Data Center Design Lead, System Engineering and Architecture

Google • Sunnyvale, CA

2d • $144,000 - $211,000

About The Position

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 Systems Engineering Architecture team designs the foundational blueprints for Google's future data center infrastructure. As a key part of Data Center Technical Strategy (DCTS), our multidisciplinary team of engineers and architects is responsible for defining and developing system-level architectures for new Data Center concepts and gPOR designs, creating and maintaining the technical roadmap for Data Center evolution, emphasizing scalability, efficiency, and speed, driving innovation in power distribution, cooling solutions, and layouts to support increasing power densities and new technologies, leading the physical infrastructure integration of critical hardware programs, including Machine Learning platforms (TPUs/GPUs), managing system interfaces and ensuring seamless compatibility between various data center products and subsystems and collaborating across numerous partner teams to translate product and service requirements into buildable, operable, and maintainable data center designs. The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Requirements

• Bachelor's degree in Electrical Engineering, Power Engineering, a related technical field, or equivalent practical experience.
• 5 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.

Nice To Haves

• Master's degree in Engineering, Business or other relevant fields, or a Professional Engineering (PE) license.

Responsibilities

• Architect and optimize data centers for 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 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 AI solutions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees