About the Role
The Lead LLM Research Scientist will lead the research and development of technologies aimed at improving the efficiency and capabilities of Large Language Models (LLMs). This role involves designing and implementing advanced NLP algorithms, leveraging ML infrastructure, and contributing to model optimization and data processing. The successful candidate will also integrate LLM algorithms with other models, such as computer vision models, and collaborate with internal and external stakeholders to drive innovation in efficient LLM technology.
Responsibilities
- Lead the research of technology for improving the efficiency of Large Language Model (LLM) while performing target capabilities or supporting many capabilities, such as novel architectures and improved pre-training.
- Design and implement NLP algorithms for model training and prediction, leverage ML infrastructure, and contribute to model optimization and data processing, using Pytorch or other frameworks.
- Integrate and improve LLM algorithms to work with other models such as computer vision models.
- Identify defined problems/gaps in existing technology and engage other Research teams, stakeholders and leaders to expand efficient LLM technology.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies.
- Write up results in design documents, technical reports, and papers for publication.
- Represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation.
- Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.