Hardware Architecture Modeling Engineer, PhD, University Graduate, 2027 Start

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.
• - 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.

Minimum qualifications:

Preferred qualifications:

Qualifications

• Minimum 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++ or Python. Preferred qualifications: - Research or internship experience in AI/ML hardware acceleration. - Experience with publications in peer-reviewed journals and conferences. - Ability to demonstrate significant understanding of relevant domains such as architecture, digital design, and performance. - Excellent problem-solving and communication skills, with the ability to work effectively in a team environment.