Applied ML QA Engineer

We are seeking an experienced Applied ML QA Engineer (Contractor) to validate machine learning models, scoring outputs, feature pipelines, and inference services for a real-time decisioning platform.

This role involves creating automated tests, implementing drift monitoring, performing consistency checks, and providing validation support for every model release.

• Validate ML models, scoring outputs, and feature pipelines for accuracy and reliability.
• Develop and maintain automated test frameworks for ML workflows.
• Perform consistency checks across training, validation, and inference environments.
• Collaborate with data scientists and engineers to ensure robust model deployment.
• Maintain documentation and validation artifacts for compliance and reproducibility.

• 8+ years of experience in Python, ML QA, drift detection, and testing ML features/pipelines.
• 5+ years of experience with Databricks, feature stores, and model serving (preferred).
• 5+ years of experience using GenAI tools (Cursor, Windsurf, Copilot).
• Strong understanding of ML lifecycle, including testing and monitoring.
• Familiarity with CI/CD workflows for ML deployments.

• Experience with real-time decisioning platforms.
• Knowledge of ML observability tools and QA best practices.
• Strong analytical and problem-solving skills.