About the job

Be part of a diverse 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.

As a Software Engineer, you will work on developing Machine Learning (ML) compilers for the Tensor TPU to accelerate machine learning models running on custom hardware accelerators. In this role, you will manage project priorities, deadlines, and deliverables.

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.

Responsibilities

• Build compilers and tools that map Machine Learning models to the hardware Information Security Assurance.
• Evaluate various trade-offs of different parallelization strategies such as performance, power, energy, and memory consumption.
• Collaborate with machine learning researchers to improve the domain-specific compiler.
• Collaborate with hardware engineers to evolve future accelerators.