Google

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Madison, WI, USA.

Minimum qualifications:

• PhD degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
• Experience in any one domain of silicon engineering through internships, academic research, or publications (e.g., digital design, design verification, silicon validation, or system integration).
• Experience with one of the hardware description languages (e.g., Verilog, SystemVerilog) or one scripting language (e.g., Python, Perl).

Preferred qualifications:

• Research or internship experience in advanced topics such as heterogeneous computing, low-power design, advanced packaging, or AI/ML hardware acceleration.
• Experience with publications in peer-reviewed journals and conferences.
• Familiarity with industry-standard design tools for simulation, and verification.
• Ability to demonstrate significant understanding of relevant domains such as Architecture, Digital Design, Design Verification, System Integration or Silicon Validation.
• Excellent problem-solving and communication skills, with the ability to work effectively in a team environment.

About the Job

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.

As a Silicon Engineer, you will be a pivotal contributor to Google’s AI efforts, working across various stages of the silicon lifecycle, from architecture and design to verification, validation, and deployment. You will investigate and implement novel approaches to optimize performance, power, and area for critical silicon infrastructure like TPUs and ML accelerators. This role involves making significant, independent technical contributions by planning, managing, and executing your priorities, selecting appropriate methods to achieve project goals. You will collaborate closely with cross-functional teams, translating research findings into impactful silicon solutions that enhance user experience. You will also contribute to developing design methodologies and automation flows that accelerate the design process.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary range for this full-time position is $132,000-$189,000 + 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

• Drive and develop innovative solutions across frontend silicon engineering domains, including architecture, digital design, design verification, and system integration.
• Utilize advanced modeling and simulation techniques to analyze and optimize system performance, power consumption, and thermal characteristics.
• Participate in the design, verification, and validation of complex silicon systems, encompassing RTL coding, functional verification, and system integration.
• Contribute to the development and improvement of electronic design automation (EDA) tool infrastructure and internal flows.
• Collaborate with cross-functional teams to debug failures and translate research findings into practical silicon solutions.