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Responsibilities
- Coach data scientists to move models from experiment to production — packaging, reproducibility, CI/CD
- Design and build data and inference pipelines
- Implement MLOps best practices: containers, model registry, experiment tracking, rollback strategies
- Set up observability layers — logs, metrics, traces, drift detection, SLOs
- Apply compliance-by-design principles aligned with security, risk frameworks, and the EU AI Act
- Take technical lead on agentic solutions built on Azure AI Foundry and Copilot Studio
- Build integrations with internal systems via function calling, RAG, and orchestration
- Set up evaluation frameworks: test suites, red teaming, versioning
- Implement orchestration patterns — planning, retries, fallbacks
- Maintain selective autonomy and human-in-the-loop design principles
- Own and manage the technical backlog within an agile team
- Write technical documentation and runbooks
- Challenge designs, collaborate with partners, and ensure integration fits target architecture
- 3–5+ years as an AI / ML / MLOps engineer, with clear production-grade delivery
- Strong Python skills — this is a hands-on role
- Hands-on experience with agentic frameworks, function calling, and RAG
- Deep knowledge of AIOps/MLOps tooling: Azure DevOps, CI/CD, Docker, Terraform (IaC)
- Working knowledge of Azure ML, Azure OpenAI / AI Foundry, Azure AI Search
- Solid understanding of security and governance: RBAC, secrets management, network segmentation, privacy
- Master's degree in CS, AI, Engineering, or equivalent demonstrated experience
- You are fluent in Dutch, and have a very good level of English
- Certifications: AZ-900, AZ-204, DP-700, PL-300, ISTQB CTFL (none strictly required)
- Insurance or financial services domain knowledge
- Location: Hybrid — minimum 2 days/week on-site in Antwerp
- Contract: Freelance or Permanent
- Duration: 12 months, extension possible
- Start: ASAP
- Own device required
Key Skills
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