Job description:

Role Overview

We are looking for a skilled Data Scientist (AI Engineering) to join our Digital, AI and Transformation Department. In this role, you will focus on the technical groundwork and infrastructure that powers our AI capabilities — enabling domain specialists to dedicate their efforts to high-impact, business-critical AI solutions. You will be at the core of building and sustaining the engineering backbone that drives our AI initiatives forward.

Key Responsibilities

Infrastructure & Environment Management

Oversee and manage complex cloud environments within Government Commercial Cloud (GCC) infrastructure to support AI workloads

Establish and maintain secure, stable connectivity between internal government systems and AI platforms and tools

Conduct routine system maintenance and performance monitoring to ensure AI models operate at peak efficiency

Design and enforce security protocols governing AI data handling and model deployment

Rapid Prototyping & Technical Validation

Lead technical due diligence assessments for emerging AI technologies, frameworks, and vendor offerings

Develop proof-of-concepts to validate the feasibility and performance of AI models prior to full-scale deployment

Carry out stress-testing of AI vendor APIs, model endpoints, and third-party AI integrations

Produce clear technical documentation and actionable recommendations to guide AI technology adoption decisions

Pipeline Development & AI Infrastructure

Build and maintain automated data pipelines tailored for AI model training and inference workflows

Write reliable, high-quality code to ensure seamless data flow from source systems to AI models

Apply MLOps best practices across model deployment, monitoring, and lifecycle management

Develop and sustain AI model serving infrastructure and API endpoints

Requirements

Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related technical discipline

Minimum 3 years of hands-on experience in AI/ML engineering or equivalent technical roles

Proficient in Python, with working knowledge of AI/ML libraries such as TensorFlow, PyTorch, and scikit-learn

Demonstrated experience managing cloud infrastructure for AI workloads (AWS, Azure, or GCP)

Solid understanding of MLOps practices including model deployment and monitoring

Experience in API development and integration, particularly within AI service ecosystems

Familiarity with data pipeline tools and ETL processes designed for AI applications

Good to Have

Exposure to Singapore Government technology standards and AI governance frameworks

Prior experience working within Government Commercial Cloud (GCC) environments and its AI service offerings

Knowledge of responsible AI principles, including bias detection in government contexts

Understanding of public sector data governance and privacy requirements as they relate to AI

Track record of delivering AI solutions in government or public sector settings

Experience in domain-specific AI applications such as natural language processing or computer vision

Familiarity with AI model interpretability and explainability methodologies

Knowledge of containerisation technologies (Docker, Kubernetes) for AI model deployment