WHO WE ARE

Artefact is a leading global consulting company dedicated to accelerating the adoption of data and AI to positively impact people and organizations. We specialize in data transformation and data marketing to drive tangible business results across the entire enterprise value chain.
Artefact offers the most comprehensive set of data-driven solutions per industry, built on deep data science and cutting-edge AI technologies, delivering AI projects at scale in all industry sectors. From strategy to operations, we offer an end-to-end approach and solutions: data strategy, data quality and governance, data platforms, AI Factory, data-driven customer experience and marketing ROI.
Our 1500+ employees operate in 20 countries (Europe, Asia, Americas, Middle East, Africa) and we partner with over 1000 clients, including some of the world’s top 300 brands such as Samsung, L’Oréal and Sanofi.
Artefact Benelux in Utrecht is looking for an ambitious Senior Machine Learning Engineering Consultant to strengthen our Data Engineering team.

WHAT WE ARE LOOKING FOR

We’re seeking someone who has:

• Fluency in English (mandatory); Dutch or French is a plus.
• A Master’s degree in a technical field.
• 3+ years of relevant experience (or equivalent), applying Machine Learning to business problems.
• Excellent Python programming skills with a focus on production-grade code.
• Strong experience with SQL, pipelines, and databases.
• Hands-on experience with ML Ops and deploying models to production environments.
• Familiarity with cloud platforms such as Azure, GCP, Databricks, or AWS (Professional Certification is a plus).
• Strong communication skills to explain complex technical concepts to various stakeholders.
• A deep understanding of machine learning fundamentals, neural network architectures, and modern AI frameworks.

As a Senior Machine Learning Engineer Consultant, you will be responsible for:

• Developing production-grade machine learning code, including models, features, and pipelines, ensuring scalability, real-time processing, monitoring, and retraining.
• Writing clean, readable, and reusable code while selecting the right technologies and coding methodologies based on business needs and tools.
• Collaborating with consultants, data scientists, analysts, and engineers to identify client needs and design end-to-end data solutions that drive business value.
• Communicating clearly with stakeholders.
• Continuously refining your expertise and staying up to date with the latest technologies.
• Mentoring team members on ML best practices and fostering technical excellence.