Requirements
Requires a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field, along with 4+ years of experience in MLOps, DevOps, or Machine Learning Engineering. Must have strong Python skills, experience with ML lifecycle management, MLOps platforms (MLflow, Kubeflow, etc.), CI/CD tools, Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP). Familiarity with infrastructure as code and monitoring tools is also essential, along with strong analytical, troubleshooting, and communication skills.
Description
Job description / Role
Job Type
Contract
Job Location
UAE
Nationality
Any Nationality
Salary
Not Specified
Gender
Not Specified
Arabic Fluency
Not Specified
Job Function
IT - Software & Web Development
Company Industry
IT, Hardware & Networking
MLOps Engineer (Freelance)
Location: Abu Dhabi, Dubai, Fujairah, UAE (Hybrid)
Contract Duration: Initial 6-Month Contract with possibility of extension
Employment Type: Freelance / Independent Contractor
About the Role
We are seeking an experienced MLOps Engineer to join our team on an initial 6-month freelance contract. This is a hybrid role offering a combination of onsite and remote work.
The successful candidate will play a key role in building, automating, and maintaining the infrastructure and processes required to deploy, monitor, and scale machine learning solutions in production environments. This opportunity offers the potential for extension beyond the initial contract period, subject to project requirements and performance.
Key Responsibilities
• Design, implement, and maintain scalable MLOps frameworks and automated machine learning workflows.
• Build and manage CI/CD pipelines for machine learning model development, testing, deployment, and monitoring.
• Collaborate closely with Data Scientists, Machine Learning Engineers, Data Engineers, and DevOps teams to operationalize AI solutions.
• Deploy, monitor, and manage machine learning models in production environments.
• Develop and maintain model versioning, governance, and monitoring processes.
• Automate model retraining, validation, and deployment workflows.
• Ensure reliability, scalability, security, and performance of machine learning infrastructure.
• Implement logging, monitoring, and alerting mechanisms for model and platform performance.
• Optimize cloud infrastructure and resource utilization for AI/ML workloads.
• Troubleshoot and resolve issues related to model deployment, infrastructure, and data pipelines.
• Promote MLOps best practices and contribute to continuous improvement initiatives.
Requirements:
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• 4+ years of experience in MLOps, DevOps, Machine Learning Engineering, or a similar role.
• Strong experience with Python and machine learning lifecycle management.
• Hands-on experience with MLOps platforms and tools such as MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML.
• Strong knowledge of CI/CD tools such as GitHub Actions, GitLab CI/CD, Jenkins, or Azure DevOps.
• Experience with containerization and orchestration technologies including Docker and Kubernetes.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Understanding of infrastructure as code tools such as Terraform or CloudFormation.
• Experience with monitoring and observability tools.
• Strong knowledge of software engineering best practices, automation, and system reliability.
• Excellent analytical, troubleshooting, and communication skills.
Preferred Qualifications
• Experience supporting Generative AI and Large Language Model (LLM) deployments.
• Familiarity with Databricks, Spark, and large-scale data processing platforms.
• Knowledge of Responsible AI, model governance, and compliance frameworks.
• Experience working in enterprise-scale production environments.
• Previous experience delivering projects within the UAE or GCC region.
If you are passionate about building reliable and scalable machine learning platforms and enjoy working at the intersection of AI, cloud infrastructure, and automation, we would love to hear from you.
Please note: This opportunity is open to freelancers/independent
About the Company
We are a privately owned, UK-headquartered technology partner with 50 years of continuous operation. We stand behind the organisations whose operations depend on IT, and we own every stage of the lifecycle under one accountable roof.
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