Job Description: MLOps & AI Platform Engineer
Job Title: MLOps & AI Platform Engineer
Experience: 3–11 Years
Location: Riyadh - Onsite
Employment Type: Full-Time
Job Overview
We are seeking a skilled MLOps & AI Platform Engineer with 3–11 years of experience to build, automate, and manage scalable machine learning platforms and production AI environments. The ideal candidate will have hands-on expertise in MLOps, Kubernetes, cloud-native AI infrastructure, CI/CD automation, and model lifecycle management. You will be responsible for enabling data scientists and AI engineers to efficiently develop, deploy, monitor, and maintain machine learning models at scale.
Key Responsibilities
- Design, build, and maintain enterprise-grade MLOps platforms and AI infrastructure.
- Develop and automate end-to-end machine learning pipelines for training, validation, deployment, and monitoring.
- Implement model versioning, experiment tracking, and model registry solutions.
- Build scalable CI/CD pipelines for AI/ML workloads.




- Deploy and manage machine learning workloads on Kubernetes-based environments.
- Collaborate with Data Scientists, AI Engineers, Data Engineers, and DevOps teams to operationalize ML solutions.
- Implement Infrastructure as Code (IaC) for cloud-native AI platforms.
- Monitor platform health, model performance, and infrastructure availability.
- Ensure platform security, scalability, reliability, and operational excellence.
- Troubleshoot production issues and continuously optimize platform performance.

Required Technical Skills
MLOps Platforms
- Hands-on experience with Kubeflow or Vertex AI Pipelines or SageMaker Pipelines.
- Strong experience with MLflow for experiment tracking, model registry, and lifecycle management.
- Experience orchestrating machine learning workflows using Apache Airflow.

Containerization & Orchestration
- Robust expertise in Kubernetes (GKE or AKS or EKS).
- Experience deploying and managing containerized AI/ML workloads in cloud

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