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.
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
requirements-expected :
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
