Research Engineer I (Computer Science/AI/Machine Learning)

Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world's top universities. NTU's College of Computing and Data Science (CCDS) is a leading college that is known for its excellent curriculum, outstanding and impactful research, and world-renowned faculty. Today, we are ranked #2 for AI and Computer Science by US News Best Global Universities and #8 for Data Science and AI by QS World University Ranking.

A hot bed of cutting-edge technology and groundbreaking research, the College aims to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU's College of Computing and Data Science is an exciting place to learn and grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing.

Cloud Application and Platform Group is a cutting-edge research group from CCDS. It is a leading research group in the area of Cloud Media Computing, Content Delivery Networks, Data Center architecture, and Big Data analytics. We are seeking 1 motivated research engineer in the topic of Digital Twin for Advanced Battery Analytics. The candidate is expected to take the following responsibilities.

Key Responsibilities:

• Architect & Build: Design, develop, and deploy proof-of-concept (PoC) autonomous agentic systems and LLM-powered copilots for critical data center applications.

• Integrate Systems: Seamlessly connect AI agents with sophisticated digital twins, real-time telemetry pipelines, and domain-specific simulation models.

• Develop & Implement: Translate novel agent architectures (including tool-use, planning, and multi-agent collaboration) into functional and robust software systems.

Requirements:

• A Bachelor's degree in Computer Science, AI, Machine Learning, or a related technical field.

• Proven backend development experience with a strong ability to build robust and scalable systems.

• Hands-on experience building with LLMs, agentic frameworks (e.g., LangChain), and/or generative AI.

• Expert-level programming skills in Python and deep familiarity with core ML/LLM libraries (e.g., PyTorch, Hugging Face, OpenAI APIs).

• Practical knowledge of Retrieval-Augmented Generation (RAG), prompt engineering, and designing agents that use external tools.

We regret that only shortlisted candidates will be notified.