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Minimum qualifications:

+ Bachelor's degree in Computer Science, Electrical Engineering, or a related field.

+ 10 years of experience with Artificial Intelligence/Machine Learning (AI/ML) and data center infrastructure.

+ 10 years of experience designing and optimizing data centers, with a focus on ML systems.

Preferred qualifications:

+ Experience with cost and performance modeling for data center infrastructure.

+ Knowledge of data center infrastructure, including power, networking, storage, and cooling systems.

+ Knowledge of GPU/TPU architectures, large-scale AI system integration, and performance optimization techniques.

+ Knowledge of current and emerging trends in ML hardware and software, and their impact on data center design.

Our thirst for technology is a part of everything we do. The Data Center Engineering team takes the physical design of our data centers into the future. Our lab mirrors a research and development department -- cutting-edge strategies are born, tested and tested again. Along with a team of great minds, you take on complex topics like how we use power or how to run state-of-the-art, environmentally-friendly facilities. You're a visionary who optimizes for efficiencies and never stops seeking improvements -- even small changes that can make a huge impact. You generate ideas, communicate recommendations to senior-level executives and drive implementation alongside facilities technicians.

With your technical expertise, you ensure compliance with codes and standards, develop infrastructure improvements and serve as an expert in your specialty (e.g., cooling, electrical).

The Data Center Engineering team takes the physical design of data centers into the future. The goal is to develop Data Center architectures, which enable state of the art technologies, are efficient to operate and globally deployable. You optimize efficiency and never stop seeking improvements, even small changes that can make a huge impact.

In this role, you will be enabling new infrastructure technology and IT technology insertion into a modular data center portfolio targeted at improving development and deployment velocity. You will be responsible for defining, implementing, and maintaining critical Data Center system architecture and interfaces between and within product areas.

You will also lead investigations and innovations in integration of IT racks into the Data centers, a full stack optimization of IT and Data Center design, focusing on ML applications.

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 $171,000-$254,000 + 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 (https://careers.google.com/benefits/) .

+ Architect and optimize data centers for large-scale AI/ML deployments, with an understanding of GPU/TPU architecture and system integration to maximize performance and efficiency.

+ Identify and implement solutions to accelerate project timelines and reduce infrastructure costs while maintaining high performance standards.

+ Evaluate emerging technologies and influence industry trends to ensure data centers are aligned with the latest ML advancements.

+ Partner with internal teams and hardware vendors to troubleshoot performance issues, influence product roadmaps, and integrate AI solutions.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.