Institute of Foundation Models
NLP
San Francisco, CAOn-siteFull-time$140k – $220k / year
About this role
Institute of Foundation Models - Research Engineer - NLP
Research Engineer - NLP
Abu Dhabi
Engineering /
Full-time /
On-site
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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
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