AI Engineer (AI Products)

About the role

This position is hosted at Nanyang Technological University (NTU) under the office of the Vice President (Artificial Intelligence & Digital Economy) and is part of AI Singapore, a national initiative supporting research, talent and Singapore's AI efforts. It focuses on developing and deploying multilingual, multicultural and multimodal large language models.

Key responsibilities

• Develop, train, fine-tune and evaluate multilingual, multicultural and multimodal foundation LLMs, including continued pre-training, supervised fine-tuning, instruction tuning, preference optimisation and model adaptation.
• Build and maintain scalable data pipelines for multilingual text ingestion, cleaning, filtering, deduplication, tokenisation, contamination detection and dataset mixture creation.
• Support large-scale distributed model training workflows, including experiment tracking, checkpointing, monitoring, debugging, profiling and compute optimisation.
• Review frontier AI and LLM research papers, reproduce methods and turn findings into practical improvements in training, evaluation and deployment.
• Contribute reusable engineering assets such as training scripts, evaluation tools, model artefacts, APIs, documentation and deployment-ready components.
• Collaborate with internal teams, research labs, academic institutions and industry partners on LLM research and knowledge sharing.
• Support community building through technical sharing, seminars, workshops, publications or outreach.

Required profile

• Applicants from all disciplines and qualification pathways (NITEC, Diploma, Bachelor's, Master's or PhD, or equivalent practical experience) are welcome.
• A formal qualification in Computer Science, AI, Machine Learning, Data Science, Engineering, Mathematics, Computational Linguistics or a related field is advantageous but not mandatory.
• Self-directed, curious, collaborative and engineering-minded, with a commitment to reproducibility, reliability, documentation and responsible AI.

Required skills

• Python with strong software engineering practices (clean, modular code, Git, testing, documentation, code review).
• Hands-on experience with PyTorch and modern NLP/LLM frameworks, especially the Hugging Face ecosystem (Transformers, Datasets, Tokenizers, Accelerate, TRL).
• Knowledge of LLM pre-training, fine-tuning, instruction tuning, evaluation and model adaptation, and multilingual NLP challenges.
• Ability to build scalable text processing and training pipelines, with familiarity with distributed training, GPU training and checkpointing.
• Familiarity with Linux, Docker, CI/CD and cloud or GPU/HPC clusters; experience with vLLM, SGLang, TGI or similar serving frameworks is advantageous.
• Ability to read research papers, design experiments and run ablation studies, and communicate technical trade-offs clearly.