Minimum qualifications:
- Bachelor's degree in Computer Science, Electrical Engineering or equivalent practical experience.
- 8 years of experience in compilers (optimization, parallelization, etc.)
- Experience in Multi-Level Intermediate Representation (MLIR) or Low Level Virtual Machines (LLVM).
- Master's degree or PhD in Computer Science or any equivalent field.
- Experience in compiler development for accelerator-based architectures.
- Experience running a large program, or several projects simultaneously.
- Experience compiling for heterogeneous architectures across IPs, including but not limited to CPU, GPU, and NPUs.
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About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
EdgeTPU is a family of embedded machine learning (ML) accelerators aimed towards a set of applications, from smartphones to self-driving cars to data center applications. The compiler team is responsible for analysis, optimization, and compilation of machine learning models aiming the EdgeTPUGoogle'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 machine learning 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 with product managers, researchers in identifying key machine learning trends, future use cases, etc.
- Collaborate with machine learning model developers, researchers, and EdgeTPU hardware/software teams to accelerate the transition from research ideas to user experiences running on the EdgeTPU.
- Manage a team of experienced compiler engineers.