Senior MLOps Engineer (Onsite | Cairo, Egypt)Experience: 5–8 YearsEmployment Type: Full-TimeLocation: Cairo, Egypt (Onsite)Salary Range: 80,000 EGP – 100,000 EGP per monthAbout The OpportunityHireOn is recruiting for its reputed international client seeking a highly skilled Senior MLOps Engineer to lead the operationalization of machine learning models in production environments.This role requires a hands-on expert who can bridge Data Science and Cloud Engineering teams, ensuring scalable, secure, and automated ML systems on AWS infrastructure. The ideal candidate will drive end-to-end MLOps architecture, CI/CD automation, and cloud-native ML deployment strategies.Core Requirements Experience5–8 years of overall experience with minimum 3+ years in MLOps or production ML environments Strong experience managing the full ML lifecycle (training, deployment, monitoring, optimization) Proven ability to work independently and collaborate across cross-functional teams AWS & Cloud Expertise (Mandatory)Hands-on Experience WithAmazon SageMaker, S3, EC2, Lambda, IAM, CloudWatch, ECR, ECS, EKSStrong understanding of secure, scalable, and highly available AWS architectureMLOps & Machine LearningModel deployment and monitoring in production Experience with TensorFlow, PyTorch, or Scikit-learn Experiment tracking tools such as MLflow Model performance monitoring and drift detection DevOps & AutomationDocker and containerization CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline Infrastructure as Code (Terraform or CloudFormation) Programming & DataStrong Python programming expertise Experience with SQL and working knowledge of NoSQL databases Experience handling structured and unstructured datasets Key ResponsibilitiesDesign and implement scalable end-to-end MLOps pipelines Deploy and manage ML models using AWS-native services Build and maintain CI/CD pipelines for ML workflows Implement model monitoring, logging, and performance tracking Containerize ML applications and deploy on ECS/EKS Automate infrastructure using Terraform or CloudFormation Ensure system scalability, reliability, and security Troubleshoot ML pipelines and cloud infrastructure issues Collaborate closely with Data Science and Engineering teams to productionize ML solutions Nice to HaveExposure to feature stores and data versioning AWS Associate-level certification Understanding of ML governance, compliance, and model risk management Skills: aws codepipeline,terraform,tensorflow,aws sagemaker,mlops,python,aws,ml