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 systems
• 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