Senior Machine Learning Engineer

📋 Description

• Drive and continuously improve MLOps practices across the machine learning environment.
• Build, optimize, and maintain CI/CD pipelines using GitLab to automate reliable ML delivery.
• Implement and maintain experiment tracking and model management workflows using MLflow.
• Productionize, deploy, and maintain machine learning models using AWS, with a strong focus on
• Design, build, and maintain scalable machine learning and data pipelines.
• Develop and maintain robust Python-based ML and data infrastructure.

🎯 Requirements

• 5+ years of professional experience in Machine Learning Engineering or a closely related field.
• Strong hands-on experience deploying, operating, and maintaining production machine learning
• Expert-level Python skills and strong knowledge of the broader data science and machine learning
• Hands-on experience with AWS cloud services, preferably including AWS SageMaker.
• Strong understanding of MLOps principles, practices, tooling, and the machine learning lifecycle.
• Practical experience with MLflow for experiment tracking and model management.

🎁 Benefits

• B2B contract arrangement.
• Opportunity to work on technically challenging machine learning projects with mature engineering
• Exposure to modern ML technologies, AWS infrastructure, MLOps tooling, and enterprise-scale systems.
• Opportunity to contribute to a globally deployed recommender system and production ML platform.
• Collaborative and supportive environment focused on knowledge sharing and professional development.
• Opportunity to provide technical mentorship and influence engineering practices across