Been working as an MLE for the last 5 years and as another comment said most of the work is close to SWE. Depending on the stage of the project I'm working on,

Been working as an MLE for the last 5 years and as another comment said most of the work is close to SWE. Depending on the stage of the project I'm working on, day-to-day work varies but it's along the lines of one of these: - Collaboration with stakeholders & TPMs and analyzing data to develop hypotheses to solve business problems with high priority - Framing business problems as ML problems and creating suitable metrics for ML models and business problems - Building PoCs and prototypes to validate the technical feasibility of the new features and ideas - Creating design docs for architecture and technical decisions - Collaborating with the platform teams to set up and maintain the data pipelines based on the needs of new and exiting ML projects - Building, deploying, and maintaining ML microservices for inference - Writing design docs for running A/B tests and performing post-test analyses - Setting up pipelines for retraining of ML models