The Role
Curate web-scale datasets and design data synthesis pipelines to support foundation-model training. Develop automated data quality assessment, trace data impact on model capabilities, optimize data-model co-design, and contribute to research publications and conferences.
Summary Generated by Built In
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 in the Data team, your primary responsibility is to curate high quality data at the web-scale to fuel the development of next generation foundation models. You will work on exploring andconsolidatingdata sources and collaborate with cross-functional teams to conduct in-depth data research, contributing to MBZUAI’s mission of driving impactful AI discoveries and positioning the institution as a leader in the global AI research community. Your expertise will be key in enhancing the performance of large-scale machine learning models, while supporting the development of transformative AI tools that can influence industries worldwide.
Key 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.
Academic Qualifications
- Minimum: Master’s in Computer Science, Data Science, or a related technical field, or equivalent practical experience required.
- Preferred: PhD or equivalent research experience in Machine Learning, NLP, or Data Science with a focus on LLMs and data is preferred.
Professional Experience
- 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.
- 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/mutli-modal models from scratch.
Preferred
Visa Sponsorship
This position is eligible for visa sponsorship.
Benefits Include
*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
Skills Required
- Master's in Computer Science, Data Science, or a related technical field, or equivalent practical experience
- PhD or equivalent research experience in Machine Learning, NLP, or Data Science (preferred)
- Experience working with large language models including evaluation, fine-tuning, and prompt engineering
- Strong Python development skills focused on research-grade code
- Experience building scalable data pipelines for large datasets
- Familiarity with collecting and processing large-scale datasets from open-source and web resources
- Experience with ML infrastructure (model evaluation, optimization, debugging)
- Proactive research mindset and ability to work with minimal supervision; strong communication and collaboration skills
- Prior research experience in web data curation, dataset synthesis, LLM evaluation, or tokenization
- Publication record in top AI conferences or contributions to open-source AI/data tools
- Hands-on experience training language or multi-modal models from scratch
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The Company
What We Do
First a passion, then an idea transformed into success – when it comes to pioneering automation and digitalisation technology, the ifm group is the ideal partner. Since its foundation in 1969, ifm has developed, produced and sold sensors, controllers, software and systems for industrial automation and for SAP-based solutions for supply chain management and shop floor integration worldwide. As one of the pioneers of Industry 4.0, ifm develops and implements consistent solutions to digitalise the entire value chain “from sensor to ERP”. Today, the second-generation family-run ifm group has more than 8,750 employees and is one of the worldwide market leaders. The group combines the internationality and innovative strength of a growing group of companies with the flexibility and close customer contact of a medium-sized company.
