Minimum qualifications:
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent practical experience.
- 15 years of professional experience in software development, or 10 years with a relevant advanced degree.
- Experience influencing teams of 20 or more, with cross-functional engagement.
- Experience with one of the following: data center design, networking/networking planning, machine delivery, or construction.
- Master's or PhD degree in Computer Science, Engineering, or other technical related field, or equivalent practical experience.
- Experience in distributed systems architecture and building scalable systems.
- Experience with capacity planning, resource management or scheduling.
- Experience influencing and driving key product innovations and opportunities across diverse stakeholders.
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About the job
As the Principle Site Reliability Engineer for ML Acceleration, you will be responsible for ensuring Google's ML resources are delivered in a speed-optimal way. You will understand the end-to-end technical and logistical challenges of taking chips received from fabs around the world, and turning them into highly-connected ML supercomputers operating in gigawatt-scale data centers. This means that you will be reviewing all capacity acceleration programs and providing technical direction and decision-making in order to make sure that the usable ML capacity is maximized over the smallest delivery time. You will knit together different technical organizations to help them produce a globally-optimal outcome for ML capacity.
Acceleration is a multi-constrained problem, full of nuance, complexity and hard trade-offs. You will work closely with technical and planning teams across Data Center Construction, Networking, and Machine Delivery to make critical decisions and drive strategy.
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 $278,000-$399,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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
- Set and deliver technical projects for ambitious Google-level OKRs around ML capacity delivery into the fleet.
- Play a key role in overall portfolio management for existing ML capacity and related infrastructure.
- Support the development of the company's global ML strategy.
- Be responsible for a strategy that encompasses more than 20 countries across three continents and growing.
- Act as a key technical leader for Global Technical Infrastructure, engaging with other leaders across the region and globally.