Engineering Manager, ML Infrastructure
Company: Google
Location: Sunnyvale
Posted on: April 2, 2026
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Job Description:
Minimum qualifications: Bachelor’s degree, or equivalent
practical experience. 8 years of experience in software
development. 3 years of experience with developing infrastructure,
distributed systems or networks, or experience with compute
technologies, storage or hardware architecture. 3 years of
experience in a technical leadership role. 2 years of experience in
a people management or team leadership role. Preferred
qualifications: Master's degree or PhD in Computer Science or a
related technical field. 3 years of experience working in a
matrixed organization. Experience with the end-to-end Machine
Learning (ML) development lifecycle and infrastructure. Excellent
communication and cross team collaboration skills. About the job
Like Google's own ambitions, the work of a Software Engineer goes
beyond just Search. Software Engineering Managers have not only the
technical expertise to take on and provide technical leadership to
major projects, but also manage a team of Engineers. You not only
optimize your own code but make sure Engineers are able to optimize
theirs. As a Software Engineering Manager you manage your project
goals, contribute to product strategy and help develop your team.
Teams work all across the company, in areas such as information
retrieval, artificial intelligence, natural language processing,
distributed computing, large-scale system design, networking,
security, data compression, user interface design; the list goes on
and is growing every day. Operating with scale and speed, our
exceptional software engineers are just getting started and as a
manager, you guide the way. With technical and leadership
expertise, you manage engineers across multiple teams and
locations, a large product budget and oversee the deployment of
large-scale projects across multiple sites internationally. In this
role, you will provide end-to-end, fleet-wide scheduling for all
Alphabet Machine Learning (ML) workloads that are efficient,
reliable, and easy-to-use. You will be responsible for scheduling
work on almost all production machines. 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. The US base salary range for this full-time
position is $207,000-$300,000 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 Lead our new Workload Optimization (WO) team. Set
the technical goal and roadmap and drive its key features in this
pivotal role. Collaborate closely with teams across machine
learning (ML), and our product area customers to ensure successful
execution. Shape the team's culture and processes, identify new
opportunities, and translate our broader strategy into concrete
priorities and projects. Coach and provide career guidance to your
reports, improve our engineering practices, and influence technical
direction across the organization. Navigate open-endedness and
actively contribute to the team's engineering efforts as a
technical leader.
Keywords: Google, San Jose , Engineering Manager, ML Infrastructure, IT / Software / Systems , Sunnyvale, California
