Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
In this role, you will work with system teams and the CPU Architecture team to develop an understanding of the CPU, System on a Chip (SoC), performance metrics, benchmarks/measuring tools, and available optimization knobs. You will define methods and technologies to model CPU performance at different accuracy levels by supporting architectural explorations and decision-making. You will correlate performance projections with measured post-silicon data.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Clouds Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Responsibilities
Design, develop, test, deploy, maintain, and improve Central Processing Unit (CPU) software modeling and other software tools.
Manage project priorities, deadlines, and deliverables.
Collaborate with hardware and software CPU architecture teams, SOC performance modeling team, and other Google Software teams.
Requirements: Minimum qualifications:
Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent practical experience.
2 years of experience with software development in C++ programming language, or 1 year of experience with an advanced degree.
2 years of experience with data structures or algorithms.
2 years of experience with performance, systems data analysis, visualization tools, or debugging.
Experience in performance modeling, performance analysis, and workload characterization.
Preferred qualifications:
Masters degree or PhD in Engineering, Computer Science, or a related technical field.
Experience in modern, high-performance CPU/ML architecture and micro-architecture.
Ability to learn coding languages as needed.
Excellent object-oriented, database design, and SQL skills.
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