Machine Learning Engineer
4 days ago
Collaborate with Us
Nanyang Technological University's (NTU) National Centre for Research in Digital Trust (DTC) is a dynamic research centre that fosters collaboration among experts from diverse fields. We invite applications for a Research Fellow position to join our interdisciplinary research team and contribute to our cutting-edge research in Generative AI, focusing on the design, development, and optimization of multi-modal LLMs.
Job Description:
You will be part of a talented team that investigates and implements methodologies to ensure AI authenticity, accountability, and the integrity of digital content. You will also develop and refine machine learning and deep learning algorithms, including machine unlearning techniques, to enhance model robustness and reliability.
Key Responsibilities:
- You will design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems.
- You will collaborate with interdisciplinary teams to align AI research with ethical standards and best practices in AI safety.
- You will publish findings in top-tier conferences and journals, contributing to the broader AI and machine learning research community.
Requirements:
- PhD in computer science/engineering or related fields.
- Proficiency in Python is a must. 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.
- 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.
- Self-motivated and able to work independently, managing multiple tasks and projects in a fast-paced environment.
- Strong collaborative skills, with experience working in cross-functional teams.
- Keen attention to detail and commitment to high-quality deliverables.
- Understanding of ethical considerations and best practices in AI research, particularly concerning data privacy and security.
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