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.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
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 SOC software modeling and other software tools.
Manage individual project priorities, deadlines, and deliverables.
Collaborate with hardware and software 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.
5 years of experience with software development in C++, and with data structures/algorithms.
Experience in performance modeling, performance analysis, and workload characterization.
Preferred qualifications:
Masters degree or PhD in Engineering, Computer Science, or a related technical field.
4 years of experience with performance, systems data analysis, visualization tools, or debugging.
Experience in modern, high-performance Networking architecture and micro-architecture.
Ability and interest to learn other coding languages as needed.
Excellent object-oriented, database design, and SQL skills.
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