Research Engineer - NLP
MBZUAI Institute of Foundation Models · Abu Dhabi, United Arab Emirates · 1y ago
Mid levelOn-siteMachine Learning & AI
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).