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.
- 2 years of experience building and architecting production quality machine learning (ML) systems.
Preferred qualifications:
- Master's degree in Computer Science or Engineering.
- Experience with AI algorithms.
- Knowledge of containerization and container orchestration technologies such as Google Kubernetes Engine (GKE).
About the job
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.
In this role, you will be passionate about shaping the future of artificial intelligence, generative AI, and machine learning platforms while driving production excellence including reliability, scalability, and performance through sound Site Reliability Engineer (SRE) principles. You will have the opportunity to collaborate closely with a global team of SREs and developers to solve large and complex problems while building and supporting groundbreaking AI/ML tools that enable both internal and Google Cloud customers to grow with game-changing artificial intelligence built on the rapidly growing Vertex AI platform.
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.
The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about
benefits at Google.
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.
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.
