Silicon Architect, AI and Infrastructure

Google LLC; Sunnyvale (CA); On-site; USD 240,000 - 333,000; Full time

Benefits offered by this job

Equity grants

Bonus target

Job summary

Google LLC is seeking a Silicon Architect, AI and Infrastructure in Sunnyvale, CA. The role focuses on shaping AI/ML hardware acceleration, driving TPU architecture and integration within AI-driven systems, and leading end-to-end product architecture for next-generation accelerators.

You will collaborate with ML researchers, compiler and systems software engineers, and cross-functional silicon leads to ensure goals across functionality, performance, power, area, cost, reliability, and

Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
• 15 years of experience in computer architecture.
• Experience with HPC, server processors, GPUs, or ML accelerators.

Responsibilities

• Drive end-to-end silicon product architecture and roadmap for next-generation accelerators.
• Define and own product-level chip architectures and top-level specifications.
• Lead architectural pathfinding and trade-off studies for emerging AI workloads.
• Set technical direction across subsystems to enable rapid and predictable server-class ASICs.
• Partner across silicon development phases and with compiler/runtime teams to resolve bottlenecks.

Skills

High-performance computing

Server processors

GPUs

ML accelerators

Education

Bachelor's degree in Electrical Engineering/CS/related field

15 years of architecture experience

Job description

Silicon Architect, AI and Infrastructure

Share Silicon Architect, AI and Infrastructure

corporate_fare Google place Sunnyvale, CA, USA

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

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  
• 15 years of experience in computer architecture.
  
• Experience with high-performance computing (HPC), server processors, GPUs, or machine learning (ML) accelerators.

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science.
  
• Experience with semiconductor technologies and system-level trade-offs across process nodes, memory subsystems (e.g., HBM/DRAM), interconnects, packaging, and power/performance/area (PPA).
  
• Experience as the lead product or chip architect across multiple generations of complex data‑center AI/ML accelerators, GPUs, or high-performance compute (HPC) silicon.
  
• Experience driving cross‑functional technical alignment across RTL design, physical implementation, verification, thermal/power engineering, and post‑silicon validation teams.
  
• Strong track record of technical influence, mentoring architects, and translating emerging academic and industry AI trends into multi‑year silicon product roadmaps.

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 Google's most demanding AI/ML applications. You’ll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU. You'll 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.

As a Silicon Product Architect within the Cloud Silicon Engineering team, you will serve as a technical leader driving end-to-end product architecture for next‑generation systems and chips. You will bridge machine learning workloads, system software, and silicon implementation to define differentiated accelerator products that power Google’s technical infrastructure and Cloud AI customers.
In this role, you will own product‑level architectural definition from initial concept and pathfinding through specification, silicon execution, and production deployment. You will partner closely with machine learning researchers, compiler and systems software engineers, and cross‑functional silicon leads to ensure our chip architectures meet goals across functionality, performance, power, area, cost, reliability, and deployability.

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.

We’re the driving force behind Google's groundbreaking innovations, empowering the development of our cutting‑edge 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: $240000 - $333000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google .

• Drive the end‑to‑end silicon product architecture and roadmap for next‑generation accelerators in collaboration with internal AI/ML research teams, software/systems teams, and customers, maintaining a rigorous hardware‑software co‑design process.
  
• Define and own product‑level chip architectures and top‑level specifications, ensuring products achieve goals across functionality, performance, power efficiency, die area/cost, reliability, usability, and fleet deployability.
  
• Lead architectural pathfinding, trade‑off studies, and engaging assessments of emerging AI workloads and semiconductor technologies.
  
• Set technical direction across key product subsystems to enable rapid and predictable execution of complex server‑class ASICs.
  
• Partner across all phases of silicon development and with compiler/runtime teams to resolve cross‑domain bottlenecks and deliver production‑ready hardware/software stacks.

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 Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

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, is 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.