Databricks Engineer with AI/ML

Role & responsibilities

Strong Databricks platform skills for end-to-end execution (Databricks used for query/processing and supports AI/ML capabilities in the target-state architecture).
PySpark / Spark foundations for feature engineering / dataset preparation.
Familiarity with Databricks capabilities noted in your internal material: AI & ML, Gen AI, NLP, plus platform elements like Spark/Photon and monitoring.
Comfort operating in a governed environment (Unity Catalog for centralized governance, auditing/lineage).
Practical ML lifecycle skills (feature engineering, evaluation discipline, reproducible experimentation) and ability to productionize simple models/POCs on the platform.
Demonstrated experience delivering AI/ML workloads on a data platform (Databricks preferred).