Staff Software Engineer, ML Compilers, Silicon
Indexed description
- Bachelor's degree or equivalent practical experience.
- 8 years of experience with software development in C++, and with data structures/algorithms.
- 5 years of experience with compilers (optimization, parallelization, etc.).
- 3 years of experience with software design and architecture.
- Experience in compiler development in the context of accelerator-based architectures.
- PhD in Computer Science, or a related field.
- Experience in Multi-Level Intermediate Representation (MLIR) or Low Level Virtual Machines (LLVM).
- Experience with hardware-software codesign.
- Experience in optimizing ML model inference on device.
- Solid understanding of hardware such as CPU, GPU, or TPU.
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
- Work as part of the EdgeTPU compiler team, including analyzing and improving the compiler quality and performance on optimization decisions, correctness and compilation time.
- Develop parallelization and scheduling algorithms to optimize compute and data movement costs to execute ML workloads on the EdgeTPU.
- Work with EdgeTPU architects to design future accelerators, the hardware/software interface, and co-optimizations of the next generation EdgeTPU architectures.
- Work on efficient mapping of generative AI models and other key workloads into EdgeTPU instructions through the compiler.
- Work with Product Managers, Researchers in identifying key ML trends, future use cases, etc. Closely collaborate with ML model developers, researchers, and EdgeTPU hardware/software teams to accelerate the transition from research ideas to user experiences running on the EdgeTPU.
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