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Network Quantitative Engineer

Meta
Posted 6 months ago, valid for 24 days
Location

Menlo Park, San Mateo 94025, CA

Salary

$122,000 - $181,000 per year

Contract type

Full Time

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Sonic Summary

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  • Meta is seeking a Network Quantitative Engineer to join their Network Infrastructure team, focusing on the design and operation of a large-scale network.
  • The role involves building production-grade forecasting and optimization models, as well as developing data foundations for informed decision-making.
  • Candidates should have a Bachelor's degree in a relevant technical field and at least 2 years of experience applying statistical or machine learning methods.
  • Proficiency in Python (or similar) and SQL is required, along with experience in delivering production-quality analytics and models.
  • The salary for this position ranges from $122,000 to $181,000 per year, in addition to bonuses, equity, and benefits.
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.

Responsibilities

  • 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


Minimum Qualifications

  • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
  • 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


Preferred Qualifications

  • 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


$122,000/year to $181,000/year + bonus + equity + benefits



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