The Machine Learning Hardware Architect role at Google focuses on shaping the future of AI/ML hardware acceleration. The position involves driving the development of custom silicon solutions, particularly Tensor Processing Units (TPUs), that support Google's demanding AI applications. The architect will work within a team dedicated to redefining computing infrastructure, ensuring high throughput, reliability, and efficiency. This role offers the opportunity to influence the evolution of intelligent data centers and enterprise hardware.

• 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.