We are seeking an experienced MLOps engineer or team to design, develop, and deploy a robust and scalable MLOps framework on Microsoft Azure. This initiative is crucial for enabling seamless end-to-end model deployment, comprehensive monitoring, and efficient lifecycle management for several artificial intelligence models currently in their experimentation phase.
The successful freelancer will collaborate closely with our existing Data Science and DevOps teams. Key responsibilities include:
Design and implementation of a production-ready ai/ml pipeline.
Integration and utilization of various Azure services, such as Azure Machine Learning, Azure Functions, and Azure Kubernetes Service (AKS), to build a resilient and automated MLOps infrastructure.
Ensuring the framework supports continuous integration and continuous delivery (ci/cd) for machine learning models.
Establishing robust monitoring, logging, and alerting mechanisms for deployed models.
Implementing version control and governance strategies for model artifacts and pipelines.
We are looking for a professional with deep expertise in MLOps principles, cloud architecture (specifically Azure), and a strong understanding of machine learning workflows in a production environment.
https://freelancerdb.com
Delivery term: Not specified