Job Description

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)