MLOps Engineer

Role Overview

Location and Work Arrangement

• Hybrid role combining onsite and remote work in Abu Dhabi or Dubai, UAE.
• The opportunity is open to freelancers and independent contractors who can support the hybrid UAE arrangement.

Key Responsibilities

• Design scalable MLOps frameworks and automated machine learning workflows.
• Build CI/CD pipelines for machine learning development, testing, deployment, and monitoring.
• Deploy, monitor, and manage production machine learning models.
• Automate model retraining, validation, and deployment workflows.
• Ensure infrastructure reliability, scalability, security, and performance.
• Implement logging, monitoring, and alerting for models and platforms.
• Optimize cloud resources and troubleshoot deployment, infrastructure, and data pipeline issues.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• At least four years of experience in MLOps, DevOps, Machine Learning Engineering, or a similar role.
• Strong Python, machine learning lifecycle, software engineering, automation, and system reliability experience.
• Strong analytical, troubleshooting, and communication skills.

Required Technical Skills

• Hands-on experience with MLOps platforms and tools.
• Strong knowledge of CI/CD tools and experience with Docker and Kubernetes.
• Experience with AWS, Azure, or Google Cloud Platform.
• Understanding of infrastructure as code using Terraform or CloudFormation.
• Experience with monitoring and observability tools.

Preferred Qualifications

• Experience supporting Generative AI and large language model deployments.
• Familiarity with Databricks, Spark, and large-scale data processing platforms.
• Knowledge of Responsible AI, model governance, and compliance frameworks.
• Experience in enterprise-scale production environments or projects delivered in the UAE or GCC region.