Google

Silicon Validation Engineer, HBM, Google Cloud

Sunnyvale, CA, USA

Sponsorship not specified$138k-$198kDetected 12 hours ago

PythonC++GCPMachine LearningVerilogElectrical EngineeringTest AutomationResearch

About the role

About the job In this role, you'll work to shape the future of AI/ML hardware acceleration.

Develop detailed silicon test plans, based on design specifications and coordination with a cross-functional silicon team (architecture, design, software, firmware) for Google's Tensor Processing Units (TPUs).
Implement test plans by developing software tests and flows for system validation and verification, then utilize it all to test hardware, collect data, and characterize the operation of HBMs in both test chips and production silicon.

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
2 years of experience in bringing up ASICs, performing functional and performance validation, or debugging failures.
Experience scripting in Python or a similar programming language.

Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture, or a related field.
2 years of experience with C++/Python software design principles.
Experience bringing up high-power ASICs and working with memories.
Experience with reading hardware description languages (SystemVerilog) and chip design flow, and building test automation tools and scripts.
Passion for unusual computer architectures.
In this role, you'll work to shape the future of AI/ML hardware acceleration.
You will work closely with Silicon Validation, HBM technologists, and pre-silicon teams during the development phase of the ASIC life-cycle, ensuring proper features are in place for post-silicon validation and debug.
Once silicon is in the lab, you will collect and help interpret data alongside system software and software test infrastructure developers to ensure the HBM subsystem has met the threshold for production release.

This listing is sourced directly from Google's careers page and normalized into a canonical job model.