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Jaheziya

Artificial Intelligence (AI) & Machine Learning Engineer

Jaheziya Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates

Emergency and Relief Services · 51-200 employees

Jun 26
machine-learning Senior (5-10 yrs) Full-time United Arab Emirates
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About the role

Design, deploy, and maintain scalable AI and machine learning infrastructure while managing MLOps pipelines for automated model deployment. Collaborate with cross-functional teams to operationalize AI solutions and ensure the performance, security, and reliability of production environments.

What they look for

Python MLOps Docker Kubernetes CI/CD Microsoft Azure AWS Google Cloud Platform Generative AI Machine Learning Infrastructure as Code Terraform Azure Machine Learning AWS SageMaker Google Vertex AI Distributed Systems

Requirements

Requires a bachelor's degree in a relevant technical field and 3–8 years of experience in AI systems engineering or MLOps. Candidates must possess strong Python programming skills and hands-on experience with cloud platforms, containerization, and CI/CD pipelines.

Full 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.

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