Research Engineer: Statistics and Machine Learning

forecasting, or anomaly detection, but candidates with relevant experience in other areas of machine learning are encouraged to apply. The lab collaborates with leading academic and industry partners. The position includes a competitive tax-free monthly salary, housing allowance, comprehensive medical insurance, an annual return flight to the home country, and full visa application support.

Key Responsibilities:

• Implement and evaluate machine-learning and statistical methods across a range of research projects. Example areas may include probabilistic prediction, uncertainty quantification, conformal prediction, time-series forecasting, and anomaly detection, among others.
• Build reliable and reproducible workflows for data preprocessing, model training, evaluation, and visualization.
• Run experiments, establish baselines, analyze model performance, troubleshoot technical issues, and communicate findings to researchers.
• Develop maintainable research software using version control, code review, automated testing, documentation, and reproducible environments.
• Maintain shared research code and computing workflows and support efficient experimentation where needed. Collaborate with research-group members and academic and industry partners and contribute to technical reports, research papers, and demonstrations.
• Strong programming skills in Python.

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is a world-leading university dedicated to advancing AI as a global force for good. The UAE’s visionary leaders established MBZUAI to educate and develop top talent, conduct advanced research, foster an innovation ecosystem, and act as a strategic think tank for the public and private sectors.

The University attracts world-class thinkers and doers in computer science, AI, bioscience, humanities and beyond. Our groundbreaking academic research initiatives are working on developing future solutions that will impact the world and change the way we imagine things.

Why Join MBZUAI?

• Top-Tier Compensation: Competitive salaries aligned with leading global academic institutions
• Exceptional Benefits:
  • Comprehensive health & life insurance
  • Relocation support for international hires
• Live in Abu Dhabi: World’s safest city, year-round sunshine, rich culture, and modern amenities
• Industry & Government Collaborations: Work with top AI researchers, leading tech firms, and policymakers

Qualifications

• Knowledge of machine learning or statistical modeling and experience implementing and evaluating models using relevant datasets.
• Experience with Git, Linux, testing, and writing clear, maintainable, and documented research code.
• Excellent organizational and communication skills, including excellent written and spoken English.
• Master's degree in Computer Science, Applied Mathematics, Statistics, Data Science, or a related discipline.

Preferred Qualifications

• Experience with a commonly used machine-learning framework or library, such as PyTorch, JAX, TensorFlow, or scikit-learn.
• Experience with research software, large-scale experimentation, GPU computing, high-performance computing, or cloud computing.
• Familiarity with modern AI-assisted software-development tools or coding agents.
• Publications, open-source contributions, or substantial thesis or applied-project experience in AI or a related field.
• Experience working in multidisciplinary or international collaborations.
• Coursework or training in machine learning, statistical modeling, data science, software engineering, or a related area.

Application Instructions

To apply for this position, please submit the following items: Interested candidates should submit the following documents:

• Cover Letter
• Curriculum Vitae (C.V.)
• A link to your Google Scholar profile.
• A 1–2 page research statement outlining directions you would like to pursue in Statistics and Machine Learning.
• Name and contact details for three referees (Referees will be contacted if the candidate moves to the final stages)