Senior SRE Engineer, Scalable ML Systems

Google LLC; Zürich; On-site; CHF 180,000 - 240,000; Full time

Job summary

Google LLC in Zürich, Switzerland seeks a Senior Software Engineer for Site Reliability Engineering in YouTube ML. You will design, build and scale fault-tolerant infrastructure, mentor teams, and partner with ML platforms to ensure reliable delivery of services globally.

The role emphasizes coding, system design, capacity planning and blameless postmortems, with collaboration across organizations to advance Google's ML initiatives with reliability and speed.

Qualifications

• Bachelor’s degree in Computer Science or related field or equivalent practical experience.
• 5+ years of experience with software development in one or more programming languages.
• 3 years of experience in designing, analyzing, and troubleshooting large-scale distributed systems.
• 2 years of experience leading projects and providing technical leadership.

Responsibilities

• Engage in and improve the whole lifecycle of services—from inception and design, through to deployment, operation and refinement.
• Support services before they go live through activities such as system design consulting, developing software platforms and frameworks, capacity planning and launch reviews.
• Maintain services once they are live by measuring and monitoring availability, latency and overall system health.
• Scale systems sustainably through mechanisms like automation, and evolve systems by pushing for changes that improve reliability and velocity.
• Practice sustainable incident response and blameless postmortems.

Skills

Software development

Distributed systems

Technical leadership

Education

Bachelor's degree in Computer Science or related field

Master's degree (preferred)

Job description

Google LLC in Zürich, Switzerland seeks a Senior Software Engineer for Site Reliability Engineering in YouTube ML. You will design, build and scale fault-tolerant infrastructure, mentor teams, and partner with ML platforms to ensure reliable delivery of services globally.

The role emphasizes coding, system design, capacity planning and blameless postmortems, with collaboration across organizations to advance Google's ML initiatives with reliability and speed.