Director, ML Ops & AI Production

Singapore Telecommunications Limited; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Singtel’s AI unit AIDA seeks an ML/MLOps leader to own the production lifecycle of AI/ML models. You will manage deployment through the CI/CD toolchain, monitor drift and cost, and govern versioning and lineage while guiding a small team across HQ and offshore.

You’ll enforce deployment discipline and collaborate with data science, engineering, and business teams to scale AI initiatives with precision and accountability.

Qualifications

• Degree in Computer Science, Data Science, Engineering, or related field.
• 10+ years in ML/MLOps/platform engineering with team leadership.
• Experience deploying and operating ML models in production.
• Experience with model lifecycle management, including model registry, versioning, lineage, reproducibility, deployment tracking, and monitoring.
• Strong SQL and data analysis skills for validation, troubleshooting, monitoring, and reporting.
• Calm, decisive incident leadership and effective crisis communication.

Responsibilities

• Own AI/ML model deployment operations via CI/CD toolchain and enforce deployment-discipline rules.
• Ensure day-to-day stability, reliability, and performance of ML models and pipelines.
• Manage model lifecycle controls, including versioning, lineage, reproducibility, monitoring, and governance.
• Develop incident handling, recovery, and escalation procedures for ML-related issues.
• Chair post-incident reviews and drive corrective actions and systemic findings into the backlog.
• Lead, roster, and develop the team across HQ and offshore; own on-call discipline, fatigue management, and shift handover quality.

Skills

ML/MLOps leadership

Production ML deployment

Model lifecycle management

SQL & data analysis

Stakeholder communication

People leadership

Education

Degree in CS/Data Science/Engineering

Tools

MLflow

Databricks

Azure ML

PowerBI

Tableau

Job description

Singtel’s AI unit AIDA seeks an ML/MLOps leader to own the production lifecycle of AI/ML models. You will manage deployment through the CI/CD toolchain, monitor drift and cost, and govern versioning and lineage while guiding a small team across HQ and offshore.

You’ll enforce deployment discipline and collaborate with data science, engineering, and business teams to scale AI initiatives with precision and accountability.