ML Ops & Analytics Engineer: Production Data Pipelines

XL Smart career; Jakarta Selatan; On-site; IDR 420,000,000 - 660,000,000; Full time

Job summary

XL Smart career is seeking an experienced data engineer focused on analytics engineering and MLOps to design and run production-grade ML pipelines. You will operationalize models by integrating them into data platforms and business workflows, monitor performance, and collaborate with data scientists and engineers to standardize deployment and experimentation.

The role requires 3–6 years in data or analytics engineering, a Bachelor’s degree in a relevant field, and preferably a Master’s; cloud

Qualifications

• Bachelor’s Degree in Computer Science, Data Engineering, Information Systems, or related fields.
• Master’s Degree in Data Engineering or AI is an advantage.
• 3–6 years of experience in data engineering, analytics engineering, or MLOps roles.
• Experience with cloud-based analytics platforms and ML deployment in production environments
• Experience in Telco industry is a plus.

Responsibilities

• Develop and manage analytics and ML pipelines covering data preparation, model deployment, and orchestration in production environments.
• Operationalize machine learning models by integrating models into data platforms, applications, and business workflows.
• Monitor model performance, data drift, and pipeline reliability to ensure stability, accuracy, and continuous improvement.
• Collaborate with data scientists and data engineers to standardize deployment, versioning, and experimentation practices.
• Strengthen MLOps and analytics engineering standards including automation, documentation, and operational controls.

Skills

Data engineering

Analytics engineering

MLOps

Model deployment

Collaboration

Automation

Education

Bachelor’s Degree in Computer Science, Data Engineering, Information Systems, or related fields

Master’s Degree in Data Engineering or AI

Tools

Cloud platforms

ML deployment in production

Job description

XL Smart career is seeking an experienced data engineer focused on analytics engineering and MLOps to design and run production-grade ML pipelines. You will operationalize models by integrating them into data platforms and business workflows, monitor performance, and collaborate with data scientists and engineers to standardize deployment and experimentation.

The role requires 3–6 years in data or analytics engineering, a Bachelor’s degree in a relevant field, and preferably a Master’s; cloud