MLOps Engineer

SCC Services Romania; Abu Dhabi; Hybrid; AED 134,000 - 201,000; Full time

Benefits offered by this job

Hybrid work in UAE

Job summary

SCC Services Romania is seeking an experienced MLOps Engineer for a hybrid UAE-based freelance role. The position involves building and maintaining scalable ML infrastructure, CI/CD pipelines, and production-grade deployment and monitoring of ML models.

Initial 6-month contract with potential extension based on project needs. Ideal candidates have 4+ years in MLOps/DevOps, strong Python, and hands-on cloud experience (AWS/Azure/GCP) with Terraform or CloudFormation for IaC.

Qualifications

• Bachelor's or Master's in CS/Engineering/Data Science or related field.
• 4+ years of MLOps/DevOps/ML engineering experience.
• Strong Python and ML lifecycle management experience.
• Hands-on with MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML.
• CI/CD tools such as GitHub Actions, GitLab CI/CD, Jenkins, or Azure DevOps.
• Containerization with Docker and Kubernetes.
• Experience with AWS/Azure/GCP.
• IaC with Terraform or CloudFormation.
• Monitoring and observability skills.
• Strong software engineering practices and reliability.

Responsibilities

• Design, implement, and maintain scalable MLOps frameworks and automated ML workflows.
• Build and manage CI/CD pipelines for ML model development, testing, deployment, and monitoring.
• Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams to operationalize AI solutions.
• Deploy, monitor, and manage ML 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 ML infrastructure.
• Implement logging, monitoring, and alerting for model and platform performance.
• Optimize cloud infrastructure and resource utilization for AI/ML workloads.
• Troubleshoot issues related to model deployment, infrastructure, and data pipelines.
• Promote MLOps best practices and continuous improvement initiatives.

Skills

Python

ML lifecycle management

CI/CD tooling

Infrastructure as Code

Logging & monitoring

Communication

Problem solving

Education

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field

Tools

MLflow

Kubeflow

Airflow

SageMaker

Vertex AI

Azure ML

Docker

Kubernetes

Terraform

CloudFormation

Job description

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.

Skills

Required Skills & Experience

• 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.

Please note: This opportunity is open to freelancers/independent contractors only and requires availability for a hybrid working arrangement in UAE.