ML Ops Engineer ID38029 – $3,000 Sign-On Bonus

3+ years in MLOps, ML Engineering, Data Engineering or related roles 5+ years of experience using Python Proficient in using Databricks (2-3 years) Proficient in Apache Spark, ML Flow, Unity Catalog, and feature stores Familiarity with ML lifecycle tools such as MLflow, Kubeflow, and Airflow Strong knowledge of Git workflows, CI/CD practices, and tools like GitLab or similar Strong understanding of model performance monitoring, drift detection, and retraining workflows Upper-Intermediate English level

Build and maintain scalable ML infrastructure on Databricks Design and implement frameworks for detecting data and model drift Develop model calibration frameworks and establish versioning practices Design and optimize reinforcement learning (RL) orchestration pipelines Create automated frameworks for training, retraining, and validating ML models Implement CI/CD best practices for ML models Work closely with ML Scientists to ship, deploy, and maintain models Build tools for model performance monitoring, operational analytics, and drift mitigation