AT&T is looking to build automation tooling for network design and capacity planning and network flow analysis for large-scale ISP networks to improve efficiency, reliability, and scalability.
Requirements
- Strong knowledge of key network flow concepts: nodes, edges, capacities, source/sink nodes, flow conservation, and bottleneck identification.
- Proven experience in solving network flow optimization problems for computer networks.
- Experience with advanced topics such as Multi-Commodity Flow, Dynamic Network Flow, and Stochastic Network Flow, Minimum cost flow, maximum flow problems, bin packing, knapsack and other complex graph theory problems.
- Expertise in Linear programing and Mixed integer linear models
- Expertise in representing and modeling networks using adjacency matrices and lists, with a focus on proper abstraction for efficient computation.
- Experience in data engineering, data science, data cleaning, and outlier removal for large datasets.
- Knowledge of statistical techniques for data analysis and validation, with experience in models such as ARIMA, Holt-Winters exponential smoothing, time series regression, and Bayesian networks for network traffic forecasting and anomaly detection.
Responsibilities
- Develop and maintain automated tools for network capacity planning and real-time capacity checking, leveraging advanced graph theory and network flow optimization.
- Solve complex network flow problems by modeling computer networks as graphs with nodes (e.g., routers, switches) and edges (links), each with capacity determinations required for each edge and flow constraints on both end to end and edge basis.
- Formulate and solve problems such as Maximum Flow, Minimum Cost Flow, Shortest Path, Transportation, and Multi-Commodity Flow to support network design and operation.
- Apply a wide range of optimization techniques—such as Ford-Fulkerson, Edmonds-Karp, Dinic’s, Preflow-Push, and cycle canceling algorithms—to maximize or minimize commodity flow, identify network bottlenecks, and optimize resource utilization.
- Model network capacity planning scenarios using directed or undirected graphs, implementing adjacency list/matrix representations for efficient storage and computation.
- Design algorithms and tooling for implementing heavily meshed and tiered, reliable, large scale carrier grade network topologies capable of carrying Order of Exabytes per second of traffic with quality of service constraints.
- Design and implement network performance troubleshooting tools.
Other
- This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.
- Excellent communication, analytical, and problem-solving skills.
- Individual starting salary within this range may depend on geography, experience, expertise, and education/training.
- Ready to join our team? Apply today
