Silicon Architecture Engineer, PhD, University Graduate

A global technology company that builds innovative AI/ML hardware and infrastructure.
Hardware
Staff Software Engineer
In-Person
5,000+ Employees
5+ years of experience
AI

Description For Silicon Architecture Engineer, PhD, University Graduate

Google is seeking a Silicon Architecture Engineer to join their Technical Infrastructure team, focusing on shaping the future of AI/ML hardware acceleration. This role is crucial in developing and advancing Tensor Processing Unit (TPU) technology that powers Google's AI/ML applications. The position offers an exciting opportunity to work at the intersection of hardware and machine learning, collaborating with diverse teams to architect, model, and define next-generation TPUs.

As a Silicon Architecture Engineer, you'll be responsible for ML workload characterization, developing architectural models, and creating specifications for future AI/ML computing needs. You'll work closely with hardware design, software, compiler, and research teams to ensure optimal hardware/software interfaces and performance.

The role requires a PhD in a relevant field and strong experience with accelerator architectures and programming. You'll be part of the team that keeps Google's infrastructure running smoothly, ensuring users have the best possible experience. This is an excellent opportunity for someone passionate about hardware architecture and AI/ML technology to make a significant impact on Google's future computing capabilities.

The position offers the chance to work with cutting-edge technology in AI/ML hardware acceleration, collaborating with world-class engineers and researchers. You'll be at the forefront of developing next-generation TPUs, balancing performance, power, features, and cost considerations. Google's commitment to diversity, equality, and inclusion ensures a supportive work environment where innovation and creativity can thrive.

Last updated 11 days ago

Responsibilities For Silicon Architecture Engineer, PhD, University Graduate

  • Work on Machine Learning (ML) workload characterization and benchmarking. Propose capabilities and optimizations for next-generation TPUs
  • Develop architectural and microarchitectural power/performance models and evaluate quantitative and quantitative performance and power analysis
  • Collaborate with the architecture team on power, performance, area (PPA) trade-off analysis as part of product definition
  • Collaborate with partners in hardware design, software, compiler, ML model, and research teams for effective hardware/software codesign
  • Develop architecture specifications that meet current and future computing requirements for AI/ML roadmap

Requirements For Silicon Architecture Engineer, PhD, University Graduate

Python
  • PhD in Electronics and Communication Engineering, Electrical Engineering, Computer Engineering or related technical field, or equivalent practical experience
  • Experience of accelerator architectures and data center workloads
  • Proficiency in programming languages (e.g., C++, Python)
  • Experience with performance modeling tools (preferred)
  • Knowledge of arithmetic units, bus architectures, accelerators, or memory hierarchies (preferred)
  • Knowledge of high performance and low power design techniques (preferred)

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