Google Inc.
corporate_fare Google place Sunnyvale, CA, USA
Advanced Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.
Apply
Bachelor's degree in Electrical Engineering, Power Engineering, a related technical field, or equivalent practical experience.
10 years of experience in mission critical facility design and construction environments.
5 years of experience in designing and optimizing data centers, with a focus on machine learning systems.
Experience with GPU/TPU architectures, AI system integration, and performance techniques.
Experience with data center infrastructure, including power, networking, storage, and cooling systems.
Experience with cost and performance modeling for data center infrastructure, and ML hardware.
Preferred qualifications
Master's degree in Engineering, Business or other relevant fields, or a Professional Engineering (PE) license.
About the job 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 US base salary range for this full‑time position is $171,000–$254,000 plus bonus and equity and 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.
Responsibilities
Architect and optimize data centers for large‑scale AI/ML deployments, with a deep 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 our 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 innovative AI solutions.
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 or 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 Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
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.
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Advanced Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.
Apply
Bachelor's degree in Electrical Engineering, Power Engineering, a related technical field, or equivalent practical experience.
10 years of experience in mission critical facility design and construction environments.
5 years of experience in designing and optimizing data centers, with a focus on machine learning systems.
Experience with GPU/TPU architectures, AI system integration, and performance techniques.
Experience with data center infrastructure, including power, networking, storage, and cooling systems.
Experience with cost and performance modeling for data center infrastructure, and ML hardware.
Preferred qualifications
Master's degree in Engineering, Business or other relevant fields, or a Professional Engineering (PE) license.
About the job 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 US base salary range for this full‑time position is $171,000–$254,000 plus bonus and equity and 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.
Responsibilities
Architect and optimize data centers for large‑scale AI/ML deployments, with a deep 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 our 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 innovative AI solutions.
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 or 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 Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
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.
#J-18808-Ljbffr