Machine Learning Hardware Architect, Google Cloud

Google Cloud is seeking a Machine Learning Hardware Architect to shape the future of AI/ML hardware acceleration, specifically focusing on TPU (Tensor Processing Unit) technology. This role combines advanced computer architecture with machine learning expertise to drive innovation in Google's most demanding AI/ML applications.

The position involves working at the intersection of hardware and machine learning, developing custom silicon solutions that power Google's TPU infrastructure. You'll be responsible for advancing ML accelerator performance and efficiency through a comprehensive approach spanning compiler interactions, system modeling, power architecture, and host system integration.

Key responsibilities include prototyping new hardware features, optimizing accelerator designs under power and thermal constraints, and streamlining host-accelerator interactions. You'll work within the ML, Systems, & Cloud AI (MSCA) organization, which manages the infrastructure for all Google services and Google Cloud.

The role offers competitive compensation ($156,000-$229,000 + bonus + equity + benefits) and the opportunity to work on cutting-edge technology that impacts billions of users. You'll collaborate with specialized teams across XLA compiler, Platforms performance, and system design to bring innovations to production.

This position is ideal for candidates with strong backgrounds in both computer architecture and machine learning, offering the chance to work on next-generation AI hardware while contributing to Google's mission of advancing AI technology. The role combines technical depth with broad impact, as your work will directly influence the future of Google's AI infrastructure and capabilities.