Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
Google’s Cloud Supply Chain and Operations (CSCO) team is seeking a Systems Architect to shape and strengthen Design for Operations (Hardware and Software) requirements for the next generation of platforms.
In this role, you will be responsible to own strategy and drive execution across a portfolio of projects, ranging from network switches to machine learning pods. The goal is to reduce time and cost for platform deployment, maintenance, and repairs. In order to achieve the goal, you will interface with stakeholders from data center operations, manufacturing, and supply chains to crystallize Design for Operations requirements. You will influence new platform architectures through technical insights and trade off analyses with stakeholders from the Hardware Design and Software Architecture teams. You will help mentor an experienced team within operations for in-house competence in platform architecture, both hardware and software.
Our Platforms Infrastructure Engineering team designs and builds the hardware and software technologies that power all of Google's services. Our computational challenges are complex and unique, enabled by cutting-edge custom hardware designed and made in-house. As a hardware engineer, you will design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You will see those systems from concept all the way through to high-volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers, affecting millions of Google users.
The US base salary range for this full-time position is $159,000-$231,000 + bonus + equity + 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.
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
- Identify flaws and issues with hardware components. Solve with limited precedent and analyze key issues, risks, or trade-offs, and address hardware failures by recommending and implementing corrective solutions.
- Evaluate hardware design feasibility based on product requirements. Help identify and customize the design solution based on trade-offs in packaging, performance, power or technology selection, and scope hardware projects. Collaborate with internal partners and external vendors.
- Apply best practices to optimize constrained hardware components to meet performance, power, and cost-effectiveness requirements. Accurately predict consequences of hardware design decisions in cross-functional trade-off discussions, supported by simulation or measurement data, as needed.
- Work with cross-functional teams to optimize hardware performance under established design constraints.
- Drive efforts for the documentation of the hardware design, its implementation, or test/validation results throughout the product life cycle.
Qualifications
Minimum qualifications:
- Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, or a specialized field (e.g., Optics, Sensors, Audio/DSP, etc.), or equivalent practical experience.
- 4 years of experience working in a Product Design for Data center platforms technical environment, or 3 years of experience with an advanced degree.
- Experience in data centers, networking or supply chain/manufacturing operations.
Preferred qualifications:
- 3 years of experience in machine learning hardware architecture and software infrastructure.
- Excellent communication, project and stakeholder management skills