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The role builds the pipelines, deployment systems, and testing infrastructure that move machine learning models from research into a production serving platform at scale. It covers CI/CD, A/B testing, monitoring, automated retraining, and production-like test environments. The ideal candidate has 4+ years in MLOps or infrastructure, with Python, Docker, Kubernetes, and production model serving experience.