Research Scientist - NLP

Job description

About the Institute of Foundation Models We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. **As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development.** You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers. **The Role** As a Research Scientist specializing in Natural Language Processing (NLP) with a focus on large language models and deep learning, your role will be crucial in advancing cutting-edge language processing technologies and contributing to the development of intelligent systems. You will be responsible for a wide range of tasks encompassing research, development, and implementation of NLP solutions, with a particular emphasis on Python coding, machine learning techniques, and deep learning methodologies. ### Key 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. ### Academic Qualifications - **Minimum**: Master’s in Computer Science, a related technical field, or equivalent practical experience - **Preferred**: PhD or equivalent research experience in Natural Language Processing ### Professional Experience - Minimum - Experience with state-of-the-art Gen AI techniques and models (e.g., LLMs, Multi-Modal, Large Vision Models) or with Gen AI-related concepts (e.g., language modeling, computer vision). - Experience with software development in one or more programming languages (e.g. Python, C++), and with data structures/algorithms. - Excellent problem-solving and troubleshooting skills to address complex technical challenges. - Effective communication and collaboration skills to work with cross functional teams. - Ability to effectively navigate ambiguity. ### Professional Experience - Preferred - Experience leading research efforts and influencing other researchers. - Experience with efficiency, modularity or related topics for LLMs. - Experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). - Experience with design and optimization of algorithms in performance constrained environments (e.g., mobile). - Experience in innovative research, contributing to research communities including publishing in forums (e.g., ACL, EMNLP, NAACL, EACL, COLING, ICLR, AAAI, NeurIPS).