Research Scientist - Data

About the Role MBZUAI is a dedicated research lab focused on building and understanding foundation models. The Research Scientist in the Data team will curate high‑quality data at web‑scale, collaborate with cross‑functional teams, and contribute to AI research that influences industries worldwide. Responsibilities Pioneer web‑scale data collection and curation methodologies for LLMs and multi‑modal foundation models Design and implement novel data synthesis pipelines for code, mathematics, and agentic reasoning datasets Trace the impact of data from pre‑training to final model capabilities and create automated quality assessment frameworks for massive datasets Design data recipes that maximize model capabilities across diverse domains Optimize data‑model co‑design for improved training dynamics Contribute to research papers and represent MBZUAI at industry conferences and events, showcasing the institution’s AI research and innovation Required Qualifications Minimum: Master's in Computer Science, Data Science, or a related technical field, or equivalent practical experience required Experience working with large language models , including evaluation, fine‑tuning , and prompt engineering Strong Python development skills with a focus on research‑grade code and scalable data pipelines Familiarity with collecting and processing large‑scale datasets from open‑source and web resources Demonstrated ability to work with ML infrastructure (e.g., model evaluation , optimization , debugging ) Proactive mindset with the ability to identify impactful research questions and execute on them with minimal supervision Effective communication and collaboration skills for working in cross‑functional teams Preferred Qualifications PhD or equivalent research experience in Machine Learning, NLP , or Data Science with a focus on LLMs and data is preferred Prior research experience in areas such as web data curation and mixing, synthetizing complex datasets for training, LLM evaluation, post‑training data, efficient inference, LLM‑as‑a‑judge, tokenization Strong publication record in leading AI conferences (e.g., NeurIPS, ICLR, ICML, EMNLP) and/or prior contributions to open‑source AI research or data tools Hands‑on experience training language/multi‑modal models from scratch Benefits Comprehensive medical, dental, and vision benefits Bonus 401K Plan Generous paid time off, sick leave and holidays Paid Parental Leave Employee Assistance Program Life insurance and disability #J-18808-Ljbffr