AI Engineer
4 months ago
SSG is a dynamic and forward-thinking organization dedicated to empowering individuals and shaping the future of Singapore's workforce. As a statutory board under the Ministry of Education, SSG leads the charge in driving the SkillsFuture movement, a national initiative that promotes lifelong learning and skills development. With a strong focus on innovation and collaboration, SSG works closely with employers, training providers, and individuals to create a vibrant ecosystem of learning and growth. By offering a wide range of initiatives, programs, and funding schemes, SSG enables individuals to unlock their full potential, acquire new competencies, and stay ahead in a rapidly changing job market.
Join the Data Strategy & Analytics Division (DSAD) team to grow SSG into a data-mature organization where we use data pervasively and securely to deliver on our business missions:
•Develop and drive SSG’s data strategy, including LOIs, data competency, and maintaining strong links with CIO Office
•Develop, implement and maintain comprehensive data governance and management framework that complies with WOG requirements Implement Lines of Inquiries
•Support data management and exploitation
•Develop MLOps and instil best practices
[What you will be working on]
As an AI Engineer within DSAD, you will play a pivotal role in developing and enhancing our AI-driven platforms. Your expertise in machine learning, AI, and GenAI applications will contribute significantly to our mission of leveraging advanced technologies to drive innovation and operational excellence. We are looking for a candidate who embodies our core values of integrity, collaboration, and continuous improvement, and who is passionate about harnessing the power of AI to achieve our strategic objectives.
AI and Machine Learning Development
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Develop and enhance machine learning models and AI solutions, focusing on generative and discriminative AI applications
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Test, deploy, and maintain scalable and reliable AI systems
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Implement MLOps principles for efficient integration of machine learning models with data pipelines and infrastructure
Collaboration and Integration
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Work closely with data scientists and engineers to integrate AI into broader system architectures
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Facilitate knowledge sharing and technical training sessions to boost organizational AI competency
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Integrate AI models and systems with APIs and external systems for seamless data and functionality flow
Innovation and Continuous Improvement
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Stay abreast of AI trends to suggest improvements to existing systems and workflows
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Participate in the entire AI model lifecycle management, from data analysis and model building to integration and deployment
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Advocate for continuous improvement in AI practices and applications, aligning with our mission of leveraging advanced technologies
[What we are looking for]
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Tertiary qualifications in computer science, statistics, applied mathematics, data management, information systems, information science, or a related quantitative field
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A minimum of three years of experience in AI and machine learning disciplines, including model development, deployment, and lifecycle management
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At least two years of experience in cross-functional team collaboration and supporting AI/GenAI initiatives.
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Proficiency in Python; familiarity with R is a plus
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Strong knowledge of AI frameworks such as TensorFlow, PyTorch, and scikit-learn
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Familiarity with AWS SageMaker, feature stores, model registry, and AWS cloud architecture
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Proficiency in SQL and containerization technologies like Docker and Kubernetes
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Excellent problem-solving skills, strong interpersonal skills, and the ability to work in a team environment
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Confident, energetic self-starter with a commitment to ethics, regulatory compliance, customer service, and business integrity
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Highly adaptable and committed to excellence in a dynamic business environment
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Demonstrated ability to work creatively and collaboratively with both business and IT teams
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Passionate about staying updated on AI advancements and advocating for continuous improvement in AI practices and applications
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