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
