Senior Machine Learning Engineer

About the Role

We are looking for an experienced Senior Machine Learning Engineer based in Qatar to lead the design, creation, deployment, and management of scalable machine learning systems for enterprise use. This position focuses on applications such as document processing, anomaly detection, and intelligent automation, ensuring robust and efficient ML-driven solutions.

Key Responsibilities

• Identify and define machine learning problems, determine necessary data, and devise solution strategies.
• Construct dependable data pipelines, ensuring the preprocessing and quality control of data.
• Develop, train, assess, and refine machine learning and deep learning models.
• Deploy production-ready ML models and inference services that are scalable.
• Continuously monitor model performance, encompassing data and model drift.
• Implement MLOps workflows including continuous integration, continuous deployment, and model version control.
• Guarantee that ML solutions comply with security, privacy, governance, and regulatory standards.
• Enhance ML infrastructure for optimal efficiency, scalability, and cost-effectiveness.
• Integrate machine learning models with existing applications via RESTful APIs and enterprise systems.
• Document technical aspects including model cards, experiments, and deployment instructions.
• Collaborate cross-functionally with software engineers, data engineers, and IT teams to ensure smooth production integration.
• Seek and implement improvements in MLOps, model effectiveness, and operational workflows.

Qualifications and Experience

• Minimum of 5 years of hands-on experience in Machine Learning and Artificial Intelligence applications.
• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Data Engineering or related disciplines; a Master’s degree is preferred.
• Strong proficiency in Python programming.
• Experienced in using scikit-learn and TensorFlow or PyTorch frameworks.
• Skilled in SQL and managing data processing tasks.
• Competent in developing and assessing ML and DL models.
• Well-versed in building data pipelines and managing data quality.
• Experience working with MLOps best practices, including CI/CD, model deployment, and monitoring.
• Familiar with monitoring for model and data drift.
• Ability to deploy models with REST APIs.
• Knowledge of cloud ML platforms and infrastructure.

Preferred Qualifications

• Master’s or higher degree in AI, Computer Science, Data Science or related fields.
• Certification in Cloud Machine Learning technologies.
• Experience with document processing, natural language processing, computer vision, anomaly detection, or intelligent automation applications.