Machine Learning Engineer - Emirati Talent (NAFIS)

Position MLOPs Engineer I Section Data & AI Division e& enterprise.ResponsibilitiesBuild and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring.Automate model workflows using CI/CD and Continuous Training (CT) principles.Develop and manage reusable pipeline templates for LLM fine-tuning, RAG deployments, and multi-agent orchestration.Optimize cloud resource usage for efficient large-model training and inferenceLead ML model lifecycle automation including CI/CD pipelines, monitoring, and production deploymentsEstablish MLOps best practices for model versioning, automated testing, and continuous deploymentManage inference endpoints for real-time and batch predictions across environments (Dev, Staging, Prod).Implement model monitoring for drift detection, performance degradation, and latency trackingManage feature stores, data versioning, and lineage tracking for reproducibility.Collaborate with AI engineers and data scientists to optimize model training and deployment workflowsDrive adoption of DevOps practices in ML teams including infrastructure as code and automated deploymentsDesign security and compliance frameworks for ML infrastructure and model governanceManage cost optimization and resource allocation for ML training and inference workloadsWork closely with AI Architects, ML Engineers, and DevOps to improve pipeline reliability.Qualifications & ExperienceEmirati with Family bookMale candidates must have completed the National service.Bachelor's or Engineering degree in Computer Science, Data Science, or related technical field.2+ years of experience in DevOps, platform engineering, or ML infrastructureKnowledge of Kubernetes, Docker, and cloud platforms (AWS, GCP, Azure)Strong experience with Infrastructure as Code tools (Terraform, CloudFormation) and CI/CD pipelines; MLOps tools knowledge like Airflow, Kubeflow, MLflow etc.#J-18808-Ljbffr