ASSIGNMENT DESCRIPTION

• Strong understanding of designing and building ML platforms in a multi-application and multi-model setup with focus on automation, traceability, monitoring, scalability, and reusability at both the model and data level.
• Preferably, the candidate has an interest to understand concepts of energy systems and potential business value provided by the platform.
• Support in designing and building an ML platform that delivers both multiple applications as well as multiple models per application, with a focus on automation, traceability, monitoring, scalability, and reusability.
• Support data scientists to reduce the time from idea and exploration to testing by building a collaborative platform.
• Managing and serving data in a validated and usable format from IoT sources with irregularly sampled data.
• Take initiatives and work together with colleagues, Product Owners, and Architects to find the best solutions for the platform.

REQUIREMENTS

• Proven experience in designing and building ML platforms.
• Fluent in Python and experience in pyspark.
• Experience with Azure services such as Azure ML, Azure blob storage, Event hubs, Azure Data Factory, Azure DevOps, Azure Data Explorer, Azure Databricks, Kusto Query Language.
• Understanding of applied MLOps and the complexity of managing data from IoT sources.
• Excellent collaboration skills to support data scientists and reduce the time from idea and exploration to PoC/MVP.
• Knowledge and experience of concepts such as lambda architecture, medallion architecture, feature stores, event sampled data, MLOps, CRISP-DM, edge compute, deploy code vs deploy model, CI/CD, common data platform patterns.

Please refer the Job description for details