In August 2025, Loredo Rod implemented support for the ml.generate_embedding function in the BigQuery dialect of the sqlglot repository. This work involved designing a new parser path and a dedicated expression class, leveraging expertise in Abstract Syntax Trees and code parsing with Python and SQL. Loredo ensured robust integration by updating and expanding test coverage to validate the new functionality. The feature enables users to express machine learning embedding generation directly within BigQuery SQL, streamlining analytics workflows and enhancing dialect extensibility. The contribution demonstrated depth in parser and dialect extension, with a focus on maintainable, test-driven development and code quality.