Rene User

I am a Senior AI/ML Engineer with 10+ years building end-to-end machine learning systems, distributed data pipelines, and production AI services across FinTech, healthcare, and enterprise software. I design scalable ML infrastructure using PySpark, Databricks, Docker, and Kubernetes on AWS, Azure, and GCP to support large datasets and high-throughput workloads.

I specialize in Generative AI and LLM-powered systems, including RAG pipelines, LangChain, embeddings, vector search, and agentic workflows, and have improved latency by ~40% and reduced infrastructure costs by ~25% while supporting platforms serving millions of users. I manage the full ML lifecycle with MLflow, automated retraining, drift detection, and explainability techniques such as SHAP to increase model transparency.

I collaborate in Agile/Scrum environments with cross-functional teams to deliver secure, production-grade AI services, integrating ML into enterprise ecosystems via REST APIs and service interfaces, and applying secure-by-default deployment practices including IAM/RBAC and encrypted storage.