Senior MLOps Engineer (Onsite | Cairo, Egypt)
Experience: 5–8 Years
Employment Type: Full-Time
Location: Cairo, Egypt (Onsite)
Salary Range: 80,000 EGP – 100,000 EGP per month
About The Opportunity
HireOn 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 Experience
- 5–8 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 With
Amazon SageMaker, S3, EC2, Lambda, IAM, CloudWatch, ECR, ECS, EKS
Strong understanding of secure, scalable, and highly available AWS architecture
MLOps & Machine Learning
- Model 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 & Automation
- Docker and containerization
- CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline
- Infrastructure as Code (Terraform or CloudFormation)
Programming & Data
- Strong Python programming expertise
- Experience with SQL and working knowledge of NoSQL databases
- Experience handling structured and unstructured datasets
Key Responsibilities
- Design 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 Have
- Exposure 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
