AI / Machine Learning Enginr

🌟 We're Hiring: AI / Machine Learning Engineer

📍 Location: United Arab Emirates (Remote)

🕒 Employment Type: Part-Time

💼 Experience Level: Mid-Level to Senior

🌐 Work Arrangement: Fully Remote

About Us

We are focused on leveraging artificial intelligence, machine learning, and data-driven innovation to solve practical business challenges and improve digital experiences. Our approach combines technical excellence, responsible AI development, and continuous experimentation. We value professionals who think critically, collaborate effectively, and transform complex data and emerging technologies into scalable solutions that deliver measurable business value.

The Role

We are seeking a technically skilled AI / Machine Learning Engineer to help design, develop, test, and optimize intelligent systems. In this part-time remote role, you will contribute to machine learning model development, data preparation, algorithm evaluation, and the integration of AI capabilities into applications and business workflows.

Working with data, software, and product stakeholders, you will help translate business requirements into practical AI solutions. The ideal candidate combines strong programming skills with analytical thinking and an interest in building reliable, efficient, and maintainable machine learning systems.

Key Responsibilities

• Design, develop, and evaluate machine learning models for classification, prediction, recommendation, and other business applications.
• Prepare, clean, transform, and analyze datasets to support model training and evaluation.
• Apply appropriate statistical methods, algorithms, and machine learning techniques to solve defined problems.
• Build and improve data pipelines and model workflows in collaboration with engineering and analytics teams.
• Evaluate model performance using suitable metrics and recommend improvements based on experimental results.
• Develop reusable code and maintain clear technical documentation for models, experiments, and implementations.
• Integrate AI and machine learning components into existing applications, APIs, or business processes.
• Support model testing, deployment, monitoring, and performance optimization.
• Explore relevant developments in machine learning, generative AI, and related technologies to identify practical opportunities.
• Collaborate with cross-functional teams to understand requirements and communicate technical findings.
• Identify data quality issues, model limitations, and potential risks, including bias and reliability concerns.
• Follow responsible AI practices and contribute to secure, scalable, and maintainable solutions.

Requirements

• At least 3 years of relevant experience in machine learning, AI engineering, data science, or software development preferred.
• A bachelor's degree or equivalent qualification in Computer Science, Data Science, Mathematics, Engineering, or a related field preferred.
• Proficiency in Python and familiarity with common data science and machine learning libraries such as scikit-learn, PyTorch, or TensorFlow.
• Understanding of machine learning algorithms, statistical concepts, model evaluation, and data preprocessing.
• Experience working with structured datasets, data pipelines, and model experimentation.
• Familiarity with APIs, version control, and software development best practices.
• Knowledge of cloud-based AI services, model deployment, or MLOps practices is an advantage.
• Strong analytical thinking, problem-solving skills, and attention to detail.
• Effective communication skills and the ability to work independently in a remote environment.
• Professional certifications are welcome but not mandatory.

What We Offer

• Flexible part-time work in a fully remote environment.
• Opportunities to contribute to practical AI and machine learning initiatives.
• A collaborative culture that values experimentation, technical quality, and innovation.
• Opportunities to expand expertise in model development, AI integration, and emerging technologies.
• A professional environment focused on responsible innovation, continuous learning, and measurable impact.