ML Engineer, Network Intelligence

ML Engineer, Network Intelligence responsible for turning Colt’s network telemetry into production ML systems. Key duties include cleaning and structuring real-world network data, building classical ML models for anomaly detection, predictive maintenance, and traffic forecasting, and getting those models into production. You will work with network telemetry data in GCP BigQuery, build the data pipeline and feature engineering layer for ML on network data, and develop models for anomaly detection, predictive maintenance, traffic forecasting, and capacity planning. Longer term, you will contribute to the AI WAN closed-loop architecture by defining what network state the model consumes and what control plane actions it can influence. You will not be required to be a deep learning researcher or a network engineer, but you should have enough network domain knowledge to understand the data and strong ML fundamentals to ensure trustworthy production models. MLOps tooling experience is a plus but not day-one required. You will have opportunities to grow into ownership of the model lifecycle layer as the team matures. The role sits at the intersection of ML and network engineering, offering direct exposure to Colt’s global fiber network and the AI WAN product as a strategic revenue opportunity.