Junior Machine Learning Engineer

Job Posting Organization:
The job posting organization is the United Nations Economic and Social Commission for Western Asia (ESCWA), which was established in 197

• ESCWA aims to promote economic and social development in the Arab region through regional cooperation and integration. The organization focuses on various areas including sustainable development, social justice, and economic growth. ESCWA operates in multiple countries across the Arab region, working with member states to enhance their capacities and foster regional collaboration. The organization employs a diverse workforce dedicated to addressing the challenges faced by the region and promoting sustainable development outcomes.

Job Overview:
The Junior Machine Learning Engineer position is designed to support the Arab Development Portal (ADP) by implementing advanced machine learning (ML) models that analyze key development trends in the Arab region. The role emphasizes the importance of data-driven insights related to social, economic, and technological transformations. The incumbent will be responsible for developing data ingestion and transformation pipelines, as well as AI and ML models that will inform technical decisions and data architecture. Additionally, the engineer will implement solutions based on large language models (LLMs) to support the mission of innovation within the Decision-Support and Data Science Division (DSDSD). This position is integral to the modernization and innovation efforts of ESCWA, which aims to leverage data-driven insights and emerging technologies to enhance policymaking and operations across the region.

Duties and Responsibilities:
The Junior Machine Learning Engineer will undertake a variety of tasks, including:

• AI Augmentation and Algorithm Development: - Implementing ETL (Extract, Transform, Load) pipelines to facilitate data processing. - Utilizing the ADP’s infrastructure to develop and implement advanced AI models for data extraction, classification, and matching algorithms, ensuring compatibility with established taxonomies relevant to socioeconomic development in the Arab region. - Exploring alternative large language models (LLMs) to enhance data analysis and classification processes, particularly in economic growth, social development, and sustainability. - Implementing APIs to facilitate communication between different tools developed. - Exploring and implementing agentic development solutions by adapting the deep research architecture to meet UNESCWA needs under the guidance of a senior ML engineer.
• Collaboration and Reporting: - Collaborating with various entities, particularly data scientists, to ensure effective data sharing and analysis aligned with project goals. - Preparing and contributing to reports and presentations that explain findings and methodologies developed during the project.

Required Qualifications:
Candidates must possess a Bachelor's degree in economics, computer science, data science, statistics, or a related field. It is essential that all candidates submit a copy of their educational degree, as incomplete applications will not be reviewed. While no previous work experience is required for this position, candidates must demonstrate knowledge in programming languages such as Python or R. Additionally, familiarity with various machine learning models and techniques is required, while knowledge of artificial intelligence concepts and LLMs is desirable.

Educational Background:
The educational background required for this position includes a Bachelor's degree in a relevant field such as economics, computer science, data science, or statistics. This foundational education is crucial for understanding the complexities of data analysis and machine learning, which are central to the role.

Experience:
This position does not require any previous work experience, making it suitable for recent graduates or individuals looking to enter the field of machine learning and data science. However, candidates should possess a solid understanding of programming and machine learning concepts as outlined in the required qualifications.

Languages:
Fluency in English is required for this position, as it is one of the working languages of the United Nations Secretariat. Fluency in Arabic is desirable, given that it is a working language of ESCWA. Fluency is defined as a rating of 'fluent' in all four areas: speaking, reading, writing, and understanding. Knowledge of French is also beneficial but not mandatory.

Additional Notes:
Recruitment for this position is conducted on a local basis, meaning that candidates must have the legal right to live and work in Lebanon. The position is for a duration of 6 months, and it is important to note that the United Nations does not charge any fees at any stage of the recruitment process, including application, interview, or training. The organization is committed to ensuring a transparent and fair recruitment process.