Research Assistant, AI Research and Engineering

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/Research-Assistant%2C-AI-Research-and-Engineering/34932-en_GB/

We regret that only shortlisted candidates will be notified.

Overview

Join the Asian Institute of Digital Finance (AIDF) at NUS to develop AI research and applications in finance. We are looking for a Research Assistant to support projects involving machine learning, large language models (LLMs), AI agents and financial data analysis. You will work with researchers to translate ideas into experiments and working systems, while coordinating and mentoring research and engineering interns. This is a hands-on technical role combining research, engineering and project coordination.

Responsibilities

• Research and development: Review literature, design experiments and implement machine learning or LLM-based methods with researchers.
• AI engineering: Develop and maintain AI applications involving LLM agents, retrieval-augmented generation (RAG), APIs, databases and evaluation pipelines.
• Intern supervision: Assign and clarify tasks, review code and experimental results, troubleshoot problems and provide regular feedback.
• Project coordination: Translate project objectives into milestones, track progress and help ensure timely, high-quality deliverables.
• Evaluation and quality: Build reproducible experiments, tests and metrics to assess model performance, system reliability and research findings.
• Documentation and communication: Maintain code and experimental records; contribute to research papers, reports, presentations and technical discussions

Requirements

Required

• Bachelor's or Master's degree in Computer Science, AI, Data Science, Financial Engineering or a related discipline
• Strong Python programming skills and hands-on experience with machine learning or LLM-based applications.
• Familiarity with AI development frameworks and tools, such as PyTorch, Hugging Face or LLM APIs.
• Ability to independently implement, debug, evaluate and maintain research code or AI applications.
• Good software engineering practices, including Git, testing, documentation and code review.
• Strong organisation, communication and critical-thinking skills; ability to guide junior team members and verify AI-generated work

Preferred

• Experience in academic research, research engineering or AI application development.
• Experience with LLM agents, RAG, model evaluation, full-stack development or financial data.
• Experience mentoring students or coordinating technical projects; publications or demonstrable AI projects.
• Prior financial domain expertise is not required.

How to Apply

Please submit your CV, relevant project or GitHub links, and a brief description of your research or engineering experience. Shortlisted applicants may be invited to discuss a previous project and their technical contributions.

Enquiries: Dr Kelvin Koa | [email protected]