Senior Software Engineer, ML Compilers, Google Silicon

2 Weeks ago • 5 Years + • Research & Development

Job Summary

Job Description

This role involves working as part of the EdgeTPU compiler team, focusing on improving compiler quality and performance. Responsibilities include developing parallelization and scheduling algorithms to optimize ML workloads on the EdgeTPU, collaborating with architects to design future accelerators and hardware/software interfaces, efficiently mapping generative AI models onto EdgeTPU instructions, and working with product managers and researchers to identify key ML trends and future use cases. The ideal candidate will have experience with compilers (parallelization, etc.), ML model development, and C++. Experience with MLIR or LLVM, optimizing ML models for inference, hardware-software codesign, and compiler development for accelerator-based architectures are preferred.
Must have:
  • 5+ years software development experience
  • Experience with compilers or ML model development
  • Experience with C++
  • Data structures/algorithms expertise
  • Software testing, maintenance, and launch experience
Good to have:
  • Master's/PhD in CS or related field
  • MLIR or LLVM experience
  • ML model optimization for inference
  • Hardware-software codesign experience
  • Compiler development for accelerator-based architectures

Job Details


Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
  • 5 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • Experience with compilers (e.g., parallelization, etc.) or ML model development.
  • Experience with C++.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • Experience in Multi-Level Intermediate Representation (MLIR) or Low Level Virtual Machines (LLVM).
  • Experience in optimizing ML models for inference.
  • Experience with hardware-software codesigns.
  • Experience with compiler development in the context of accelerator-based architectures.

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.

In this role, you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

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, and 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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