Senior AI Engineer

Description

You join the Data & AI team, a mix of data engineering, architecture, AI, analytics, governance and visualisation specialists who help clients get more from their data.

The team covers everything from data foundations to dashboards, analytics and AI use cases that support better decisions.

The role is about designing, building and industrialising AI solutions that address specific business problems and run in live operational settings.

Work spans traditional AI and generative AI, including machine learning models, NLP, LLMs, semantic search, RAG and conversational AI, delivered for clients.

Some projects start from nothing, while others involve running and improving an existing solution over the medium to long term.

You work alongside Data Scientists, MLOps Engineers, Data Engineers and AI Architects to bring all parts of a solution together.

The team is a Data Science and AI Engineering practice that takes AI ideas to practical, scalable and responsible solutions, and people share knowledge and learn from each other.

Responsibilities

• Train, fine-tune, improve and deploy ML and AI models.
• Write production-ready Python code to serve online, batch and real-time models.
• Build applications and software components that make AI use cases work in practice.
• Work with other specialists to integrate all parts of the solution.

Requirements

• Strong AI knowledge combined with solid software engineering skills, with the ability to turn AI use cases into reliable, maintainable, production-ready solutions.
• At least 4 years of experience as a Machine Learning Engineer, Data Scientist, MLOps Engineer or in a similar role.
• Experience with traditional NLP, LLMs and conversational AI, in both experimentation and production.
• Experience with vector databases for semantic search and RAG in production.
• Strong Python background with production-ready code.
• Experience with experiment tracking, model monitoring, LLM and NLP evaluation, and deployment strategies.
• Comfortable with the machine learning lifecycle and MLOps and DevOps principles.
• Experience with at least one cloud provider and good knowledge of the data ecosystem.
• Able to coach others, give technical direction and work independently.
• Master's or PhD in Machine Learning, Artificial Intelligence, Computer Engineering or a related field.
• Proficient in English, and fluent in Dutch and/or French.

Conditions

Location, work model and schedule are not specified in the posting.

Benefits

• Perks include mobility options (including a company car), insurance coverage, meal vouchers, eco-cheques and more.
• Continuous learning through the company Academy.
• Career development opportunities locally and internationally, with the option to grow internally.
• Team events for connecting with colleagues.