AI Engineer - Generative AI & Apprenticeship Lead

Nanyang Technological University

Singapore

On-site

SGD 90,000 - 150,000

Full time

7 days ago
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Job summary

NTU Singapore hosts AISG’s AI Apprenticeship Programme and seeks an AI Engineer to drive projects and spearhead cutting-edge AI technologies. You will mentor apprentices, lead AI-driven solutions, and coordinate program delivery across multiple LADP and LADP Enterprise streams.

You will work within NTU’s AI & Digital Economy office, collaborating with researchers and industry partners to push innovations in NLP, computer vision, and generative AI, while applying strong Python and MLOps practices.

Qualifications

  • End-to-end AI project delivery from scoping to deployment.
  • Experience with NLP/Computer Vision or tabular data problems.
  • Hands-on production LLM apps and agentic systems.
  • Strong Python and software engineering practices.
  • Experience with MLOps and cloud platforms (AWS/Azure/GCP).

Responsibilities

  • Drive tasks from AIAP, LADP, and related programs.
  • Mentor AI apprentices during phases of training and projects.
  • Lead solution development for internal and external AI projects; perform research and maintain technologies.
  • Plan LADP intakes and update the LADP syllabus.
  • Oversee LADP Enterprise, Essentials, and portfolio activities.
  • Support industry/community activities through talks and workshops.

Skills

AI project delivery
Applied ML
Generative AI & LLMs
Python
MLOps & Cloud
Communication
Mentorship

Tools

Docker
Git
CI/CD
LLM tooling

Job description

NTU Singapore hosts AISG’s AI Apprenticeship Programme and seeks an AI Engineer to drive projects and spearhead cutting-edge AI technologies. You will mentor apprentices, lead AI-driven solutions, and coordinate program delivery across multiple LADP and LADP Enterprise streams.

You will work within NTU’s AI & Digital Economy office, collaborating with researchers and industry partners to push innovations in NLP, computer vision, and generative AI, while applying strong Python and MLOps practices.

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