Network Production Engineer (University Grad)

About the Role

This Network Production Engineer role is for university graduates who are passionate about large-scale network challenges. You will play a key role in ensuring the network is reliable, robust, and scalable for over a billion users. Automation and continuous improvement are central to this position, focusing on developing and deploying network designs, automation systems, and performance enhancements into the production network.

Key Responsibilities

• Build experience with Backbone, Data Center, and Network Infrastructure Engineering teams through rotational experiences during your first year.
• Build, manage, and maintain multi-vendor, multi-protocol data center and backbone networks.
• Develop optimized network monitoring systems.
• Design and deploy new network architectures.
• Develop automated methods to mitigate and remediate network events.
• Analyze data to diagnose and identify root causes of network issues.
• Participate actively in deep technical discussions.
• Develop and maintain consistency within the network infrastructure.

Requirements & Tech Stack

• Experience learning new concepts around network design and management.
• Experience with UNIX, TCP/IP, network fundamentals, or similar.
• Experience with computer networks.
• Experience coding in at least one language (Python/Golang/Rust/C++).

Qualifications

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization.

Preferred Qualifications

• Knowledge of Switching and Routing concepts and implementation.
• Knowledge of routing protocols BGP, OSPF, and ISIS.
• Knowledge of tunneling protocols MPLS, GRE, IPnIP.
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact.
• Experience adhering to and implementing responsible, ethical AI practices.
• Demonstrated ongoing AI skill development and staying current with emerging AI technologies.