About the Role
The Lead Researcher will spearhead the research into technologies aimed at enhancing the efficiency of Large Language Models (LLMs). This includes exploring novel architectures and improved pre-training methods to support various target capabilities.
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.