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Metro Bangalore role at an established global company, senior specialization reduces broad applicant density.
Requires deep ML production and time-series expertise; telecom OSS preferred, so moderate cross-industry transferability.
Explicit 8+ years plus mandatory ML production, time-series, MLOps, and Kubernetes requirements.
Develop and productionize AI/ML models for anomaly detection, fault prediction, and root cause analysis across telecom network data.
Build and maintain the AI harness infrastructure including training, evaluation, inference, monitoring, and lifecycle management to deploy models from development to production.
Partner with data engineering teams to define data contracts and ensure robust, scalable pipelines for real-time AI-driven network operations.
Bachelor's or Master's degree in Computer Science, Engineering, Statistics or related field (or equivalent experience).
Minimum 8 years of experience in ML/AI engineering with production deployment on live high-volume datasets.
Proven experience with time-series ML models including anomaly detection, forecasting, or classification using deep learning and classical approaches.
Strong Python engineering skills and experience with SQL databases (ClickHouse, YugabyteDB, or PostgreSQL); solid software engineering practices including CI/CD and containerization.
Experienced in telecom OSS, network operations, or AIOps with a focus on operational AI model impact in production environments.
Skilled in building end-to-end ML infrastructure: from data handling and training to serving, monitoring, and retraining models reliably in critical applications.
Able to work with advanced AI technologies including LLMs, streaming data platforms, and rigorous evaluation methods like shadow deployments and human-in-the-loop feedback.