AI Memory Architect & ML Systems Engineer

Rodrigo is a software engineer specializing in applied ML and scalable systems. He is particularly focused on solving the 'context window' problem using graph-based knowledge representations for information compression and long-term memory in AI agents. He develops pipelines integrating LLMs with structured memory for efficient knowledge generalization and recall. His expertise includes building persistent, graph-oriented systems for AI memory architectures, developing ML systems like TTS, semantic search, and RAG pipelines, and full-stack development bridging PyTorch models with production-ready Svelte/React interfaces on Linux/Postgres infrastructure. He is seeking roles contributing to advanced LLM integration with persistent memory and structured reasoning.