Mauricio Rubio Rodríguez

I am a machine learning engineer with 4+ years focused on LLM optimization, fine-tuning, and deploying models to production. I deliver measurable improvements in cost and latency through efficient inference pipelines and model optimization.

I've architected and deployed multi-agent LLM systems and production inference pipelines, fine-tuning models such as GPT-4o and integrating APIs (GPT-4/Claude/Gemini) with custom RAG solutions. I curated and validated 10K+ training examples and built evaluation frameworks combining automated testing with human-in-the-loop QA.

My MLOps and data engineering experience includes dataset curation at scale, data cleaning/annotation pipelines, dataset/model versioning, monitoring dashboards, and containerized deployment practices. I achieved an 85% cost reduction and 75% latency improvement through optimization and caching strategies.

I am a fast learner and strong communicator who translates product requirements into technical ML specifications, collaborates across cross-functional teams, and is eager to deepen expertise in model compression, distributed training, and next-generation AI systems.