ML Operations Engineer
Core
Operate traditional data science and machine learning models in production, executing deployments, retraining, and monitoring for drift to maintain accuracy for predictive models like churn, fraud, and network forecasting.
Role type
ML Operations Engineer (hands-on IC)
Builds
Production ML models for churn, fraud, and network forecasting
Domain
Telecommunications / Data Science
Deliverable
production ML models
Required skills
Python, CI/CD pipelines, model deployment, model registries, lineage management, drift monitoring, champion-challenger methods, backtesting, cloud ML services
Preferred skills
ML or cloud certifications, telco domain experience, large-scale data environment experience
Technologies
Python, CI/CD tooling, Cloud ML services
Responsibilities
Execute model deployments and retraining through approved pipelines; Monitor data, feature, and concept drift; Validate models using backtesting or champion-challenger methods; Run optimization algorithms for intervention selection; Maintain model lineage records; Execute rollbacks to previous models or baselines; Prepare model-performance, cost, and quota reports.
