Job DescriptionWe are looking for a Senior Machine Learning Engineer with strong experience in the Telecommunications Telco domain to design develop deploy and maintain productionready machine learning solutionsThe ideal candidate will have handson experience in ML model development feature engineering deployment monitoring and retraining with a strong understanding of MLOps practices and the endtoend machine learning lifecycleKey ResponsibilitiesDevelop and deploy productiongrade machine learning models for Telco use casesBuild ML solutions for use cases such as customer churn prediction customer segmentationclustering and demand forecastingPrepare clean transform and analyze large customer datasetsPerform feature engineering and develop relevant features for machine learning modelsTrain validate and evaluate supervised and unsupervised machine learning modelsUse Python for data preparation model development validation and automationUse SQL to access extract transform and process data from various sourcesImplement and maintain MLOps pipelines across the ML lifecycleManage model versioning deployment production monitoring and retrainingMonitor model performance and datamodel drift in production and take appropriate corrective actionsCollaborate with data engineers data scientists and business stakeholders to deliver scalable ML solutionsEnsure ML models are reliable maintainable and suitable for production environmentsContinuously improve existing models features and ML workflows based on production resultsRequirementsRequirements4 years of experience in Machine Learning Data Science or a related fieldTelcoTelecommunications domain experience is a MUSTProven experience building and deploying production ML models for Telco use cases such asChurn predictionCustomer clusteringsegmentationDemand forecastingCustomer behavior predictionStrong knowledge of supervised and unsupervised machine learning techniquesStrong handson experience with Python for data preparation feature engineering and ML model developmentStrong SQL skills for accessing processing and analyzing customer dataHandson experience with feature engineering and customer data preparationPractical MLOps experience includingModel versioningModel deploymentProduction monitoringModel retrainingExperience with MLflow or an equivalent MLOpsmodel lifecycle management platformExperience taking ML models from development through production deployment and ongoing monitoringAbility to evaluate model performance and identify opportunities for model improvementStrong understanding of the endtoend machine learning lifecycleExperience with Dataiku or equivalent enterprise ML platforms is a plusExperience with Spark Feature Stores or uplift modelling is a plus
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