Machine Learning Engineer

Role
: Machine Learning Engineer - Expert

Exp
: At least 6 yrs of relevant years

Location
: Brussels, Belgium

Language Requirement
: English - mandatory ; Dutch or French is a plus

Telework
: 50 % homework and 50 % onsite

Responsibilities:

You have experience in the building and deployment of
python micro-services
. Your role will be to ensure the boundaries between micro-services are correctly defined to allow different teams to work in parallel in the most efficient manner.

Your toolkit must contain knowledge of
swagger, mocking, and testing
and you are willing to share your knowledge with the other members of your chapter.

Machine Learning Engineers typically help data scientists promote the adoption of best standards in industrial code development across the ML&AI community. They do so by developing ML pipelines that are production-ready by design or by integrating existing ML solutions into industrial pipelines.

They participate in the development, deployment and monitoring of AI services, which means they contribute to data quality checks, data flow design, the design of the models themselves and their overall integration into the production environment.

ML Engineers are meant to facilitate the communication between AI & Analytics teams and IT production with regards to the deployment of ML models, ensuring that models put in production are equipped with the appropriate data pipelines and monitoring.

Function Description
:

ML Engineers contribute to Machine Learning projects by:

• Working with the Data Scientists to define and develop the target solution with production constraints in mind. This allows to select the correct run infrastructure and serving model (e.g. data ingestion scheme, API synchronicity, …) to address the business requirements (real-time responses, processing volumetry, …)
• Contributing to the
  automation of the different elements of the ML pipeline
  in order to integrate and deploy them in the production environment (e.g. building Docker/VM images, prepare unitary, regression and integration tests, …)
• Supporting Data Scientists on the usage of the existing
  industrial solutions available to build and monitor AI services
  (i.e. the CI/CD tools)
• Supporting IT Production on the parameterization of the target environment

Ensuring that the model runs without errors, is retrained if needed (incl. automatically) and is monitored both from the IT and the business perspective.

Certifications:

Certifications in linux, python, data science are a plus.

Technical experience mandatory
:

• Containerization
• AI platforms & IDEs
• CI/CD
• Code, model & data versioning
• Cloud computing services
• Relational databases
• Swagger/Schema definition

Technical experience preferable :

• IT language of their entity or project
• ML packages and libraries relevant to their entity or project
• Model compression techniques

Business experience mandatory
:

• Project Coordination