Assignment Description

Our client is seeking a Machine Learning Platform Engineer to join their platform development team. The ideal candidate will have a strong understanding of designing and building ML platforms in a multi-application and multi-model setup. They will focus on automation, traceability, monitoring, scalability, and reusability at both the model and data level.

What you’ll do:

• 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 irregular sampled data
• Take initiatives and work together with colleagues, Product Owners, and Architects to find the best solutions for the platform.

Who you are:

• 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.
• An interest and drive to understand the concepts of the energy system and the potential business value provided by the platform. And be able to understand what is good enough to provide that value.
• 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.