As a Photonic Engineer for Machine Learning Systems at Google, you will focus on creating next-generation optical interconnect technologies for TPU systems. You will collaborate with both the optics and machine learning teams to develop technology roadmaps that enhance future machine learning systems. This role is part of the Platforms Infrastructure Engineering team, which designs and builds the hardware and software technologies that support Google's services. Your work will influence the design and manufacturing of systems that power Google's extensive computing infrastructure.

• PhD degree in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience.
• 2 years of experience working in a high-speed datacom technical environment.
• Experience with script writing and test and measurement system automation is preferred.
• Knowledge of large volume high-speed optical transceiver designs and manufacturing is preferred.
• Knowledge of data center network and machine learning system architectures is preferred.
• Proficiency in digital signal processing, high-speed optoelectronic circuit simulation or system modeling is preferred.

• Design low-cost and high-speed optical transceivers for data center applications.
• Develop optical systems and architectures to expand 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.

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.