AI/ML System Architect, Silicon

Google is seeking an AI/ML System Architect to join their innovative team working at the intersection of artificial intelligence, software, and hardware. This role focuses on developing next-generation technologies for AI efficiency and performance optimization, particularly in mobile computing environments. The position offers an opportunity to work on cutting-edge projects involving Generative AI, Large Language Models, and hardware optimization.

The ideal candidate will have strong expertise in AI/ML hardware and software systems, with experience in both theoretical and practical applications. You'll be working on enhancing Dynamic Voltage and Frequency Scaling (DVFS) for future AI applications, implementing energy-efficient solutions for various AI models, and analyzing hardware/software performance metrics to optimize AI processing on mobile devices.

As part of Google's mission to organize the world's information and make it universally accessible, you'll be contributing to technologies that impact millions of users worldwide. The role offers competitive compensation ($127,000-$187,000 base salary) plus additional benefits, equity, and bonuses. You'll be working with an extraordinarily creative, motivated, and talented team that pushes the boundaries of technology.

The position requires a bachelor's degree in a relevant field and at least 3 years of experience in AI/ML hardware or software. Knowledge of programming languages like Python, C/C++, Java, and frameworks like TensorFlow is essential. The role presents an excellent opportunity for those interested in the future of AI computing, particularly in mobile and energy-efficient applications.

Working at Google's locations in either San Diego or Mountain View, CA, you'll be at the forefront of AI innovation, developing solutions that combine the best of Google's AI, software, and hardware capabilities. This role is perfect for someone passionate about creating radically helpful experiences through technology while solving complex technical challenges in AI system architecture.