11 days ago

Staff Hardware Systems Architect

Google DeepMind

On Site
Full Time
$225,000
Mountain View, CA

Job Overview

Job TitleStaff Hardware Systems Architect
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$225,000
LocationMountain View, CA

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Job Description

Snapshot

At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. We are seeking a highly motivated Staff Hardware Systems Architect to join our team and contribute to the development of groundbreaking datacenter infrastructure for machine learning acceleration.

About Google DeepMind

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

We seek out individuals who thrive in ambiguity and who are willing to help out with whatever moves datacenter infrastructure innovation forward. We regularly need to invent novel solutions to problems, and often change course if our ideas don’t work out, so flexibility and adaptability to work on any project is a must.

The Role of Staff Hardware Systems Architect

In this role, you are at the forefront of designing and building the next generation of datacenter infrastructure. We are seeking a highly experienced and visionary Systems Architect to join our dynamic team. You will play a pivotal role in shaping the future of our datacenter and server architectures, from the system level down to the component selection. The ideal candidate will have a deep and broad understanding of datacenter technologies, with a proven track record of innovative design and successful implementation of large-scale, high-performance computing systems.

Responsibilities

  • Datacenter and Server Systems Design: Lead the architectural design of large-scale, high-density server platforms, considering system topology, power distribution, advanced cooling methodologies, and mechanical constraints. Architect the physical, electrical, and thermal design of server racks, hosts, trays, and other datacenter hardware from concept to deployment. Drive system-level decisions for host and server architecture, including motherboard design, power delivery, memory subsystems, and high-speed interconnects. Oversee and steer the design and development of complex printed circuit boards, ensuring signal and power integrity for cutting-edge interconnects and components. Define and analyze system requirements for reliability, availability, and serviceability (RAS) at the server and rack level.
  • Holistic System Integration and Optimization: Develop and analyze system-level performance models to guide architectural trade-offs between performance, power, and cost. Collaborate with software and firmware teams to ensure seamless integration and co-optimization across the entire system stack. Lead cross-functional teams to drive technical alignment and decision-making from concept to high-volume deployment.

Qualifications

Education
  • Master's or Ph.D. in Electrical Engineering, Computer Engineering, or a related field.
Minimum Qualifications
  • 10+ years of experience in systems architecture, with a primary focus on datacenter and server hardware design.
  • Proven track record of architecting and delivering complex, high-performance computing systems at scale.
  • Deep expertise in server and host architecture, including motherboard design, power delivery, and thermal management for high-power components.
  • In-depth understanding of datacenter power and cooling infrastructure, including both air and liquid cooling solutions at the rack and facility level.
  • Extensive experience with high-speed system-level interfaces (e.g., ICI, PCIe Gen5/6, CXL, high-speed Ethernet).
  • Experience with system-level performance modeling and analysis.
Preferred Qualifications
  • Experience influencing the selection and design of SoC interfaces, with a focus on high-speed serial interconnects.
  • Knowledge of chiplet-based design methodologies and advanced semiconductor packaging technologies (e.g., 2.5D/3D integration).
  • Expertise in datacenter networking, including leaf-spine topologies and RDMA.
  • Working knowledge of transformer-based large language models is a plus.
  • Knowledge of high-performance and low-power architectures for ML acceleration.
  • Exceptional problem-solving and analytical skills.
  • Excellent written and verbal communication skills, with the ability to present complex technical concepts to a variety of audiences.
  • Strong leadership and collaboration skills, with the ability to influence and guide cross-functional teams.

Key skills/competency

  • Datacenter Architecture
  • Server Hardware Design
  • High-Performance Computing
  • Thermal Management
  • Power Delivery
  • System Integration
  • PCIe Gen5/6
  • CXL
  • High-Speed Ethernet
  • ML Acceleration

Tags:

Staff Hardware Systems Architect
datacenter architecture
server design
high-performance computing
machine learning acceleration
systems integration
thermal management
power delivery
PCIe
CXL
Ethernet
motherboard design
chiplet design
semiconductor packaging
RDMA

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How to Get Hired at Google DeepMind

  • Research Google DeepMind's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume: Highlight extensive experience in datacenter architecture, server hardware design, and high-performance computing, using keywords from the job description.
  • Showcase relevant projects: Detail your proven track record in architecting and delivering complex, large-scale systems and ML acceleration solutions.
  • Prepare for technical depth: Be ready to discuss specific expertise in high-speed interfaces, power delivery, thermal management, and system-level performance modeling.
  • Demonstrate problem-solving and leadership: Practice articulating how you've solved novel problems and led cross-functional teams in complex technical environments.

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