Software Engineer, Machine Learning Compilers

1 Month ago • 1 Years + • Artificial Intelligence

Job Summary

Job Description

As a Software Engineer, you will work on developing Machine Learning (ML) compilers for the Tensor TPU to accelerate Generative AI and other machine learning models running on custom hardware accelerators. You will manage project priorities, deadlines, and deliverables. Responsibilities include building compilers and tools that map ML models to the hardware ISA, evaluating trade-offs of parallelization strategies (performance, power, energy, memory), collaborating with ML researchers to improve the compiler, and collaborating with hardware engineers to evolve future accelerators. The role requires expertise in C++, data structures, algorithms, and ideally experience with power/performance optimizations, machine learning, compilers, and hardware parallelism.
Must have:
  • Bachelor's degree or equivalent experience
  • 1 year C++ experience
  • Data structures and algorithms expertise
  • Build ML compilers for Tensor TPU
  • Evaluate parallelization strategies
Good to have:
  • Master's degree in Computer Science
  • Power & performance optimization experience
  • Machine learning experience
  • Compiler experience
  • Hardware understanding (parallelism)

Job Details

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 1 year of experience in C++.
  • Experience in data structures and algorithms.

Preferred qualifications:

  • Master's degree in computer science or equivalent practical experience.
  • Experience in power and performance optimizations.
  • Experience with machine learning.
  • Experience with compilers.
  • Understanding of hardware, especially hardware that provides a degree of parallelism.

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.

As a Software Engineer you will work on developing Machine Learning (ML) compilers for the Tensor TPU to accelerate Generative AI and other machine learning models running on custom hardware accelerators. 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 (with a particular focus on always-on computing use cases) to the hardware ISA.
  • Evaluate various trade-offs of different parallelization strategies such as performance, power, energy and memory consumption.
  • Collaborate with machine learning researchers to constantly improve the domain-specific compiler.
  • Collaborate with hardware engineers to evolve future accelerators.

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