Senior Machine Learning Engineer

Support the Databricks-native (i.e., Databricks Workflows, Delta Live Tables, Databricks Asset Bundles, Unity Catalog, etc.) machine learning and AI platform. In this role you will operationalize production-grade machine learning and AI models, manage deployments, and ensure robust monitoring and governance. In addition to solid technical skills, this role requires strong communication across functions, including data scientists, data engineers, and product managers; ability to drive clarity from requirements; and active participation and sense of ownership of end-to-end design, implementation, and testing of complex ML and AI workflows in a collaborative team environment. Manage and support ML and AI model lifecycle using Databricks and MLflow: training, tracking, packaging, deployment, monitoring, agentic AI safety and generative AI guardrails. Automate and optimize model deployment pipelines for batch and real-time use cases. Collaborate with data scientists to productionize models, ensuring scalability, reproducibility, and reliability. Implement CI/CD pipelines for ML and AI workflows, including testing, version control, and rollback strategies. Monitor deployed models for performance drift, data quality, and SLA adherence. Support governance and compliance requirements: model registry usage, auditability, reproducibility). Troubleshoot and resolve issues related to model training, deployment, and integration with downstream systems. Provide operational support for Databricks Workflows, Jobs, and Delta Lake integration. Document processes, automation frameworks, and operational runbooks. Bring best practices to bear on the team’s products and educate the team members.