MLOps Engineer

Job description / Role

Job description

Kinetic has partnered with a leading technology company who are hiring an MLOps engineer to be based in Abu Dhabi.

Please note that you must meet all the criteria set out below for your application to be considered. Suitable candidates will be contacted within 5 working days. If you are not contacted by us within that time, please consider your application unsuccessful on this occasion.

Main responsibilities

• Build, deploy, monitor, and manage large-scale AI infrastructure based on HGX H200 nodes.
• Operate and manage Kubernetes or OpenShift clusters for multi-node orchestration.
• Deploy and manage LLMs and other AI models for inference using Triton Inference Server or custom endpoints.
• Automate CI/CD pipelines for model packaging, serving, retraining, and rollback using GitLab CI or ArgoCD.
• Set up model and infrastructure monitoring systems (Prometheus, Grafana, NVIDIA DCGM).
• Implement model drift detection, performance alerting, and inference logging.
• Manage model checkpoints, reproducibility controls, and rollback strategies.
• Track deployed model versions using MLFlow or equivalent registry tools.
• Implement secure access controls for model endpoints and data artifacts.
• Collaborate with the AI/Data engineer to integrate and deploy fine-tuned datasets.
• Ensure high availability, performance, and observability of all AI services in production.

Requirements

• 10+ years overall experience with solution operations.
• Minimum 3+ years of experience in DevOps, MLOps, or AI/ML infrastructure roles.
• Proven experience with Kubernetes or OpenShift in production environments, preferably certified.
• Experience with CI/CD automation tools with OpenShift/Kubernetes.
• Hands-on experience with model registry systems (e.g., MLFlow, KubeFlow).
• Experience with monitoring tools (e.g., Prometheus, Grafana) and GPU workload optimization.
• Strong scripting skills (Python, Bash) and Linux system administration knowledge.
• Familiarity with deploying and scaling PyTorch or TensorFlow models for inference.
• Applicants should be available for face-to-face interviews in the location mentioned above.

Must read: The 7 uncomfortable reasons you were rejected from the role you just applied for.

About the Company

Flow Talent have been sourcing the best Banking, Technology, Financial Services & Legal professionals locally and internationally for leading organisations across the Middle East region since 2018.

Through years of experience, we know there is significant demand for highly skilled professionals and pride ourselves on having the highest calibre candidates. As a team, we strive to help our clients achieve operational and business excellence by identifying quality talent, quickly, through our collaborative approach.

Flow place professionals in the following sectors: - Banking & Financial Services - Digitalisation & Technology - Legal & Compliance

We help our clients with: - Contingent Recruitment: - Retained Recruitment - Emiratization and Saudization - Market Entry