Senior ML Engineer

SSC HR Solutions

. Develop and deploy production-grade machine learning models for Telco use cases .

Posted 10/5/2026full-timeRemote • EgyptSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying production-grade machine learning models specifically for Telco use cases, with strong capabilities in Python, SQL, and MLOps practices. Proven ability to manage the entire machine learning lifecycle, from data preparation to model monitoring and improvement.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProgrammingSQL Data ProcessingMLOps ImplementationTelco Domain Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningFeature EngineeringData PreparationModel ValidationModel EvaluationSupervised LearningUnsupervised LearningCustomer SegmentationDemand ForecastingChurn Prediction

Soft Skills

CollaborationProblem SolvingCommunication

Tools & Technologies

MLflowDataikuSparkFeature Stores

Industry Keywords

TelecommunicationsCustomer Behavior PredictionMLOps PipelinesModel VersioningProduction Monitoring

Tech Stack

Tools & technologies

PythonSparkSQL

About the role

Key responsibilities & impact

Develop and deploy production-grade machine learning models for Telco use cases
Build ML solutions for customer churn prediction, customer segmentation/clustering, and demand forecasting
Prepare, clean, transform, and analyze large customer datasets
Perform feature engineering and develop relevant features for machine learning models
Train, validate, and evaluate supervised and unsupervised machine learning models
Use Python for data preparation, model development, validation, and automation
Use SQL to access, extract, transform, and process data from various sources
Implement and maintain MLOps pipelines across the ML lifecycle
Manage model versioning, deployment, production monitoring, and retraining
Monitor model performance and data/model drift in production and take appropriate corrective actions
Collaborate with data engineers, data scientists, and business stakeholders to deliver scalable ML solutions
Ensure ML models are reliable, maintainable, and suitable for production environments
Continuously improve existing models, features, and ML workflows based on production results

Requirements

What you’ll need

4+ years of experience in Machine Learning, Data Science, or a related field
Telco/Telecommunications domain experience is a MUST
Proven experience building and deploying production ML models for Telco use cases, including churn prediction, customer clustering/segmentation, demand forecasting, and customer behavior prediction
Strong knowledge of supervised and unsupervised machine learning techniques
Strong hands-on experience with Python for data preparation, feature engineering, and ML model development
Strong SQL skills for accessing, processing, and analyzing customer data
Hands-on experience with feature engineering and customer data preparation
Practical MLOps experience, including model versioning, model deployment, production monitoring, and model retraining
Experience with MLflow or an equivalent MLOps/model lifecycle management platform
Experience taking ML models from development through production deployment and ongoing monitoring
Ability to evaluate model performance and identify opportunities for model improvement
Strong understanding of the end-to-end machine learning lifecycle
Experience with Dataiku or equivalent enterprise ML platforms is a plus
Experience with Spark, Feature Stores, or uplift modelling is a plus