Expertise includes among others:

• Machine learning operations: Designed and developed complex MLOps systems including application deployment strategies, experiment trackers, model monitoring, packaging, versioning, and testing.
• Designing and building data platforms: Designed and developed cloud infrastructure via infrastructure as code and worked on multiple (big) data platforms serving multiple purposes: as fundament for machine learning use cases, as platform to combine data silo’s and as analytical backend serving transactional systems.
• Modeling: Built and deployed time series models for use cases like day ahead energy forecasting, order delivery forecasting, and product forecasting.

Background: 3+ years of experience working as machine learning engineer in online marketplaces and climate tech. MSc Operations Management (data intensive industries) from the Eindhoven University of Technology.

Why Enjins? “Making impact of machine learning solutions is not only about building a decent machine learning model. To make a real difference, an organisation needs to implement (and embrace) a complete solution. This ranges from application deployment strategies, data engineering, cloud infrastructure and data science to the way people are using and interpreting the results and interacting with the model. I enjoy working in teams and solving engineering heavy puzzles. Enjins provides the perfect balance between applying consultancy and engineering skills.”