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Institute of Foundation Models

Researches and develops foundation models

Research Scientist - Data

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeSunnyvale, CA, USA

About the Job

Requirements

  • A Master's degree in Computer Science, Data Science, or a related technical field, or equivalent practical experience, is required.
  • Experience working with large language models, including evaluation, fine-tuning, and prompt engineering.
  • Strong Python development skills focused 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 machine-learning infrastructure, including model evaluation, optimization, and debugging.
  • Ability to identify impactful research questions and execute them with minimal supervision.
  • Effective communication and collaboration skills for working in cross-functional teams.

Responsibilities

  • Pioneer web-scale data collection and curation methodologies for large language models and multimodal 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.
  • Explore and consolidate data sources and collaborate with cross-functional teams to conduct in-depth data research.
  • Curate high-quality web-scale data to fuel the development of next-generation foundation models.

Desired Qualifications

  • A PhD or equivalent research experience in Machine Learning, NLP, or Data Science, with a focus on large language models and data.
  • Prior research experience in web data curation and mixing, synthesizing complex datasets for training, large language model evaluation, post-training data, efficient inference, large-language-model-as-a-judge, or tokenization.
  • A strong publication record in leading AI conferences such as NeurIPS, ICLR, ICML, or EMNLP, and/or prior contributions to open-source AI research or data tools.
  • Hands-on experience training language or multimodal models from scratch.

About the Company

Institute of Foundation Models

Researches and develops foundation models

IFM builds and studies foundation models—large AI models designed to learn broadly from diverse data and be used across many tasks. Its work centers on academic research to create open, fast, and practical models that address real-world societal needs, rather than narrow applications. The models are developed by a global team across Abu Dhabi, Paris, and Silicon Valley, with a strong emphasis on openness and collaboration to advance AI science and accessibility. Unlike typical private labs that lock models behind paywalls, IFM aims to provide publicly accessible, efficient models that can be used by researchers and developers to solve real problems. The overarching goal is to push the science of foundation models forward while ensuring their benefits reach society at large.

Company size
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Total funding
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Headquarters
United Arab Emirates
Founded
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