Hardware Architecture Modeling Engineer, PhD, University Graduate

About the role

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.

Responsibilities

• Develop architectural and micro architectural models to enable quantitative analysis.
• Conduct performance and power analyses and quantitatively evaluate proposals.
• Contribute to Machine Learning workload characterization, benchmarking, and hardware-software co-design.
• Collaborate with partners in hardware design, software, compiler, Machine Learning (ML) model and Research teams for hardware/software codesign.
• Propose capabilities and next-generation TPUs and chip roadmap, and contribute to TPU chip specifications.

Qualifications

• PhD degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience
• Experience in any one domain of computer engineering or silicon engineering through internships, academic research, or publications (e.g., co-design, digital design, architecture).
• Experience programming in C++.
• Research or internship experience in AI/ML hardware acceleration (preferred)
• Experience with publications in peer-reviewed journals and conferences (preferred)
• Excellent problem-solving and communication skills, with the ability to work effectively in a team environment.

Pay

$138,000 - $198,000 (USD) + 15% bonus target + equity + benefits

Schedule

Nightly shift

Benefits

See benefits at Google.