Staff Data Center Design Lead

Google Google · Big Tech · Sunnyvale, CA +1

This role focuses on the physical design and optimization of data centers to support large-scale AI/ML deployments. The lead will architect solutions, evaluate emerging technologies, and partner with internal teams and vendors to ensure data centers are aligned with the latest ML advancements, focusing on performance, efficiency, and cost reduction. While the role heavily interacts with AI/ML infrastructure, the core craft is data center engineering, not AI model development.

What you'd actually do

  1. 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.
  2. Identify and implement solutions to accelerate project timelines and reduce infrastructure costs while maintaining high performance standards.
  3. Evaluate emerging technologies and influence industry trends to ensure our data centers are aligned with the latest ML advancements.
  4. Partner with internal teams and hardware vendors to troubleshoot performance issues, influence product roadmaps, and integrate innovative AI solutions.

Skills

Required

  • 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.

Nice to have

  • Master's degree in Computer Science, Electrical Engineering, Mechanical Engineering or a related field.
  • Experience in large campus-scale data center design concepts.
  • Experience with current and emerging trends in ML hardware and software, and their impact on data center design.

What the JD emphasized

  • large-scale AI/ML deployments
  • GPU/TPU architecture
  • AI system integration
  • ML advancements
  • AI solutions