The Alibaba-NTU Global e-Sustainability CorpLab (ANGEL) represents a key collaboration between Alibaba Group and Nanyang Technological University (NTU). Supported by the Singapore RIE2025 Fund, ANGEL creates and deploys impactful green digital technologies for global sustainability.

ANGEL’s mission aligns seamlessly with Singapore’s national objectives, such as the Singapore Green Plan 2030 and the Singapore Smart Nation Initiative. ANGEL’s work in developing sustainable and equitable digital solutions and promoting a sustainable and green lifestyle will contribute to a smaller carbon footprint. Its holistic approach will help to secure a brighter, more sustainable future for humanity. 

We are looking for a motivated Research Scientist to conduct innovative research and develop intelligent algorithms and system frameworks that optimize cost, performance, and scalability. The role focuses on leveraging machine learning and reinforcement learning to enhance storage and service efficiency under dynamic workloads, while bridging theoretical research with practical implementation through close collaboration with cross-functional teams.

Job Description:

• Design, development, and implementation novel machine learning and large language model (LLM) algorithms for Green AI applications.
• Conduct research of efficient AI techniques, including model optimization, parameter-efficient fine-tuning, self-training, retrieval-augmented generation (RAG), prompt engineering, and efficient inference.
• Conduct experiments, benchmark algorithms, and analyze performance using rigorous scientific methodologies.
• Publish research findings in leading AI conferences and journals
• Collaborate with cross-functional teams to translate research outcomes into deployable technologies.
• Keep abreast of the latest developments in Green AI, foundation models, code intelligence, and AI systems.

Job Requirements:

• PhD in Computer Science, Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, or a related discipline.
• Strong background in machine learning, deep learning, and large language models.
• Experience working with large-scale datasets and distributed model training.
• Strong programming skills in Python.
• Experience with modern deep learning frameworks such as PyTorch or TensorFlow.
• Strong analytical and problem-solving abilities.
• Good written and verbal communication skills.
• Ability to work independently and effectively in collaborative research environments.

We regret to inform that only shortlisted candidates will be notified.