AI / Machine Learning Engineer

Role Overview

Key Responsibilities

• Design and develop machine learning models for practical business applications.
• Build, test, evaluate, and optimize AI solutions against defined objectives.
• Prepare, transform, and analyze data for model development and experimentation.
• Develop reusable workflows for training, validation, deployment, and monitoring.
• Research emerging AI and machine learning techniques relevant to business needs.
• Collaborate with software engineers, data scientists, product teams, and stakeholders.
• Monitor model performance and identify opportunities for improvement.
• Support integration of AI capabilities into existing products and systems.
• Document technical approaches, model performance, assumptions, and results.
• Promote responsible, scalable, and reliable approaches to AI development.

Requirements

• A bachelor’s degree or equivalent qualification in a related field is preferred.
• Three or more years of relevant AI, machine learning, software engineering, or data science experience is preferred.
• Strong understanding of machine learning algorithms, model evaluation, and data preparation.
• Knowledge of supervised and unsupervised learning techniques.
• Familiarity with Python and commonly used machine learning frameworks and libraries.
• Understanding of APIs, databases, software development, and model deployment concepts.
• Strong analytical, problem-solving, communication, and organizational skills.
• Ability to work independently in a remote environment.
• Professional certifications are not required unless specifically relevant to the role.

Work Arrangement

• The position is part-time and fully remote within the United Arab Emirates.
• The role requires independent work in a remote environment.

What the Company Offers

• Flexible part-time working arrangements in a fully remote environment.
• Competitive compensation aligned with experience and responsibilities.
• Opportunities to work on practical AI and machine learning initiatives.
• Exposure to emerging technologies, international teams, and cross-functional projects.
• Professional growth through challenging technical and business-focused work.
• A collaborative culture supporting innovation, responsible AI, and continuous learning.