Senior Machine Learning Engineer #AIDA

Date: 7 Jul 2026

Location: Singapore, Singapore

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Company: Singtel Group

An empowering career at Singtel begins with a Hello. Our purpose, to Empower Every Generation, connects people to the possibilities they need to excel. Every "hello" at Singtel opens doors to new initiatives, growth, and BIG possibilities that takes your career to new heights. So, when you say hello to us, you are really empowered to say…“Hello BIG Possibilities”.

Powering the Future with AIDA

To lead the next phase of our AI evolution, we’ve launched a new business unit AIDA – Artificial Intelligence & Data Analytics – a strategic engine driving our transformation designed to scale our AI ambitions with precision and purpose. This marks a pivotal shift in how we operate, innovate, and serve to embed intelligence into every layer of our business.

At Singtel, this is more than a technology upgrade. It’s a strategic transformation that redefines how value is created across the enterprise core—augmenting human capabilities and unlocking entirely new potential. It is a transformation journey by aligning people, platforms, and processes under one cohesive strategy. Our mission is to build AI literacy, and foster a culture where intelligence empowers people.

We welcome you to join us on a transformational journey that’s reshaping the telecommunications industry — and redefining what’s possible with AI at its core. Grow with us in a workplace that champions innovation, embraces agility, and puts human potential at the heart of everything we do.

Be a Part of Something BIG!

Position Summary

Responsible for managing MLOps workflows, tools, and production support processes for ML solutions.

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.

Support data quality, lineage tracking, and governance practices across the ML lifecycle.

Strong MLOps and production operations focus

Make an Impact by:

Responsible for designing, implementing, and managing MLOps workflows, tools, and operational processes for ML and GenAI solutions.

Oversee the day-to-day stability, reliability, and operational health of ML models and ML pipelines.

Manage model lifecycle operations, including model registration, versioning, deployment tracking, lineage, reproducibility, and governance.

Implement monitoring for data drift, concept drift, model performance degradation, inference quality, and service-level issues.

Set up dashboards and alerts to track model health, data quality, inference behaviour, and operational metrics.

Develop and execute incident handling, recovery, rollback, and escalation plans for ML-related issues.

Plan and implement data quality, dataset versioning, and lineage tracking solutions across the ML lifecycle.

Support data governance discussions, documentation, controls, and policies relating to ML models, datasets, and production usage.

Skills for Success:

Bachelor’s or Master’s degree in Computer Science or a related field

Experience with MLOps processes and tools

Experience with SQL, Databricks, MLFlow and PowerBI/Tableau.

Hands-on experience with MLOps tools and cloud ML platforms such as MLflow, Databricks, Azure ML, or equivalent.

Strong SQL and data analysis skills for validation, troubleshooting, monitoring, and reporting.

Experience with model lifecycle management, including model registry, versioning, lineage, reproducibility, deployment tracking, and monitoring.

Familiarity with dashboards and alerting tools such as Power BI, Tableau, Databricks SQL dashboards, or equivalent.

Working knowledge of Git, CI/CD, scripting, and production support practices would be advantageous.

Analytical and pragmatic, with the ability to interpret governance principles into implementation plans

Clear communicator who can explain complex technical risks and solutions to non-technical stakeholders

Self-driven and proactive, comfortable working in a fast-paced environment

Familiarity with ML and data development process in telco environment

Are you ready to say hello to BIG Possibilities?