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Network Quantitative Engineer

United States, Menlo Park 154000.00 - 217000.00 USD / Year · Job Posted March 13, 2026
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Job Description

Meta’s global network powers products for billions of people and is continually evolving to support the demands of next-generation applications. As part of the Network Infrastructure team, you’ll help design and operate one of the world’s largest, most complex networks—scaling infrastructure to meet the needs of emerging technologies and rapidly growing workloads. As a Network Quantitative Engineer, you will play a pivotal role in shaping the future of Meta’s network to accommodate significant growth across broad applications. You’ll build production-grade forecasting and optimization models, develop robust data foundations for decision-making, and collaborate with engineers and planners to ensure our infrastructure delivers the scale, performance, and reliability required for Meta's products and services. This is a unique opportunity to work at the intersection of quantitative analysis, systems engineering, and network infrastructure—where your contributions will help Meta deliver products and services to billions of users worldwide.

Job Responsibility

  • Build and productionize models for network forecasting, capacity planning, and performance risk, including uncertainty and sensitivity analysis
  • Design and maintain scalable datasets, feature pipelines, and monitoring systems to support modeling and decision workflows
  • Develop and apply algorithms, analytical tooling, and approaches—including what-if analysis, optimization, anomaly/change detection, causal inference, prescriptive analytics, and simulation etc.—to support infrastructure planning and drive improvements across Meta’s global network
  • Communicate results and recommendations through clear narratives, dashboards, and decision support tools
  • Partner cross-functionally to translate network infrastructure needs into measurable metrics, model requirements, and shipped solutions

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 2+ years of experience applying statistical, machine learning, or optimization methods to real-world problems
  • Programming skills in Python (or similar) and SQL, experience with large-scale data
  • Experience delivering production-quality analytics/models including testing, code review, and scheduled pipelines or services

Nice to have

  • Master’s or PhD in a quantitative field
  • Experience with time-series forecasting for large-scale systems and uncertainty quantification
  • Familiarity with networking fundamentals, or equivalent experience in large-scale infrastructure domains
  • Proven track record in algorithm design and implementation for large-scale data, optimization, anomaly detection, or network infrastructure challenges

What we offer

  • bonus
  • equity
  • benefits

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