Expert in Multimodal Machine Learning

2 weeks ago

Singapore beBeeArtificial Full time $90,000 - $120,000
Researcher in Artificial Intelligence

We are seeking a Research Fellow to join our Digital Trust Centre. The successful candidate will focus on multi-modal model testing, conducting advanced research in Generative AI and designing, developing, and optimizing multi-modal LLMs.

Key Responsibilities:

  • Conduct cutting-edge research in Generative AI, focusing on the design, development, and optimization of multi-modal LLMs.
  • Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content.
  • Develop and refine machine learning and deep learning algorithms, including machine unlearning techniques, to enhance model robustness and reliability.
  • Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems.
  • Collaborate with interdisciplinary teams to align AI research with ethical standards and best practices in AI safety.
  • Publish findings in top-tier conferences and journals, contributing to the broader AI and machine learning research community.

Requirements:

  • PhD degree in computer science/ engineering or related field.
  • Proficiency in Python is mandatory.
  • Experience with other programming languages such as Java, C/C++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous.
  • Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large language models (LLMs), including tasks such as data preprocessing, feature extraction, model training, and evaluation.
  • Background in Generative AI research, including multi-modal LLMs as well as background in AI Safety research, including AI authenticity, accountability, and integrity of digital content.
  • Strong knowledge of machine learning and deep learning techniques, including machine unlearning, and AI testing.
  • Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders, bridging the gap between research and practical application.
  • Strong analytical and problem-solving skills, with a focus on developing innovative solutions for multi-modal LLMs.
  • Understanding of ethical considerations and best practices in AI research, particularly concerning data privacy and security.
  • Competent in collaborative skills, with experience working in cross-functional teams.

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