Summary
United Arab Emirates University’s Big Data Analytics Center (BIDAC) is seeking a Data Engineer for its AI and digital innovation research team. The role involves building data pipelines and databases, developing and deploying LLM and NLP systems, and fine-tuning models for domain-specific applications. The engineer will also support model evaluation, production integrations, research publications, grant proposals, and technical documentation. Applicants need a bachelor’s degree in a relevant field and experience with Python, data processing, machine learning frameworks, databases, and cloud platforms; a master’s degree and LLM deployment experience are preferred.
The posting
As published on uaeu.ac.ae. Pulled from the employer's site and shown as they wrote it.
Job description
The Big Data Analytics Center (BIDAC) at UAE University is expanding its research and innovation team to advance the next generation of AI, Machine Learning, and Large Language Model (LLM) applications. The Center plays a national leadership role in AI research, data infrastructure, and digital transformation, supporting major UAE initiatives in smart government, education, and innovation.
We are seeking highly motivated Data Engineers who will contribute to developing and deploying scalable AI and NLP systems, with a focus on LLM fine-tuning, optimization, and deployment in secure, domain-specific environments.
This is an exceptional opportunity to work in a cutting-edge AI lab within a top research university, collaborating with multidisciplinary teams to deliver impactful projects that advance the UAE’s AI capabilities.
Key Responsibilities:
• Design, build, and maintain data pipelines, ETL workflows, and databases supporting AI/ML projects.
• Develop and deploy LLMs and NLP pipelines for real-world use cases (education, government services, healthcare, etc.).
• Conduct data preprocessing, cleaning, feature extraction, and model training for structured and unstructured data.
• Fine-tune and optimize foundation models (GPT, LLaMA, Falcon, etc.) using domain-specific datasets.
• Collaborate with research teams on AI model evaluation, interpretability, and explainability.
• Integrate AI models with front-end applications, APIs, and databases for operational deployment.
• Support research publications, grant proposals, and technical documentation under BIDAC initiatives.
Minimum qualification
- Bachelor’s degree (BSc) in Computer Science, AI, Data Science, Data Engineering, or a related field.
- Strong programming skills in Python and experience with data processing libraries (Pandas, NumPy, PySpark, etc.).
- Experience in machine learning model development using frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
- Solid understanding of data structures, algorithms, and statistical methods.
- Experience working with databases (SQL/NoSQL) and cloud platforms (AWS, Azure, or GCP).
Preferred qualification
- Master’s degree in AI, Data Science or a related field.
- Prior experience in LLM fine-tuning, distillation, or on-premises deployment (e.g., Falcon, LLaMA, Mistral).
- Experience building knowledge graphs or retrieval-augmented generation (RAG) pipelines.
- Knowledge of distributed computing (Spark, Dask, Ray) and data lake architectures.
- Experience integrating AI systems into production-grade web or enterprise applications.
- Contribution to open-source AI projects, or publications in high-impact AI/ML venues.
- Understanding of Arabic NLP and bilingual (EN/AR) model development is a plus.
Expected skills
- Proficiency in NLP and LLM ecosystems, including tokenization, embeddings, transformers, and model fine-tuning.
- Familiarity with LangChain, Hugging Face Transformers, and OpenAI / Anthropic / Cohere APIs.
- Understanding of MLOps, containerization (Docker), and deployment tools (FastAPI, Streamlit, MLflow, etc.).
- Strong knowledge of data versioning and reproducibility tools (DVC, Git, etc.).
- Ability to handle large-scale, multi-modal datasets (text, audio, video, sensor data).
- Excellent analytical and problem-solving skills with a research mindset.
- Strong written and verbal communication skills for technical and interdisciplinary collaboration.
Department
Center For AI & Digital Innovation
College or division
Research Centers