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 development for Google Cloud. This role combines advanced machine learning hardware architecture with practical implementation, requiring deep expertise in SoC design and AI accelerator development. The position offers the opportunity to shape the future of Google's AI infrastructure, working on cutting-edge technology that powers millions of users worldwide.
The ideal candidate will bring 10+ years of experience in machine learning or graphics SoC architecture, with proven expertise in multi-chiplet SoC architectures and ASIC design flows. You'll be responsible for developing sophisticated SoC architectures that drive Google's AI/ML roadmap, collaborating with various teams to optimize hardware-software interfaces, and ensuring optimal performance across all design aspects.
Working at Google's Bengaluru office, you'll be part of a team that pushes the boundaries of what's possible in AI acceleration, developing custom silicon solutions that power Google's direct-to-consumer products. The role offers the chance to work with world-class engineers and contribute to technology that impacts users globally.
This position requires a unique blend of technical expertise in hardware architecture, machine learning, and system design, combined with strong collaborative skills to work effectively with multiple stakeholders. You'll be at the forefront of AI hardware development, making critical decisions that balance performance, power efficiency, and cost considerations.
The role offers the opportunity to work on groundbreaking technology while being part of Google's inclusive culture that values diversity and innovation. You'll contribute to the architecture behind products used by millions, ensuring they deliver unparalleled performance and efficiency.
Responsibilities For Silicon AI/ML Architect, TPU, Google Cloud
- Develop SoC architecture and Architecture specifications that meet current and future computing requirements for AI/ML roadmap
- Evaluate different silicon solutions for executing Google's data center AI accelerator roadmap: off-the-shelf components, vendor co-developments, custom designs, and chiplets
- 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, a related field, or equivalent practical experience
- 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
- Experience working with software teams optimizing the hardware/software interface
- Experience in estimating performance by analysis and modeling
- Knowledge of high performance and low power design techniques
- Knowledge of arithmetic units, bus architectures, accelerators, or memory hierarchies
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