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Strong Tier-1 brand, mid-level (5+ years) role, and metro location increase competition density.
Highly specialized network telemetry and optical systems expertise reduces cross-industry transferability.
Explicit 5+ years plus mandatory Spark, DL frameworks, and MLOps/production skills enforce strict filters.
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Lead design and deployment of predictive and real-time health analytics platforms monitoring enterprise-grade routing and optical network hardware.
Develop and optimize data pipelines, statistical algorithms, and machine learning models (time-series forecasting, anomaly detection) for network performance and failure prediction.
Transition models from research into production ensuring scalability, low latency, and high availability, collaborating closely with network hardware and software teams.
5+ years of professional experience in Data Science, Machine Learning, or AI Engineering roles.
Expert proficiency in Python and deep learning frameworks like PyTorch or TensorFlow; advanced experience with Apache Spark (PySpark/Scala).
Strong background in time-series forecasting, anomaly detection, multivariate analysis, and production-level coding including CI/CD, Docker, Kubernetes.
Education: PhD preferred with 3+ years relevant experience or Master's degree with 5-6+ years relevant experience.
Experienced in blending data engineering and advanced machine learning specifically for infrastructure/network telemetry and optical systems data.
Capable of building and deploying complex stateful, distributed analytics systems using production ML frameworks and scalable data pipelines.
Skillful in collaborating across hardware and software teams to integrate data-driven insights into network monitoring and assurance platforms under real-time constraints.