AI/ML Operations (MLOps)

Job Purpose

Manages machine learning pipelines, automates deployment, and ensures ongoing monitoring and maintenance of AI models.

Key Responsibilities

· Develop and maintain CI/CD pipelines for ML models.

· Automate model training, testing, deployment, and monitoring.

· Implement tools for drift detection, model performance tracking, and retraining.

· Ensure reliability, scalability, and auditability of ML infrastructure.

· Collaborate with engineers and data scientists to ensure seamless deployment.

Minimum Qualifications

Education: Bachelor of Computer Science, Master's in AI or Data Science is a plus.

Experience: 3–5 years

Key Competency Requirements

Technical Skills:

· Expertise in MLOps tools (MLflow, TFX, Kubeflow).

· Experience with Kubernetes, Docker, and cloud platforms.

Operational Skills:

· Automation of model lifecycle and monitoring workflows.

· Knowledge of version control and DevOps practices.

Soft Skills:

· Attention to detail and proactive monitoring.

· Strong documentation and support capabilities.

Job Type: Full-time

Application Question(s):

• What is your current notice period or earliest joining date?
• What are your salary expectations for this role?
• Current location, nationality, and current job title/role?
• Are you willing to work remotely ?
• Have you worked with CI/CD pipelines specifically for machine learning model deployment?
• Are you experienced with Kubernetes, Docker, and cloud platforms (AWS / Azure / GCP)?
• Total years of experience in MLOps / ML Engineering?

Education:

• Bachelor's (Preferred)

Experience:

• MLOps tools such as MLflow, Kubeflow, TFX, or Airflow: 5 years (Preferred)

Language:

• Arabic and English (Preferred)

Location:

• Dubai (Preferred)