AI / Machine Learning Engineer

Function

We’re looking for an engineer to join our client’s team, responsible for implementing various technical components vital for a project delivery. This role requires close collaboration with both internal teams and external partners to ensure the robustness and efficiency of all components.

The successful candidate will engage in several key activities, including:

• Development of end-to-end data pipelines, focusing on document ingestion, extraction, and structured storage.
• Creation of embeddings, RAG indexes, and search logic to enhance the AI system performance.
• Implementation of integrations with cloud services, internal databases, and API layers.
• Collaboration with architects to align technical solutions with the overall strategy.
• Ensuring high code quality through rigorous testing, documentation, and performance enhancements.
• Providing support during testing phases and validating functional requirements.

The ideal candidate will possess a strong technical background complemented by a proactive mindset. Key qualifications include:

• Expertise in C#.NET for AI/ML data processing and backend development.
• Experience with various backend technologies, including C#, PHP, JavaScript, and both relational and non-relational databases.
• Understanding of AI algorithms, embeddings, and deployment strategies for AI components.
• Hands-on experience with cloud-based AI services, particularly Azure OpenAI, is highly valuable.
• Capability to adapt quickly to change and thrive in an Agile environment.
• Strong problem-solving skills and the ability to communicate effectively within cross-functional teams.

Besides technical expertise, our client values collaboration and responsibility. Candidates should be:

• Fluent in Dutch and have good proficiency in French, with English considered a strong plus.
• Autonomous, disciplined, and able to deliver results within stringent timelines.
• Familiar with Agile methodologies and iterative project frameworks, with knowledge of DevOps practices being advantageous.
• Willing to commit to a minimum of two days per week on-site presence.