You will be joining the PE Network AI team that is responsible for the end-to-end health (performance and reliability) of Meta's backend datacenter networks that support our GPU based AI Training Clusters. You will build tools and use automation to efficiency scale how we mitigate real-time impact to the network, identify and investigate long-term trends into performance and risks in our data center networks, and drive innovative solutions to monitor and improve Meta's current and future DC network products. AI is essential in driving more relevant content recommendations and ads, enhancements in engagement, and improving user experiences. Network production engineer supporting the Network AI PE team is pivotal in ensuring that the backend DC network is robust, efficient, and capable of supporting Meta's AI training clusters effectively. This role is crucial for driving AI innovations and enhancements that impact various aspects of Meta's operations and services. Engineers that typically thrive in this role are hybrid software and network engineers with experience working with systems, how they fail, and how we can increase their reliability. You have the opportunity to dig into interesting challenges in the networking and software domains, at a scale that offers new challenges on a daily basis.