AI Engineer for AI Singapore (AI Talent Development)

Requirements

• Degree in computer science, engineering, data science, or equivalent practical experience.
• Minimum 1 year in software engineering / ML engineering / applied AI and deploying models into production.

Additional Information

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal. NUS Career Portal link: https://careers.nus.edu.sg/job/AI-Engineer-for-AI-Singapore-%28AI-Talent-Development%29/33283-en_GB/ We regret that only shortlisted candidates will be notified. Job Description AI Singapore (AISG) is a national AI programme launched by the National Research Foundation (NRF), Singapore, to build and anchor deep national capabilities in AI. AISG is supported through a government-wide partnership including the NRF, Ministry of Digital Development and Information (MDDI), Infocomm Media Development Authority (IMDA), Economic Development Board (EDB) and Enterprise Singapore (ESG). We bring together research institutions and the vibrant ecosystem of AI start-ups and companies to support impactful research, develop talent, and power Singapore's AI efforts. AI Singapore (AISG) in partnership with the SAF AI Centre (SAIC), is seeking an experienced AI engineer to provide mentorship and consultancy to SAIC engineering teams, support real-world project selection for skills deepening, and enable professional certification readiness. SAIC is a unit within the Digital and Intelligence Service, dedicated to addressing SAF's operational data science challenges and operationalising AI solutions. As the centre of excellence for AI, SAIC enhances the operational capabilities of SAF, driving productivity and efficiency through innovative AI solutions that advance SAF's defence capabilities. Duties & Responsibilities In this role, you will: - Develop and deliver AI courses and programmes that raise AI fluency level for SAF workforce, including but not limited to playbooks for operational users and raising awareness of common AI use cases within SAF. - Provide technical mentorship via sprints or personal mentorship; capture feedback on knowledge sharing and technical problem-solving impact. - Identify real-world AI projects that build software engineering depth and machine learning pipeline skills of workforce for certification readiness. - Assist Senior AI Engineer to develop and maintain a job-skills-proficiency (JSP) map. - Assist Senior AI Engineer to execute AI engineer certification programme.

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