Photonic Engineer, Machine Learning Systems, Platforms, PhD, University Graduate

About the position

The Platforms Team designs and builds the hardware, software and networking technologies that power all of Google's services. Google's machine learning systems use the latest and greatest optical transceiver and optical switching technologies to scale and interconnect TPU and Graphics Processing Unit (GPU) processors. As a Photonic Engineer for machine learning systems, you will be responsible for creating next generation optical interconnect technologies for TPU systems. You will work with both the optics team and machine learning team to lay out the optical technology roadmaps to scale future generation machine learning systems. 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.

Responsibilities

• Design low-cost and high-speed optical transceivers for data center applications.
• Design optical systems to scale TPU and GPU superpods.
• Identify, research, and evaluate emerging photonic networking technologies.
• Explore optical technologies to disaggregate and improve the efficiencies of future computing systems.

Requirements

• PhD degree in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience.
• Academic, research, or internship experience in digital coherent optical transmission systems and fiber optical components and packaging techniques.
• Experience with high-speed optical transceiver designs and manufacturing, high speed electronics, and signal integrity in an industry, internship, or graduate lab setting.

Nice-to-haves

• Experience working in a data center or hyperscale technical environment.
• Experience with TPU/GPU superpod systems.
• Experience with script writing and test and measurement system automation.
• Experience with data center network architectures.
• Understanding of signal integrity, especially for high speed interfaces, and best practices to collect accurate SI data.

Benefits

• Bonus
• Equity
• Health benefits