workflows.

Ideal candidates have 8+ years in software, 5+ in testing/launching products, and strong ML design experience, with a proven ability to influence engineering practices and drive safety