Senior ML Engineer
LocationCairo, Cairo Governorate, Egypt
Typefull-time
SenioritySenior
Experience4+ yrs
DepartmentEngineering
Company size1,001–5,000 people
PostedOct 4, 2026 · 1w ago
Verified live22h ago
At a glanceSummarised by Seekless from the posting.
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 (churn prediction, customer clustering/segmentation, demand forecasting, 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, 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
Skills
Python
SQL
MLflow
Dataiku
Spark
Feature Stores
About the role
Job Description
We are looking for a Senior Machine Learning Engineer with strong experience in the Telecommunications (Telco) domain to design, develop, deploy, and maintain production-ready machine learning solutions.
The ideal candidate will have hands-on experience in ML model development, feature engineering, deployment, monitoring, and retraining, with a strong understanding of MLOps practices and the end-to-end machine learning lifecycle.
Key Responsibilities
•
Develop and deploy production-grade machine learning models for Telco use cases.
•
Build ML solutions for use cases such as 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
Requirements
•
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, such as:
•
Churn prediction
•
Customer clustering/segmentation
•
Demand forecasting
•
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
•
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.
More roles at SSC HR Solutions