AI Machine Learning Engineer

Global Aerospace Logistics, LLC; Abu Dhabi; Sur place; AED 180 000 - 300 000; Plein temps

Résumé du poste

Global Aerospace Logistics (GAL) in Abu Dhabi seeks an AI Machine Learning Engineer to design, develop, deploy and maintain ML solutions that enhance operational efficiency and drive data-driven decisions across the organization.

You will collaborate with data scientists, software engineers and business stakeholders to build scalable AI applications, productionize models, deploy via APIs and cloud platforms, monitor performance, and implement MLOps practices including CI/CD, versioning, and

Qualifications

• Bachelor's degree in CS/DS/AI/SE or related field.
• Strong programming skills in Python.

Responsabilités

• Design, build, train, and deploy machine learning models.
• Develop scalable data pipelines and feature engineering workflows.
• Productionize AI and machine learning solutions.
• Deploy models through APIs, microservices, and cloud platforms.
• Monitor, retrain, and optimize model performance.
• Implement MLOps practices including CI/CD, model versioning, and monitoring.
• Ensure data quality, security, and compliance requirements are met.
• Document AI systems, models, and technical workflows.

Connaissances

Python

Formation

Bachelor's degree in Computer Science/ Data Science/ AI/ Software Engineering

Outils

MLflow

Kubeflow

Airflow

Description du poste

Global Aerospace Logistics (GAL) is seeking a talented and driven AI Machine Learning Engineer to join our AI and Digital Transformation team. This role is responsible for designing, developing, deploying, and maintaining machine learning solutions that drive operational efficiency, automation, and data-driven decision making across the organization.

You will work closely with data scientists, software engineers and business stakeholders to build scalable AI applications and bring machine learning models into production environments.

Responsibilities:

• Design, build, train, and deploy machine learning models.
• Develop scalable data pipelines and feature engineering workflows.
• Productionize AI and machine learning solutions.
• Deploy models through APIs, microservices, and cloud platforms.
• Monitor, retrain, and optimize model performance.
• Implement MLOps practices including CI/CD, model versioning, and monitoring.
• Ensure data quality, security, and compliance requirements are met.
• Document AI systems, models, and technical workflows.
• Collaborate across multidisciplinary teams to deliver AI initiatives.

Qualifications:

• Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related field.
• Strong programming skills in Python.

Experience Required:

• 3-8 years of experience in Machine Learning, Data Science, or Software Engineering.
• Minimum 2 years of hands-on experience deploying machine learning models into production.
• Experience in machine learning model development, feature engineering, data pipelines, and model deployment, with knowledge of MLOps tools such as MLflow, Kubeflow, or Airflow.
• Experience with Generative AI, LLMs, NLP, Computer Vision, or similar AI technologies is an advantage