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.
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/mutli-modal models from
scratch.
$150,000 - $450,000 a year
Salary Range
The posted salary range represents the company’s good faith
estimate of the compensation for this position upon hire. The
actual compensation offered may vary within this range depending on
individual qualifications, including but not limited to relevant
skills, experience, education, certifications, geographic location,
and specific business needs.
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
We may use artificial intelligence (AI) tools to support parts of
the hiring process, such as reviewing applications, analyzing
resumes, or assessing responses and identifying potential
inconsistencies or verification signals in application materials
based on available information. These tools assist our recruitment
team but do not replace human judgment. Final hiring decisions are
ultimately made by humans. If you would like more information about
how your data is processed, please contact us.
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.
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/mutli-modal models from
scratch.
$150,000 - $450,000 a year
Salary Range
The posted salary range represents the company’s good faith
estimate of the compensation for this position upon hire. The
actual compensation offered may vary within this range depending on
individual qualifications, including but not limited to relevant
skills, experience, education, certifications, geographic location,
and specific business needs.
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
We may use artificial intelligence (AI) tools to support parts of
the hiring process, such as reviewing applications, analyzing
resumes, or assessing responses and identifying potential
inconsistencies or verification signals in application materials
based on available information. These tools assist our recruitment
team but do not replace human judgment. Final hiring decisions are
ultimately made by humans. If you would like more information about
how your data is processed, please contact us.
