Design, build, and maintain ML infrastructure and tooling to support the full ML lifecycle (data preparation, training, evaluation, deployment, monitoring, and retraining).
Lead a team of young and bright MLOps Engineers in conducting research, design, and prototype MLOps practices, tools, and frameworks to expedite the machine learning lifecycle at MoneyLion.
For large-model training and evaluation scenarios, participate in formulating and continuously iterating data quality standards, judgment rules, and acceptance criteria.
Own and extend the identity / firmographic and financial layers of the ICP Profile Schema, working from Companies House API data and the Data Platform.
Own and extend the identity / firmographic and financial layers of the ICP Profile Schema, working from Companies House API data and the Data Platform.
For large-model training and evaluation scenarios, participate in formulating and continuously iterating data quality standards, judgment rules, and acceptance criteria.
Design, build, and maintain MLOps pipelines for training, testing, deploying, and monitoring AI/ML models in production, ensuring stable, reliable, and scalable performance.
Lead a team of young and bright MLOps Engineers in conducting research, design, and prototype MLOps practices, tools, and frameworks to expedite the machine learning lifecycle at MoneyLion.
For large-model training and evaluation scenarios, participate in formulating and continuously iterating data quality standards, judgment rules, and acceptance criteria.
For large-model training and evaluation scenarios, participate in formulating and continuously iterating data quality standards, judgment rules, and acceptance criteria.