Green AI Research Scientist – ML/LLM for Sustainable Tech

Nanyang Technological University

Singapore

On-site

SGD 120,000 - 180,000

Full time

4 days ago
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Job summary

ANGEL (Alibaba-NTU Global e-Sustainability CorpLab) at NTU seeks a Research Scientist to advance Green AI through machine learning and reinforcement learning, improving cost, performance and scalability. Work bridges theory with practical implementation alongside cross-functional teams in Singapore.

Applicants should hold a PhD in a related field, be proficient in Python and DL frameworks, and have experience with large-scale data and distributed training. Publication in top venues is encouraged.

Qualifications

  • PhD in Computer Science, AI, DS, EE, or related field.
  • Strong background in ML, DL, and LLMs.
  • Experience with large-scale datasets and distributed training.
  • Proficient in Python.
  • Experience with PyTorch or TensorFlow.

Responsibilities

  • Design and implement ML/LLM algorithms for Green AI.
  • Conduct experiments, benchmark algorithms, and analyze performance.
  • Publish research findings in leading AI conferences and journals.
  • Collaborate with cross-functional teams to translate research into deployable tech.
  • Stay updated on Green AI, foundation models, code intelligence and AI systems.
  • Contribute to advances in AI research and scalable deployment.

Skills

Machine Learning
Deep Learning
Large Language Models
Python
PyTorch
TensorFlow
Research

Education

PhD in Computer Science or related field

Tools

PyTorch
TensorFlow

Job description

ANGEL (Alibaba-NTU Global e-Sustainability CorpLab) at NTU seeks a Research Scientist to advance Green AI through machine learning and reinforcement learning, improving cost, performance and scalability. Work bridges theory with practical implementation alongside cross-functional teams in Singapore.

Applicants should hold a PhD in a related field, be proficient in Python and DL frameworks, and have experience with large-scale data and distributed training. Publication in top venues is encouraged.

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