Machine Learning Engineer

As a collaborator in the Machine Learning team, you ensure the different predictive models and algorithms are running qualitatively and on time in the production environment also called the model factory. The mission of the machine learning engineer is key because this role makes the bridge between the products delivered by the Data Science team and the usage of the business.

The machine learning engineer will also cover some more technical missions as for example web scraping, POC’s concerning AI & Generative AI (in order to ensure a move to production for those POC’s).

The Machine Learning team is responsible for the quality of the models and as a consequence of the value created by the models that will be used by all the internal clients.

Your responsibilities:

• Deploy large scale machine learning models and other scripts into production environment (in cloud and on-premise environments)
• Review, optimize and simplify the code to ensure quality and reusability
• Monitor the quality of input variables and the performances of the models’ outputs.
• Contribute to parts of the ML pipeline, such as data preprocessing, feature selection, and model evaluation.
• Collaborate with data scientists, software engineers, and product teams to integrate models into production.
• Monitor model performance and updates models as needed
• Solve well-defined machine learning problems and may work on smaller projects or parts of larger projects.
• Apply existing algorithms and techniques to specific business problems

Specific expertise:

• Expert understanding of git, experience with CI/CD pipelines;
• Proficiency at Python and solid knowledge of at least one deep learning framework such as TensorFlow / Keras or PyTorch is a must.
• Good knowledge of computational infrastructure;
• Basic knowledge of Terraform;
• Knowledge of machine learning techniques, general deep learning, predictive modelling and Generative AI in order to be able to challenge the inputs and the outputs produced by the Data Science team
• Understanding of Google Cloud Platform, ML Ops principles and software development tools/best practices;
• Expertise in Data Ingestion / Processing and Modelling: you are able to express complex data needs and understand data quality-cleansing processes & methods
• Extensive Corporate Data Knowledge: aware of critical company business processes and underlying data, you are able to challenge data quality
• Fluency in SQL for writing efficient queries on large datasets
• Good knowledge of Linux operating system
• Ability to write robust code in Python, R and Java
• Good to have: good knowledge of networking, multiprocessing, parallel computing and real-time computations;
• Should be able to challenge the inputs and outputs of AI and Gen AI products as well as the way it was built.

Your profile:

• Master's degree in a related field (e.g., Computer Science, Data Science, Mathematics) or equivalent work experience. with 2-5 years of experience in machine learning or related fields
• Proficient in key machine learning tools and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Analytical thinking and self-learning spirit
• Strong programming and data analytics skills
• Able to work and collaborate transversally
• Good communication and presentation skills (vulgarisation)
• Collaboration skills (with other data scientists, data engineers and other teams)
• Capacity to influence and engage, assertiveness and being diplomatic
• Customer-oriented and pragmatic
• Stress resistant
• Fluent English and fluent French or Dutch

Our offer:

You will make the difference in this highly innovative vibe. As a result, you will develop your full potential by working with highly skilled colleagues and through continuous training. Moreover, you can count on a highly competitive and versatile compensation (market competitive salary, company car or legal mobility budget, homeworking and net allowance, performance bonus, meal vouchers) and benefits package.

Inspired? Please send us your resume and we will rapidly get back to you to invite you for further interviews.