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Tier-1 brand, Bengaluru metro location and mid-level ML role increase applicant competition.
Requires specialized ML engineering plus network/optical telemetry domain knowledge, limiting cross-industry transferability.
Explicit 5+ years, deep ML, Spark, and MLOps requirements and degree preferences create strict filters.
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Design, deploy, and optimize data pipelines, statistical algorithms, and machine learning models for monitoring and forecasting health of enterprise routing and optical infrastructure.
Lead transition of ML models from R&D to production ensuring scalability, low-latency, and high availability on Datacenter Assurance platform.
Collaborate with network hardware engineers and software architects to integrate predictive analytics into monitoring workflows for anomaly detection and diagnostics.
5+ years professional experience in Data Science, Machine Learning, or AI Engineering roles.
Expert-level proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
Experience with time-series forecasting, anomaly detection, multivariate analysis, and production data engineering using Apache Spark.
Education: PhD in Statistics, OR Operations Research, OR Computer Science with 3+ years relevant experience; OR Master's degree with at least 5-6 years relevant experience.
Strong expertise bridging advanced ML modeling (e.g., BiLSTM, Transformers) with scalable production engineering using CI/CD, Docker, Kubernetes, and MLOps.
Domain experience with network telemetry, optical systems, and hardware performance metrics for predictive maintenance.
Proven ability to design and deploy real-time, low-latency analytics solutions on big data platforms collaborating effectively with cross-functional technical teams.