After the successful launch of our revolutionary Petcare Platform this year, we're embarking on an exciting journey to blend real-time event data with curated historic datasets. This initiative aims to train and deploy machine learning models in a live environment, revolutionizing how consumers interact with our products and services. We're seeking talented MLOps Engineers to join our Engineering team and collaborate closely with our Data Science division to build self-serve orchestration systems for model training, evaluation, and hosting in a multi-cloud environment.
Role Overview:
As an MLOps Engineer, your role will center on the robust deployment, monitoring, and maintenance of machine learning models within our Google Cloud Platform (GCP) and Microsoft Azure environments. You will play a crucial part in ensuring our models deliver value efficiently and reliably. While closely collaborating with Data Science, the emphasis of this role is on enabling model deployment through self-serve orchestration, automated testing, data transfer, and lightweight endpoint hosting. Although this position is focused on MLOps, there will be opportunities to contribute to and upskill in predictive modeling and advanced analytics.
Key Responsibilities:
* Oversee the deployment, monitoring, and maintenance of machine learning models within GCP and Azure environments.
1. Enhance model de...