Systems Engineering Manager, Site Reliability Engineering, ML Compute

On-site in London·Added 1 month ago

Google

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Overview

Requirements

Work on-site in London
No relocation package mentioned.
Have 5+ years of experience
Senior-level role.

Skills

Nice to have

Mentoring

Requirements

Minimum qualifications:

Bachelor's degree in Computer Science or a related technical field or equivalent practical experience.
5 years of experience with programming in one or more programming languages.
3 years of people management experience.
3 years of experience leading projects and working with administration (e.g., filesystems, inodes, system calls) or networking (e.g., TCP/IP, routing, network topologies and hardware, SDN).

Preferred qualifications:

Master's degree in Computer Science or related technical field involving coding (e.g., physics or mathematics).
Track record of mentoring technical leads.
Proven success leading and influencing multiple technical teams.

The role

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 Compute SRE team mission is to deliver a ML compute infrastructure for all users. We ensure that all ML accelerators (TPUs and GPUs) are fully and appropriately supported as part of the TI and Cloud Compute platforms and that all ML jobs run efficiently, safely and reliably. We support both the hardware and the low level services that provide ML as an IaaS.

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.

Responsibilities

Lead a team of software/systems engineers on projects for users and be directly responsible for uptime.
Own end-to-end availability and performance of key services and build automation to prevent problem recurrence. Automate response to all non-exceptional service conditions.
Lead by example, mentor the team and establish credibility through quality technical execution.
Manage on-call rotations across continents, using a follow-the-sun model.
Design, write and deliver software to improve the availability, scalability, latency and efficiency of Google's services.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all

Apply online
Assessments
Online test · Not every role
You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.
Recruiter conversations
With a recruiter · Phone call · 1–2 sessions
One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.
Project work
In your own time · Not every role
For some roles, a small project before interviews: a case study, writing or code samples.
Interviews
With a rotating cast of Googlers
A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.
Decision and offer · With a recruiter

Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
AI tools are not permitted during interviews.
For some roles, pre-selected interviews happen virtually before final interviews onsite.