Machine Learning Physical Design Engineer

Join Google's innovative hardware team as a Machine Learning Physical Design Engineer, where you'll be at the forefront of developing custom silicon solutions that power Google's direct-to-consumer products. This role combines traditional physical design expertise with cutting-edge machine learning applications to optimize chip design. You'll work on improving Power Performance Area (PPA) using ML techniques, collaborating with design, CAD, and machine learning teams across Alphabet, including Google DeepMind.

The position requires expertise in physical design flow, including floorplanning, place and route, clock and power planning, timing analysis, and Power Delivery Network (PDN) analysis. You'll apply machine learning algorithms ranging from logistic regression to deep neural networks and reinforcement learning to solve complex technical problems in chip design.

As part of Google's mission to organize the world's information and make it universally accessible, you'll contribute to creating radically helpful experiences by combining the best of Google AI, Software, and Hardware. The team focuses on making computing faster, seamless, and more powerful, ultimately aiming to improve people's lives through technology.

This is an excellent opportunity for someone with both physical design experience and machine learning knowledge to shape the future of Google's hardware experiences. You'll be working on products used by millions worldwide, with access to Google's vast resources and cutting-edge technology. The role offers the chance to work with world-class experts in both chip design and machine learning, while contributing to innovations that push the boundaries of what's possible in hardware design.