Silicon Automation Engineer

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world. We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

Design, test, deploy, and maintain robust software automation solutions that accelerate the hardware design lifecycle, reduce iteration time, and elevate hardware quality. Architect and write clean, testable, and robust applications primarily in Python, building the software backbone that integrates operational frameworks and drives our EDA pipelines. Harness Generative AI and LLMs as powerful tools within your software pipelines. Build agentic workflows to resolve specific bottlenecks in ASIC and SoC flows, taking responsibility for making these AI capabilities seamlessly accessible, intuitive, and practical for hardware engineering end users. Prototype and deploy tools in close partnership with hardware engineering teams, making a measurable impact on Google's custom chip development. Triage, debug, and resolve complex software defects, meticulously analyzing their impact on hardware, network, and lab operations.

Minimum qualifications: Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. 3 years of industry software development experience with systems and debugging. 3 years of experience in Python. Experience with software development and working with data structures and algorithms. Preferred qualifications: Experience utilizing GenAI tools, AI agents, or orchestrating Large Language Models (LLMs) to enhance and automate complex computing workflows. Experience building developer tools, automation systems, or scripting workflows that improve engineering velocity. Deep understanding of object-oriented or functional programming, system health diagnosis, and software test engineering. Excellent software architecture and design skills, with the flexibility to rapidly adapt to new programming languages and frameworks. Strong asynchronous communication skills, with experience or a willingness to support collaborations across global time zones.