Data Center System Architect

Job Description

Data Center System ArchitectLocation: Seattle, WA, USAExperience Level: AdvancedMinimum qualifications:

• Bachelors 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.

About the jobOur 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. Youre 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 the 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 Googles product portfolio possible. Were 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.CompensationThe US base salary range for this full-time position is $171,000-$254,000bonusequitybenefits. 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

• 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.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Googles Applicant and Candidate Privacy Policy. Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law.See also Googles EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire. If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form. Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.Locations: Seattle, WA, USAExperience Level: Advanced

Keyskills :
data center optimization ai/ml expertise system architecture performance modeling stakeholder influence job posting recruitment workforce communicationdecision making compensation