We are looking for a Senior Machine Learning Engineer to help evolve a globally deployed recommender system delivering business value across multiple markets. This role focuses on strengthening the MLOps foundation, improving system architecture and supporting production-grade ML model deployment.

You will work at the intersection of machine learning engineering, data engineering and cloud infrastructure, collaborating closely with data scientists, product managers and business stakeholders.

• Lead architectural evolution of a production recommender system
• Design and implement MLOps practices and CI/CD pipelines in GitLab
• Productionize machine learning models using AWS SageMaker
• Implement experiment tracking and model lifecycle management using MLflow
• Develop Python code for ML infrastructure and deployment pipelines
• Mentor data scientists and engineers on scalable ML system design
• Improve monitoring, reliability and performance of ML services

• 5+ years of experience in Machine Learning Engineering or MLOps
• Strong Python programming skills and experience with ML ecosystems
• Experience deploying models on AWS SageMaker
• Experience with MLflow and GitLab CI/CD
• Experience designing scalable ML or data pipelines in cloud environments
• Hands-on experience with TensorFlow or PyTorch
• Strong system design and communication skills

• MSc or PhD in Machine Learning, AI, Computer Science or similar field
• Experience with monitoring tools such as Prometheus, Grafana or Evidently AI
• Experience working with recommender systems or marketing analytics platforms