Machine Learning Engineer, Digital Experience

📋 Description

• Productionization: Take models from prototype to production, building reliable, scalable pipelines
• Data & ML Infrastructure: Design and maintain data pipelines, feature stores, and workflow
• Monitoring & Reliability: Build monitoring for model performance, data drift, and pipeline
• Model Development: Build and validate machine learning models and statistical approaches when
• Cross-Functional Collaboration: Work with Data Scientists, Data Engineers, and Software Engineers
• We are primarily an in-office environment and therefore, you will be expected to work from the

🎯 Requirements

• Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Engineering, Statistics, or a
• 3-5 years of industry experience in data engineering, ML engineering, or a hybrid data
• Strong software engineering fundamentals in Python and SQL, including writing production-quality
• Hands-on experience with a workflow orchestration tool, such as Airflow or Dagster.
• Experience working in a cloud-native environment (AWS, GCP, or Azure).
• Working knowledge of machine learning and statistical modeling, with familiarity with a library