The Role
Build and maintain large-scale data collection and preprocessing pipelines for NLP research. Develop web crawlers, APIs, and workflows; refine LLM outputs into structured datasets; collaborate with researchers to ensure data quality and document methodologies. Support scalable storage, retrieval, and distribution of datasets.
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 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
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field required
- Master’s degree or PhD degree or equivalent experience in Computer Science, Data Engineering, or related technical fields preferred.
Professional Experience - Required
- Extensive experience in data engineering, data processing, and automation using Python.
- Demonstrated proficiency in designing and deploying web crawling solutions, automated data extraction, and processing pipelines.
- Strong understanding of data structures, algorithms, databases, SQL, and performance optimization.
- Experience working with cloud infrastructure and distributed data processing frameworks (e.g., AWS, Spark, Kafka, Kubernetes).
- Excellent problem-solving abilities, attention to detail, and the capability to rapidly address technical challenges.
- Strong communication and collaboration skills with cross-functional teams.
Professional Experience - Preferred
- Proven track record of supporting NLP or AI research teams with rapid and reliable data delivery.
- Experience working with large language models, including evaluation, efficient inference, and prompt engineering.
- Experience with refining outputs from large-scale AI models, such as LLM-generated data.
- Contributions to open-source projects, coding competitions, or high visibility in coding communities (e.g., GitHub, Stack Overflow).
- Familiarity with the latest advancements in NLP data processing and large language model technologies.
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
- Bachelor's degree in Computer Science, Data Science, Engineering, or related technical field
- Extensive experience in data engineering, data processing, and automation using Python
- Proficiency designing and deploying web crawling solutions, automated data extraction, and processing pipelines
- Strong understanding of data structures, algorithms, databases, SQL, and performance optimization
- Experience with cloud infrastructure and distributed data processing frameworks (e.g., AWS, Spark, Kafka, Kubernetes)
- Strong communication and collaboration skills with cross-functional teams
- Master's or PhD in Computer Science, Data Engineering, or related field
- Proven track record supporting NLP or AI research teams and working with large language models (LLMs), prompt engineering, or LLM output refinement
- Contributions to open-source projects or high visibility in coding communities (e.g., GitHub)
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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.
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