Senior Software Engineer, Site Reliability Engineering, YouTube ML New

Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. SRE ensures that Google's services—both our internally critical and our externally-visible systems—have reliability, uptime appropriate to users' needs and a fast rate of improvement. Additionally SRE’s will keep an ever-watchful eye on our systems capacity and performance.

Much of our software development focuses on optimizing existing systems, building infrastructure and eliminating work through automation. On the SRE team, you’ll have the opportunity to manage the complex challenges of scale which are unique to Google, while using your expertise in coding, algorithms, complexity analysis and large-scale system design.

SRE's culture of intellectual curiosity, problem solving and openness is key to its success. Our organization brings together people with a wide variety of backgrounds, experiences and perspectives. We encourage them to collaborate, think big and take risks in a blame-free environment. We promote self-direction to work on meaningful projects, while we also strive to create an environment that provides the support and mentorship needed to learn and grow.

To learn more: check out our books on Site Reliability Engineering or read a career profile about why a Software Engineer chose to join SRE.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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.

Minimum qualifications:

Bachelor’s degree in Computer Science, a 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.

Preferred qualifications:

Master's degree in Computer Science or Engineering.