Machine Learning Engineer - Emirati Talent (NAFIS)

Position MLOPs Engineer I Section Data & AI Division e& enterprise.

Responsibilities • Build 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 inference • Lead ML model lifecycle automation including CI/CD pipelines, monitoring, and production deployments • Establish MLOps best practices for model versioning, automated testing, and continuous deployment • Manage inference endpoints for real-time and batch predictions across environments (Dev, Staging, Prod). • Implement model monitoring for drift detection, performance degradation, and latency tracking • Manage feature stores, data versioning, and lineage tracking for reproducibility. • Collaborate with AI engineers and data scientists to optimize model training and deployment workflows • Drive adoption of DevOps practices in ML teams including infrastructure as code and automated deployments • Design security and compliance frameworks for ML infrastructure and model governance • Manage cost optimization and resource allocation for ML training and inference workloads • Work closely with AI Architects, ML Engineers, and DevOps to improve pipeline reliability.

Qualifications & Experience • Emirati with Family book • Male 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 infrastructure • Knowledge 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.