Silicon Hardware Architecture Modeling Engineer, TPU, Google Cloud

Google is a global technology leader that develops innovative products and services used by billions of people
Hardware
Mid-Level Software Engineer
In-Person
5,000+ Employees
3+ years of experience
AI · Enterprise SaaS

Description For Silicon Hardware Architecture Modeling Engineer, TPU, Google Cloud

Google is seeking a Silicon Hardware Architecture Modeling Engineer for their TPU (Tensor Processing Unit) team within Google Cloud. This role is crucial in shaping the future of AI/ML hardware acceleration. The position offers an opportunity to drive cutting-edge TPU technology that powers Google's most demanding AI/ML applications. As part of a diverse team, you'll be pushing boundaries and developing custom silicon solutions that power Google's TPU future. You'll work closely with hardware and software architects to model, analyze, and define next-generation Tensor Processing Units.

The Technical Infrastructure team at Google is responsible for building and maintaining the architecture that keeps everything running smoothly. This team develops and maintains data centers and builds next-generation Google platforms, making Google's entire product portfolio possible. The team takes pride in being the engineers' engineers and focuses on keeping networks up and running to ensure users have the best and fastest experience possible.

This role combines hardware architecture, machine learning, and performance optimization, making it perfect for someone passionate about advancing AI hardware technology. You'll be working on critical projects that directly impact Google's AI infrastructure, from workload characterization to architectural modeling and optimization. The position offers the opportunity to collaborate with various teams across hardware design, software, compiler development, and ML research, ensuring a broad exposure to cutting-edge technology development.

The ideal candidate will bring together expertise in computer architecture, performance analysis, and software development, with a particular focus on ML hardware acceleration. This role offers the chance to be at the forefront of AI hardware development, working on technology that powers some of the world's most advanced AI applications.

Last updated 3 months ago

Responsibilities For Silicon Hardware Architecture Modeling Engineer, TPU, Google Cloud

  • Work on Machine Learning (ML) workload characterization and benchmarking
  • Conduct performance and power analysis and evaluate proposals
  • Develop architectural and microarchitectural models to enable quantitative analysis
  • Collaborate with partners in hardware design, software, compiler, ML model and research teams for effective hardware/software codesign
  • Propose capabilities and optimizations for next-generation Tensor Processing Units (TPU) and chip roadmap

Requirements For Silicon Hardware Architecture Modeling Engineer, TPU, Google Cloud

Python
  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience
  • 3 years of experience in computer architecture performance analysis and optimization, or a PhD degree in lieu of industry experience
  • Experience in developing software systems in C++
  • Experience in hardware and software co-design (preferred)
  • Experience in analyzing workload performance and creating benchmarks (preferred)
  • Experience developing in Python (preferred)
  • Knowledge of processor design or accelerator designs and mapping Machine Learning (ML) models to hardware architectures (preferred)
  • Knowledge of design of digital logic at the Register Transfer Level (RTL) using Verilog (preferred)

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