Summary
✨ AI‑Generated
An experienced MLOps engineer is needed to design and operate an enterprise machine learning platform. Responsibilities span automated ML pipelines, continuous delivery and training, low-latency and batch model serving, production observability, model registries, and monitoring for performance, latency, drift, and reliability.
Highlights
Opportunity to build an enterprise-grade ML platform within an AI-focused financial services environment, with ownership across automation, model deployment, observability, and scalable inference infrastructure.
Description
MLOps Engineer - Abu Dhabi, UAE
Discover the Opportunity
We’re partnering with a leading financial services organisation in Abu Dhabi that is investing significantly in its AI and data capabilities.
Discover the role
We are seeking an experienced MLOps Engineer to join its AI innovation group.
In this role, you will design and develop an enterprise-grade ML platform that empowers data science teams to accelerate model experimentation, streamline deployment, and scale AI solutions across the organization.
Design and automate end-to-end ML pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT).Configure model serving infrastructure supporting both ultra-low latency real-time APIs (e.g., FastAPI, gRPC) and large-scale batch inference.Implement production monitoring and logging systems to track model performance, runtime latencies, data drift, and concept decay.Manage model registries and metadata using tools like MLflow or Kubeflow to ensure auditable lineage, reproducible versioning, and artifact tracking.Orchestrate and scale containerized applications using Docker and production-grade Kubernetes or managed cloud services (EKS, AKS).Partner with security and data governance teams to enforce pipeline encryption, network isolation, secure IAM policies, and strict compliance standards.
Discover the Requirements
3–7 years of hands-on experience building and operating high-availability ML pipelines, automation scripts, and foundational platform infrastructure.Strong programming proficiency in Python, Go, or Java, combined with systems scripting and deep Linux environment expertise.Deep familiarity with tools such as MLflow, Kubeflow, Argo Workflows, Feast, or managed platform equivalents (SageMaker, Azure ML).Hands-on experience with Docker, Kubernetes, Infrastructure-as-Code (Terraform, CloudFormation), and cloud security (VPC isolation, private endpoints, RBAC, encryption).Bachelor’s degree in Computer Science, Engineering, or a related field required; Master’s degree preferred.
Why Join?
An excellent salary package on offerEnjoy a 4.5-day work week, plus 24 annual flexi-work days allowing you to work from anywhere.Full platinum health cover for you and your sponsored dependents.You will be a part of one of the region's biggest AI innovation teams and gain the opportunity to work with cutting-edge technologies to transform large-scale enterprise banking systems.
