Site Reliability Engineer, ML Compute SRE
Company: Google
Location: Raleigh
Posted on: April 2, 2026
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Job Description:
info_outline X Note: By applying to this position you will have
an opportunity to share your preferred working location from the
following: Raleigh, NC, USA; Durham, NC, USA . Minimum
qualifications: Bachelor’s degree in Computer Science, a related
field, or equivalent practical experience. 2 years of experience
with software development in one or more programming languages
(e.g., Golang). Experience with debugging and troubleshooting
software issues. Preferred qualifications: Master's degree in
Computer Science or Engineering, a related field, or equivalent
practical experience. 4 years of experience designing, analyzing,
and troubleshooting large-scale distributed systems. 2 years of
experience with data structures and algorithms. Experience with
Machine Learning infrastructure. Experience in statistical analysis
to identify trends and root causes in production data. 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. The
ML Accelerator SRE team mission is to deliver an exceptional ML
compute infrastructure for all users. We ensure that all ML
accelerators 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. The US base
salary range for this full-time position is $147,000-$211,000 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 . Responsibilities Design/develop new
features to help us support ML operations across Technical
Infrastructure ( TI) and Google Cloud Platform (GCP). Participate
in tier 2 on-call support for ML accelerator and platform issues.
Identify and improve our operational experience and help us reduce
toil and reduce incident impact. Define and improve metrics and
Service Level Objectives (SLOs) for the operations of the ML fleet.
Work with Platform Infrastructure Engineering (PIE), Cloud, and SRE
stakeholders to understand and reduce risks to upcoming accelerator
launches.
Keywords: Google, Greensboro , Site Reliability Engineer, ML Compute SRE, IT / Software / Systems , Raleigh, North Carolina
