Tensor Processing Unit Architect, Silicon
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- Master's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.
- 2 years of experience in computer or chip architecture, performance, or compiler.
- Experience with one or more general purpose programming languages (e.g., C, C++, Python).
- PhD degree in Computer Science or Electrical Engineering.
- Experience with domain-specific accelerators.
- Experience with distributed/parallel programming.
- Experience with hardware/software co-design for machine learning.
- Experience with simulator development and micro-architecture.
About the job
As a Tensor Processing Unit Architect, you will develop the next generation machine learning accelerator architecture for on-device machine learning applications. You will be responsible for balancing priorities to ensure delivery on architecture goals.
Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.
- Define the next generation machine learning accelerator architecture for on-device machine learning applications.
- Explore various trade-offs of future architecture designs in terms of performance, power, energy, and area.
- Collaborate with compiler engineers to optimize compilation results and extend the compiler infrastructure. Initiate new feature modeling in the architecture simulator.
- Collaborate with researchers and application developers to enable the latest machine learning work and to optimize the performance.
- Work collaboratively with full stack software engineers to partition machine learning workload to selected compute engines to enhance user experiences.
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