Network Quantitative Engineer

Meta's global network, composed of cutting-edge platforms, is looking for a Network Quantitative Engineer to join the network infrastructure team. This team is responsible for designing, implementing and supporting one of the world’s largest and complex networks. As a Network Quantitative Engineer, you will have a unique opportunity to influence network planning decisions, shaping the future network to accommodate hyper-exponential growth as well as internal product requirements. Specifically, the team works in the intersection of: Quantitative analysis (statistical analysis, data exploration, experimentation, A/B testing), Systems (building data foundation and analytical frameworks), and Infrastructure (understanding networking and applying the appropriate model for each problem domain).

Responsibilities

• Work with large, complex data sets around the Meta data infrastructure and solve difficult analysis problems
• Develop, and deploy automated data and analysis pipelines to support prototyping and proof-of-concept efforts across the team
• Produce data visualizations and reporting for network demand, capacity, and performance, which will enable decision-making to internal partners
• Support end users on ad hoc data usage and in-depth experience for solution development across the team
• Leverage the Meta software and data infrastructure to develop efficient analytics
• Build cross-functional relationships with Network Planners, Software Engineers, and Network Engineers to understand their business needs

Minimum qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Preferred qualifications

• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies