Machine Learning Engineer II

What you'll do

• Translate business requirements into durable data models and segmentation frameworks for product teams.
• Build scalable data preparation, feature engineering pipelines, and production-grade data services.
• Develop and deploy predictive, recommendation, and clustering models using various machine learning techniques.
• Create and manage MLOps pipelines covering training, versioning, deployment, and model monitoring.
• Design and evolve data platform architectures leveraging Azure Data Fabric capabilities.
• Build APIs to expose model predictions to web, mobile, CRM, and other enterprise applications.
• Ensure all data products comply with privacy, security, and regulatory requirements.
• Perform code reviews and participate in architectural design discussions for the data platform.

What we're looking for

• Bachelor's degree in Computer Science, Engineering, Data Science, or equivalent experience.
• 3+ years of hands-on experience in data platform, analytics engineering, or backend engineering roles.
• Strong programming experience with Python and common data and machine learning libraries.
• Experience developing production machine learning models using frameworks like scikit-learn, PyTorch, TensorFlow, or XGBoost.
• Strong SQL skills and experience working with large enterprise datasets.
• Practical understanding of MLOps, including experiment tracking, model versioning, CI/CD, and monitoring.
• Experience designing and deploying training, evaluation, and inference pipelines in production environments.
• Authorized to work.