Location: Portugal
Remote: Yes
Willing to relocate: Yes
Technologies: Python, Deep Learning (PyTorch), NLP, Graph Knowledge Systems, Vector Search (Cosine Similarity), PostgreSQL, React/Svelte.
Résumé/CV: https://www.linkedin.com/in/rodrigo-heck-7280a218a/
Email: rodrigo.heck29@gmail.com
Hi HN, I’m Rodrigo. I’m a software engineer working at the intersection of applied ML and scalable systems. Lately, I’ve been obsessed with solving the "context window" problem through graph-based knowledge representations. My recent work focuses on treating graphs not just as data stores, but as a method for information compression and long-term memory permanence in AI agents. I develop pipelines that integrate LLMs with structured memory to allow for more efficient knowledge generalization and recall.
Key areas of expertise:
1. AI Memory Architectures: Building persistent, graph-oriented systems for reasoning and long-term retrieval.
2. ML Systems Engineering: Developing TTS systems, semantic search tools, and RAG pipelines that go beyond simple vector lookups.
3. Full-Stack Foundations: Bridging the gap between a PyTorch model and a production-ready Svelte/React interface, backed by robust Linux/Postgres infrastructure.
I’m looking for a role where I can contribute to the "Next Step" of LLM integration—moving past simple chat interfaces toward systems with true persistent memory and structured reasoning.