Location: Damascus

Employment Type: Full-time, On-site

Job Purpose:
The AI Engineer is responsible for designing, developing, and deploying AI-driven solutions to support operations, logistics, and personalization. This role involves building advanced predictive models, developing intelligent decision-making systems, and transforming complex data into actionable, production-ready solutions. The AI Engineer works closely with Product and Engineering teams to deliver high-performance systems that support business objectives and enhance operational efficiency.

Key Responsibilities:

1. Lead end-to-end development of AI solutions from concept to production deployment.
2. Design and implement time-series forecasting models, routing algorithms, and real-time prediction systems.
3. Perform advanced feature engineering on high-dimensional data such as orders, drivers, and user behavior.
4. Build and manage machine learning pipelines (ML Pipelines) using Python, databases (MySQL), caching tools (Redis), and modern cloud technologies.
5. Apply causal inference and data analysis techniques to identify key operational performance drivers.
6. Develop APIs and internal tools to enable cross-functional teams to leverage model outputs.
7. Monitor model performance in production and continuously improve accuracy, efficiency, and reliability.
8. Experiment with external datasets and employ transfer learning or foundation models when needed.
9. Collaborate with cross-functional teams to translate business requirements into actionable AI solutions.
10. Keep up-to-date with AI trends and contribute to the development of the company's technical strategy.

Qualifications & Requirements:

• Bachelor's degree or higher in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Minimum of 2 years of practical experience developing and deploying machine learning models in production environments.
• Proficiency in Python with strong experience in machine learning applications.
• Advanced understanding of feature engineering, especially for time-series and structured data.
• Hands-on experience in causal modeling, optimization problems, or real-time inference systems.
• Experience developing systems using REST APIs or microservice architectures.
• Strong problem-solving skills, with the ability to translate ambiguous problems into actionable technical solutions.
• Excellent communication skills and ability to work effectively in cross-functional teams.
• Ability to work in a fast-paced environment and handle high-pressure situations.

Preferred Qualifications:

• Experience with large language models (LLMs), RAG architectures, or autonomous agent systems.
• Experience in natural language processing (NLP), embeddings, or vector search systems.
• Background in operations research or optimization of delivery networks.
• Familiarity with ML model monitoring, A/B testing, and causal evaluation methods