Join a forward-thinking team dedicated to developing custom silicon solutions that will power Google's future direct-to-consumer products. Your contributions will drive innovation in products enjoyed by millions globally. You will play a key role in shaping next-generation hardware, delivering exceptional performance, efficiency, and integration.

The AI and Infrastructure team is at the forefront of innovation, enabling Google customers with advanced capabilities and insights through AI and Infrastructure solutions delivered at an unprecedented scale, efficiency, and reliability. Our reach extends to Googlers, Google Cloud customers, and billions of Google users worldwide.

We are the engine behind Google's pioneering advancements, facilitating the development of cutting-edge AI models, providing immense computing power for global services, and building the foundational platforms for future developer innovations. Across both software and hardware, our teams are shaping the future of world-leading hyperscale computing. Key initiatives include the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, and systems research.

Develop comprehensive architecture specifications aligned with current and future AI/ML roadmap computing requirements. Create architectural and microarchitectural power/performance models, and conduct thorough quantitative and qualitative performance and power analyses.

Collaborate closely with hardware design, software, compiler, Machine Learning (ML) model, and research teams to achieve effective hardware/software co-design and establish high-performance hardware/software interfaces. Evaluate diverse silicon solutions for executing Google’s data center Artificial Intelligence (AI) accelerator roadmap, including components, vendor collaborations, custom designs, and chiplets.

Take ownership of the microarchitecture for compute blocks and subsystems. Identify and lead initiatives to enhance power, performance, and area for your designated modules. Develop and contribute to simulation tools.

Work with stakeholders across software, verification, emulation, physical design, packaging, and silicon validation to ensure the completeness, correctness, and performance of designs.

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, coupled with equivalent practical experience. Possess 4 years of experience in at least one of the following areas: architecture and micro-architecture design for graphics, Machine Learning (ML), managing low-precision or mixed-precision numerics, vector processors, DSP processors, or architecting networking ASICs.

Demonstrated experience with memory hierarchy, memory controllers, HBM, and DRAM technologies.

Preferred qualifications include a Master's degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science, with a focus on computer architecture. Experience collaborating with software teams to optimize hardware/software interfaces and in estimating performance through analysis, modeling, and network simulation is valuable. Proficiency in programming languages like C++ and Python, along with knowledge of arithmetic units, bus architectures, accelerators, memory hierarchies, and high-performance/low-power design techniques, is beneficial.