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 operates in 17 member states and focuses on various areas including sustainable development, social justice, and economic growth. ESCWA is committed to providing a platform for dialogue and collaboration among member states, and it plays a crucial role in supporting the implementation of the 2030 Agenda for Sustainable Development in the region.

Job Overview:
The Machine Learning Engineer position is designed to support the Arab Development Portal's initiatives by leveraging advanced machine learning techniques to analyze and interpret key development trends in the Arab region. The role involves designing, developing, and deploying sophisticated machine learning models that provide data-driven insights into social, economic, and technological transformations. The engineer will be tasked with building robust data pipelines and maintaining machine learning models at scale, ensuring that the solutions developed align with the innovation mandate of the Decision-Support and Data Science Division (DSDSD). This position is integral to enhancing the organization's capacity to utilize data effectively for policymaking and operational improvements, thereby contributing to evidence-based decision-making across the region.

Duties and Responsibilities:
The Machine Learning Engineer will undertake a variety of tasks, including but not limited to:

• Machine Learning Model Development: This includes designing, training, evaluating, and deploying both supervised and unsupervised machine learning models for various tasks such as forecasting, classification, clustering, anomaly detection, and natural language processing on regional datasets. The engineer will also implement and maintain ETL pipelines for data ingestion and transformation from diverse sources, ensuring data quality and integration.
• LLM Integration and Agentic Solutions: The engineer will explore and benchmark various large language models (LLMs) to enhance data analysis and content generation processes. This involves implementing LLM-powered pipelines for document understanding and information extraction, particularly focusing on Arabic and multilingual content.
• API Integration and Technical Infrastructure: The role requires designing and implementing RESTful APIs to expose machine learning model outputs, ensuring that these outputs integrate seamlessly with the broader data ecosystem. The engineer will also ensure that models are scalable and maintainable, with thorough documentation for institutional use.
• Collaboration and Reporting: The engineer will work closely with data scientists, engineers, and domain experts to facilitate effective communication and data sharing. They will also prepare technical reports and presentations to communicate methodologies and findings to both technical and non-technical audiences.

Required Qualifications:
Candidates must possess a bachelor's degree in computer science, data science, applied mathematics, statistics, or a related field. A master's degree in one of these areas is desirable. All applicants are required to submit a copy of their educational degree, as incomplete applications will not be considered. Additionally, a minimum of 5 years of professional experience in machine learning engineering or a closely related field is required. Proficiency in Python and core machine learning libraries such as NumPy, pandas, scikit-learn, and either PyTorch or TensorFlow is essential. Candidates should also have experience in designing and deploying end-to-end machine learning pipelines in production environments, as well as knowledge of LLMs and their integration into analytical workflows.

Educational Background:
The educational background required for this position includes a bachelor's degree in a relevant field such as computer science, data science, applied mathematics, or statistics. A master's degree in these areas is considered an asset. Candidates must provide proof of their educational qualifications, as incomplete applications will not be reviewed.

Experience:
The position requires a minimum of 5 years of professional experience in machine learning engineering or a closely related discipline. Candidates should have demonstrated experience in developing and deploying machine learning models, as well as familiarity with MLOps practices and tools for experiment tracking and pipeline orchestration. Experience with cloud or containerized ML deployment environments is also desirable, along with a background in natural language processing tasks and multilingual or Arabic language models.

Languages:
Fluency in English is required for this position, as it is one of the working languages of the United Nations Secretariat. Additionally, knowledge of French is beneficial, and Arabic is a working language of ESCWA. Fluency in English means a rating of 'fluent' in all four areas: speaking, reading, writing, and understanding. Knowledge of French or Arabic is considered a plus but is not mandatory.

Additional Notes:
The position is expected to be remote and has a duration of 6 months. The United Nations does not charge any fees at any stage of the recruitment process, including application, interview, or training. Furthermore, the organization does not request information regarding applicants' bank accounts.