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Network Modeling and Optimization Engineer
- Meta (Menlo Park, CA)
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Summary:
Meta's global network comprised of cutting-edge platforms, is looking for a Network Modeling and Optimization Engineer to join the backbone and edge engineering team. This team is responsible for designing, implementing and supporting one of the world’s largest and complex networks. As a Network Modeling and Optimization Engineer, you will have a unique opportunity to influence optical and IP architectures, strategic network acquisitions, network design, deployment, and operations to shape the future network to accommodate hyper-exponential growth as well as internal product requirements.
Required Skills:
Network Modeling and Optimization Engineer Responsibilities:
1. Work with various teams to understand Meta's network, user base, performance constraints, and growth requirements
2. Create modeling framework for various networking problems such as cross-layer optimization under constraints such as latency/availability, demand uncertainty, risk assessment, and data center optimization
3. Work with procurement and other teams to devise strategies on hardware and network acquisitions around the globe
4. Data analysis from a large number of data sources to create a network strategy for capacities, location and facilities
5. Own the design, development, testing, and tuning of future capacity and topology models
Minimum Qualifications:
Minimum Qualifications:
6. 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
7. Experience using concepts of operations research, stochastic optimization, machine learning, queuing theory, probability theory to construct models for solving network optimization problems
8. Experience creating formulation using commercial mathematical optimization software like: Xpress, Gurobi, CPLEX, and other similar optimization tools
9. 2+ years of experience coding in higher-level languages (e.g., Python, C++, Go, etc.) coupled with experience creating models for optimization
Preferred Qualifications:
Preferred Qualifications:
10. Experience with large data sets and distributed computing (Hive/Hadoop)
11. Graduate work experience (masters or PhD) in the area of operations research, stochastic optimization, machine learning, queuing theory, probability theory
Public Compensation:
$117,000/year to $173,000/year + bonus + equity + benefits
**Industry:** Internet
Equal Opportunity:
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].
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