The Machine Learning Hardware Architect role at Google focuses on shaping the future of AI/ML hardware acceleration, specifically through the development of Tensor Processing Unit (TPU) technology. The position involves driving the architecture and technical direction for high-performance computing systems that support Google's most demanding AI applications. The architect will work within a team that is redefining capabilities in AI and infrastructure, contributing to innovative products that impact millions of users worldwide. This role requires collaboration across multiple engineering teams to ensure effective system-level integration.

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
• 10 years of experience in computer architecture or hardware engineering.
• Experience with performance modeling, performance analysis, or hardware-software codesign.
• Experience leading the architecture and technical direction for hardware or system-level projects.

• Develop architectural specifications for next-generation high-performance computing systems.
• Collaborate with software and systems teams to define requirements for AI workloads.
• Perform architecture studies and drive performance, scalability, and power efficiency projections.
• Influence technical roadmaps and provide strategic leadership for hardware-software platforms.
• Drive cross-functional technical alignment across multiple engineering teams to ensure system-level integration.

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.