Machine Learning Engineer

Mission context The Employee Assistant is looking for an Expert developer that can help structure the vision around our employee virtual assistant into a coherent technical implementation roadmap.

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.

Language requirements Dutch nice to have

French nice to have

English Mandatory

Education Master in Computer Science or related field/experience

Certification Certifications in linux, python, data science are a +

Telework Expectation: 50% on site & 50% homeworking

Required experience / knowledge At least 6 years of relevant experience

Technical experience mandatory

Containerization

AI platforms & IDEs

CI/CD

Code, model & data versioning

Cloud computing services

Relational databases

Swagger/Schema definition

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

Soft skills

Communication skills - oral & written

Ability to deliver/Results driven

Attention to detail/rigor

Creativity & Innovation/Problem Solving

Proactively invests time in continuous learning and knowledge improvement.

Demonstrates awareness of efficiency and efficacy.

Thinks out of the box outside existing processes and frameworks.

Works with energy and empowerment to deliver great results and a large contribution to the company’s success Is constructive by being open to the changes and to other’s opinions, ideas and feedback