Silicon Engineer, PhD, University Graduate, 2027 Start

Silicon Engineer, PhD, University Graduate, 2027 Start

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Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

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XThis role is open to consideration for all eligible PhD graduates with completion dates in any month of 2026 or 2027. We encourage all upcoming PhD graduates with aligned backgrounds and interests to apply!

In most instances, this position requires in-person interviews as part of the hiring process.

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: architecture and RTL, verification and validation, physical design and circuits, systems, test or CAD.

• Experience with one of the hardware description languages (e.g., Verilog, SystemVerilog) or programming (e.g., Python, Tcl, Perl, or C++).

Preferred qualifications:

• Research experience in specialized areas such as high-performance/low-power architectures, domain-specific accelerators (DSAs/TPUs), memory hierarchies, coherent interconnects (e.g., CXL, PCIe, UCIe, NoC), or advanced packaging/chiplets.
• Experience developing and maintaining CAD/EDA design flows, methodology infrastructure, or applying ML for chip design automation.
• Understanding of advanced ML/DL model architectures (e.g., Transformers, LLMs) with experience in performance modeling, cycle-accurate simulation, or custom AI accelerator evaluation.
• Familiarity with industry-standard EDA tools (e.g., from Synopsys, Cadence, Siemens EDA, or emulation/formal platforms).
• Demonstrated research track record and ability to work on complex, open-ended problems, with publications in conferences (e.g., ISCA, MICRO, HPCA, ASPLOS, DAC, ICCAD, ISSCC, NeurIPS, MLSys).

About the job

In this role, you'll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Googles most demanding AI/ML applications. You'll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Googles TPU. Youll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.

The Chip Innovation Infrastructure team focuses on building Googles next-generation systems. The teams work is grounded in creating custom hardware, and as a Silicon Engineer youll get to collaborate with engineers from various parts of the organization to influence the future of Google Cloud and the AI infrastructure by working on the foundational technology that makes it all possible. This is the hardware that powers everything from Google Cloud, to our most advanced models like Gemini.

You will work on fundamental problems at the intersection of hardware, software, and algorithms. You will collaborate with exceptional engineers and researchers on projects that directly impact Googles custom silicon portfolio, including highly specialized AI accelerators like our TPUs and complex SoCs. Your responsibilities and projects will be tailored to your expertise and could focus on any part of the system stack.

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.

Were the driving team behind Googles groundbreaking innovations, empowering the development of our 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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Responsibilities and projects will be determined based on your background, interest, and skills.
• Collaborate cross-functionally across hardware and software teams to research, design, and model custom silicon solutions and AI accelerators.
• Develop, simulate, and verify architectural features, digital blocks, or subsystem interfaces targeting performance, power, and area optimizations.
• Contribute to EDA design automation flows, tooling infrastructure, or post-silicon bring-up and characterization.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Googles Applicant and Candidate Privacy Policy.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Googles EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.