Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. 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 on efficient mapping of AI models and other key workloads into EdgeTPU instructions through the compiler.
- Manage a team of experienced compiler engineers.
- Collaborate with Machine Learning (ML) model developers, researchers, and EdgeTPU hardware/software teams to accelerate the transition from research ideas to exceptional user experiences running on the EdgeTPU.
Qualifications
Minimum qualifications:
- Bachelor's degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience.
- 8 years of experience in compiler development, including machine learning optimization and experience with ML accelerators (e.g., Tensor Processing Units (TPUs) or Graphics Processing Units (GPUs))
- 8 years of experience with embedded operating systems and experience with compilers (e.g., optimization, parallelization, etc.)
- 2 years of experience in a people management or team leadership role.
- Experience in Multi-Level Intermediate Representation (MLIR) or Low Level Virtual Machines (LLVM).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 3 years of experience working in a complex, matrixed organization.
- Experience compiling for heterogeneous architectures across IPs, including but not limited to CPU, GPU, and NPUs.
- Compiler development experience in the context of accelerator-based architectures, vector instruction optimizations, or vectorizing compilers.