Staff Site Reliability Engineer, Semantic Understanding

at Google

Location

San Jose, CA, USA

Compensation

$207k–$300k USD

Type

full time

Posted

3 weeks ago

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Market range · company + function + seniority

$210k—$252k—$300k

p25 · target · p75 · n=800

Posted $300k · in the market band

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Job description

Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. SRE ensures that Google Cloud's services—both our internally critical and our externally-visible systems—have reliability, uptime appropriate to customer's 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 Cloud, 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.

Semantic Understanding Platform (SUP) is the standard platform for hosting image, text, video and data understanding signals at Google. SUP is a unified platform for understanding and generating content, and developing signals from raw data. Our team ensures the reliability, scalability, and operation of several Semantic Understanding Services, which we develop jointly with our partner SWE teams.

This role is open to both Site Reliability Engineering (SRE) Systems Engineering and SRE Software Engineering applicants.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

Develop and drive the technical strategy and roadmap for critical areas within SU SRE, mentoring team members to enhance system reliability and efficiency.
Initiate, own, and lead large-scale, complex projects and programs to significantly improve the reliability, scalability, and performance of SU services, often spanning multiple teams and systems.
Partner with development teams to influence system design and architecture, embedding reliability principles throughout the development life-cycle. Drive alignment on technical direction across teams, navigating priorities.
Identify, analyze, and mitigate risks in production. Design and implement architectural improvements to ensure long-term service health, scalability, and efficiency.
Participate in the oncall rotation, respond to incidents, and drive postmortem actions to prevent recurrence.

Minimum qualifications:

Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.
8 years of experience with software development in one or more programming languages.
4 years of experience in applying Design for Reliability techniques.
3 years of experience as a Site Reliability Engineer.
3 years of experience leading projects.
3 years of experience designing, analyzing, and troubleshooting distributed systems.

Preferred qualifications:

Master's degree in Computer Science or Engineering.
Experience in Generative AI, Generative AI Agent, Google Infrastructure.
Experience in large-scale and secure fleet management of servers and components.
Experience in enterprise risk assessments.
Experience with process improvement and automation.

In most instances, this position requires in-person interviews as part of the hiring process.

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