ML Engineer

Job Location: Belgium
Job Category: Data
Job Type: Full Time

Mission context

A data science squad consists of a small group of people combining the required skills to design, build and test AI-enabled solutions within a limited timeframe.
As a member of the data science team, the ML engineer applies his knowledge of software development best practices to help data scientist delvier fully operationable solutions. Included, you set-up the necessary monitoring to guarantee that the solution can be monitored.
Collaboration with data scientist and IT Ops engineers enables you to make sure that solutions are built first time right and can be deployed.

Function description

The ML Engineer commits to helping the team meet the code quality and testing standards expected to be able to serve AI models in production. He is responsible for helping reduce the application footprint, guarantee resilience, and setup monitoring of the solution. 

The focus is on the completion of the sprint backlog, containing all elements that the team must deliver and of which the sequence has been determined by the Product Owner based on the added value for the (internal or external) client.

The ML Engineer adheres to the scrum values (focussed, committed, open, respectful, and courageous) and is able to closely collaborate with the team members. Knowledge sharing, open communication, continuous learning and commitment to deliver added value are key.

Required experience/knowledge

  • knowledge of Python development and packaging
  • excellent understanding of architecture (hardware, OS, networking, databases, middleware)
  • knowledge of code quality standards and security procedures as well as development tools
  • experience with integration using different technologies (distributes/mainframe) and infra components
  • knowledge of agile methodology

Soft skills

  • excellent analysis skills
  • efficient communication skills
  • ambitious towards the targets of his/her squad
  • agile values: focussed, committed, open, respectful, courageous
  • promote continuous improvement (market evolutions, working methods, …) to improve the delivery speed of software and hardware, and to improve operational quality