Machine Learning Engineer

Job Summary

Working remotely as a full-time Machine Learning Engineer, the candidate will manage the entire model lifecycle on AWS SageMaker using Python, focusing on data exploration, model training and validation, deployment, and monitoring to enhance educational assessment solutions.

Key responsibilities

• Explore data thoroughly before and after model fitting, documenting findings for team review
• Train and validate models using SageMaker, ensuring rigorous tracking of experiments and parameters
• Deploy and monitor model versions, maintaining quality through dashboards and alerts for prediction performance

Required qualifications

• A Master's or PhD in a quantitative field, with three or more years of relevant experience or a doctorate with practical experience
• Proficiency in Python, with a strong foundation in CI/CD practices, testing, and infrastructure as code
• Solid understanding of statistics and exploratory data analysis, with the ability to communicate findings effectively
• Experience with AWS services, particularly SageMaker, and familiarity with experiment tracking tools like MLflow
• Demonstrated ability to build and ship models or ML systems that meet production standards