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.

Senior MLOps Engineer with AWS

Your responsibilities

• 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

Our requirements

• 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