Data Engineer

Job Description

Job Description

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 Data Engineer specializing in Natural Language Processing (NLP) and large-scale data processing, you will quickly and effectively gather, curate, and prepare high-quality datasets to support cutting-edge NLP research. Your role will be instrumental in enabling researchers by delivering essential data through efficient and scalable engineering practices, including web crawling, LLM-generated content refinement, and robust data pipelines, primarily leveraging Python and related technologies.

Key Responsibilities

• Rapidly collect, curate, and preprocess datasets based on detailed specifications provided by NLPresearchers,delivering data within tight timelines.
• Develop and maintain efficient web crawling solutions, APIs, and automated workflows to continuously improve data collection processes.
• Refine and evaluate outputs from Large Language Models (LLMs) to generate structured datasets suitable for model training and benchmarking.
• Implement scalable data pipelines, ensuring efficient data processing, storage, retrieval, and distribution to research teams.
• Collaborate closely with researchers and engineers to ensure collected data meets specified quality and relevance criteria.
• Document data collection methodologies, dataset characteristics, and pipeline architecture clearly and effectively.
• Engage with peer teams and participate in technical reviews to uphold best practices and data quality standards.
• Represent MBZUAI at industry and research forums, showcasing technical capabilities in large-scale data processing and AI data infrastructure.

Academic Qualifications

Professional Experience - Required

Professional Experience - Preferred

Visa Sponsorship

This position is eligible for visa sponsorship.

Benefits Include