Artificial Intelligence (AI) & Machine Learning Engineer

Jaheziya; Abu Dhabi; On-site; AED 300,000 - 520,000; Full time

Job summary

Jaheziya is seeking a skilled AI systems engineer to design, deploy, and scale AI/ML platforms in Abu Dhabi. You will build robust MLOps pipelines, containerized deployments, and CI/CD for AI applications.

You will collaborate with data scientists and engineers to operationalize AI solutions, monitor performance, and ensure reliability and security across production environments in the cloud-based stack.

Qualifications

• Bachelor's degree in CS/AI/DS/SE or related field.
• 3–8 years of experience in AI systems engineering, MLOps, or ML platform engineering.
• Strong programming skills in Python.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Hands-on experience with Docker and Kubernetes.
• Experience designing and maintaining CI/CD pipelines.
• Knowledge of distributed systems and scalable AI infrastructure.
• Experience deploying and operationalizing ML and generative AI solutions.

Responsibilities

• Design, deploy, and maintain scalable AI/ML systems and infrastructure.
• Develop and manage MLOps pipelines for automated model deployment and monitoring.
• Ensure performance, reliability, security, and scalability of AI platforms.
• Deploy, serve, and optimize ML and generative AI models for production.
• Build and maintain CI/CD pipelines for AI applications.
• Manage containerized AI applications using Docker and Kubernetes.
• Collaborate with data scientists, software engineers, and stakeholders to operationalize AI solutions.
• Monitor AI system performance, reliability, and availability; implement improvements.
• Troubleshoot production issues and optimize AI infrastructure.

Skills

Python programming

ML/Ops

Distributed systems

AI infrastructure

CI/CD pipelines

Production ML deployment

Collaboration

Education

Bachelor's degree in CS/AI/DS/SE

Tools

Docker

Kubernetes

Terraform

Job description

About the Role

Design, deploy, and maintain scalable AI and machine learning systems that deliver secure, reliable, and high-performing AI solutions. Ensure efficient model serving, deployment, monitoring, and operational excellence across AI environments.

Key Responsibilities

• Design, deploy, and maintain scalable AI/ML systems and infrastructure.


• Develop and manage MLOps pipelines for automated model deployment and monitoring.


• Ensure the performance, reliability, security, and scalability of AI platforms.


• Deploy, serve, and optimize machine learning and generative AI models for production environments.


• Build and maintain CI/CD pipelines for AI applications.


• Manage containerized AI applications using Docker and Kubernetes.


• Collaborate with data scientists, software engineers, and business stakeholders to operationalize AI solutions.


• Monitor AI system performance, reliability, and availability, implementing continuous improvements.


• Troubleshoot production issues and optimize AI infrastructure.

Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.


• 3–8 years of experience in AI systems engineering, MLOps, or machine learning platform engineering.


• Strong programming skills in Python.


• Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.


• Hands‑on experience with Docker, Kubernetes, and containerized deployments.


• Experience designing and maintaining CI/CD pipelines.


• Knowledge of distributed systems and scalable AI infrastructure.


• Experience deploying and operationalizing machine learning and generative AI solutions.

Preferred Qualifications

• Experience with Azure Machine Learning, AWS SageMaker, or Google Vertex AI.


• Experience with Infrastructure as Code (Terraform or similar).


• Familiarity with AI monitoring, observability, and model lifecycle management.


• Relevant cloud or AI certifications.