Silicon AI/ML Architect, TPU, Google Cloud
Description For Silicon AI/ML Architect, TPU, Google Cloud
Google is seeking a Silicon AI/ML Architect to join their Technical Infrastructure team, focusing on TPU (Tensor Processing Unit) development for Google Cloud. This role combines hardware architecture expertise with machine learning specialization, working on custom silicon solutions that power Google's future products.
As a Silicon AI/ML Architect, you'll be at the forefront of developing sophisticated AI accelerator architectures, working with cutting-edge technology in Google's data centers. You'll collaborate with diverse teams across systems, software, and hardware domains to create optimal solutions that balance performance, power efficiency, and cost-effectiveness.
The position requires deep expertise in SoC architecture, particularly in machine learning applications, with significant experience in performance optimization and hardware-software interface design. You'll be responsible for developing comprehensive architecture specifications, evaluating various silicon solutions, and driving improvements across multiple generations of products.
This role offers the opportunity to work with world-class engineers, contribute to Google's AI infrastructure, and impact products used by millions globally. You'll be part of a team that pushes technological boundaries, developing custom silicon solutions that define the future of AI acceleration in cloud computing.
The ideal candidate combines strong technical skills in hardware architecture with a deep understanding of machine learning systems, bringing experience in SoC design, performance optimization, and cross-functional collaboration. This position offers the chance to shape the future of AI hardware at one of the world's leading technology companies.
Responsibilities For Silicon AI/ML Architect, TPU, Google Cloud
- Develop SoC architecture and Architecture specifications for AI/ML roadmap
- Evaluate different silicon solutions for executing Google's data center AI accelerator roadmap
- Collaborate with Systems and Software teams to create high performance hardware/software interfaces
- Collaborate with design, verification, emulation, physical design, packaging, and silicon validation stakeholders
- Evaluate power, performance, area tradeoffs and drive improvements across generations
Requirements For Silicon AI/ML Architect, TPU, Google Cloud
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field
- 10 years of experience in architecture of machine learning or graphics SoCs
- 8 years of experience with performance, power, area, cost tradeoff analysis for multi chiplet SoC architectures
- Experience with ASIC design flows, from specification to production
- Experience in SoC designs, RTL coding and integration flows
- Proficiency in a procedural programming language (C++, Python, Go)
- Knowledge of arithmetic units, bus architectures, accelerators, or memory hierarchies
- Knowledge of high performance and low power design techniques
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