SSC HR Solutions

Senior Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeRemote in EgyptNo salary listedRemote

About the Job

Requirements

At least 4 years of experience in Machine Learning, Data Science, or a related field.
Telecommunications domain experience is required.
Proven experience building and deploying production machine-learning models for telecommunications use cases, such as churn prediction, customer clustering or 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 machine-learning 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 or model lifecycle management platform.
Experience taking machine-learning 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.

Responsibilities

Develop and deploy production-grade machine-learning models for telecommunications use cases.
Build machine-learning solutions for use cases such as customer churn prediction, customer segmentation or 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 machine-learning lifecycle.
Manage model versioning, deployment, production monitoring, and retraining.
Monitor model performance and data or model drift in production and take appropriate corrective actions.
Collaborate with data engineers, data scientists, and business stakeholders to deliver scalable machine-learning solutions.
Ensure machine-learning models are reliable, maintainable, and suitable for production environments.
Continuously improve existing models, features, and machine-learning workflows based on production results.

Desired Qualifications

Experience with Dataiku or equivalent enterprise machine-learning platforms.
Experience with Spark, feature stores, or uplift modelling.

Senior ML Engineer

SSC HR Solutions · Cairo, Egypt (Remote) · — · Posted 2026-10-04

Workplace: remote

Department: Engineering

Description

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

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.

Apply

Apply at SSC HR Solutions

About the Company

SSC HR Solutions

Company size: Not listed
Company stage: Not listed
Total funding: Not listed
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