Research Scientist - Reinforcement Learning

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Develop novel research toward massive scale self-play for foundation model training, agentic tasks, and imbuing models with the capability to proactively learn from its environment.

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Initiate and pursue novel reinforcement learning algorithmic approaches to define and drive emergent capabilities in Foundation Models.

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Full-stack engineering from data curation, model architecture and algorithm design, to final production of models for end-users using high quality (documented, tested, maintainable) code.

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Contribute to technical reports and research publications.

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Represent MBZUAI at industry conferences and events, showcasing the institution’s technology and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation.