Vincent Claes is a Data and MLOps Engineer with 11 years of experience building production-ready ML and data platforms, currently accelerating AI teams at miDiagnostics while consulting as an LLMOps Engineer and AI Solutions Architect. He designs end-to-end AI products and infrastructure on AWS—spanning data lakes, model training, inference, RAG applications and prompt/LLMOps—combining a product mindset with Infrastructure as Code and CI/CD best practices. Vincent repeatedly helps startups and enterprises move research into reliable deployments, having optimized document-processing, semantic search, and audio/vision ML pipelines using tools like Sagemaker, Step Functions, Terraform, DuckDB and Hugging Face. He pairs hands-on implementation (from Jupyter workspaces to EKS and serverless inference) with stakeholder-facing activities: discovery, SOW drafting, delivery and hiring. Notably, he balances deep engineering work with practical guidance for teams on prompt engineering and monitoring ML systems in production. Based in Leuven, Belgium, he shares learnings publicly (GitHub, Medium, StackOverflow) and schedules calls to help tackle complex AI challenges.
Contributions:17 commits, 1 PR, 14 pushes in 1 year 4 months
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