Collaborate with cross-functional teams: Partner with data scientists, data managers, analysts, infrastructure engineers, and peer AI Engineers to develop, integrate, and scale new algorithmic products

Evaluate new models and technology: Engage in proof of concepts and experiments to assess the efficiency of new models and technologies

Ensure code quality: Develop high-quality, standard-compliant, and tested code, and refactor code as necessary

Contribute to code and tool libraries: Contribute code and tools to central re-usable libraries and repositories for enhanced efficiency and collaboration

Develop data models and pipelines: Design data models, model features, data quality tests, ETL/ELT pipelines, and distributed compu...