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Ngee Ann Polytechnic is seeking an AI Engineer on a 2-year contract to build production-ready AI applications and systems that leverage GenAI, deep learning, and cloud AI services. You will collaborate with data scientists and cross-functional teams to transition AI models from research to production and embed AI into NP's administrative and academic workflows.
The role focuses on scalable AI solutions, MLOps, API/microservice deployment, and ensuring compliance with NP's standards for security,
This is a 2-year contract position with the Digital Services & Technology Office. The AI Engineer will be instrumental in implementing NP's AI transformation strategy by developing production-ready AI applications and systems that leverage AI tools and Cloud AI services. This role focuses on building robust, scalable AI solutions using GenAI models, deep learning, neural networks, and other AI technologies to improve NP operations through intelligent automation and advanced analytics. Working in close collaboration with the AI Product Manager, data scientists, and cross-functional teams, the AI Engineer will transition AI models from research to production and embed AI capabilities into NP's administrative and academic support workflows.
AI Solution Development
Design, develop, and implement AI/ML models, algorithms, and GenAI-powered applications (including conversational AI, content generation, and intelligent document processing systems) using diverse approaches and platforms such as Microsoft Copilot Studio, Databricks Apps, Azure AI Studio, and custom development frameworks.
Deploy and integrate AI solutions with existing enterprise systems, ensuring compatibility with data infrastructure and institutional workflows.
Model Development & Operations
Design, build, and train machine learning, deep learning, and neural network models tailored to address specific institutional needs across administrative and operational domains.
Collect, analyse, and clean data from various sources to train and test AI models, working closely with data engineering teams to ensure data quality and accessibility.
Test, validate, and optimise algorithms to ensure reliability, scalability, and performance across various use cases and production environments.
Technical Implementation
Configure and utilise AI development environments and tools within the AI platform infrastructure provided by the infrastructure team.
Implement MLOps practices including automated model training, testing, deployment pipelines, version control, and continuous integration for AI solutions.
Deploy AI models and applications using cloud AI services (Azure, AWS) and platform infrastructure, ensuring optimal performance and resource utilisation.
Develop APIs and microservices to serve AI models, enabling robust integration with institutional workflows and applications.
Quality Assurance & Support
Ensure AI solutions meet NP's technical standards for scalability, reliability, security, and maintainability while complying with data privacy regulations and ethical AI guidelines.
Provide technical support, troubleshooting, and performance optimisation for deployed AI applications and models.
Collaborate with Infrastructure team to define requirements for AI platform capabilities and provide feedback on platform performance and functionality.
Work closely with data scientists, product teams, and business stakeholders to align AI solutions with institutional goals and embed AI capabilities into workflows.
Degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related technical discipline.
Minimum 3 years of hands-on experience in AI/ML development with demonstrated expertise in building and managing both AI infrastructure and applications in production environments.
Skills & Certifications
Proficiency in programming languages such as Python, R, or Java, with experience in AI/ML frameworks like TensorFlow, PyTorch, scikit-learn, and related ecosystem tools.
Experience with cloud platforms (Azure, AWS) including AI services, infrastructure-as-code, containerisation technologies (Docker, Kubernetes), and platform engineering practices.
Expertise in MLOps tools and practices, including model lifecycle management, automated deployment pipelines, monitoring, and governance frameworks.
Knowledge of data engineering concepts, API development, microservices architecture, and enterprise integration patterns.
Experience with enterprise platforms such as Databricks, Microsoft Co-Pilot Studio, Power Platform, and familiarity with Singapore IT governance and security frameworks.
Attributes
Detail-focused and methodical.
Problem-solver with a performance-driven mindset.
Adaptable and collaborative within cross-functional teams.
Strong communicator able to work across AI, governance, and business stakeholders.
At Ngee Ann Polytechnic, our nine academic schools offer over 40 full-time diplomas to a growing student population of more than 15,000. As a public tertiary institution, internationally-recognised for its academic excellence and close industry links, NP prides itself on having a dedicated and professional teaching faculty, complete with campus facilities that are among the finest in the world. An institution of higher learning, Ngee Ann Polytechnic believes in giving every student an enriching learning experience and every employee the opportunity to build a meaningful career. If you are a self-starter with an innovative mind, a versatile person with the drive for all-rounded excellence, and a dedicated team player who shares our vision and values, we invite you to join our inspired team.