Andrés Marafioti leads the Multimodal Research Team at Hugging Face, where he develops efficient, open, and accessible AI systems. He holds a PhD in applied machine learning, with a focus on generative models for speech and music.
At Hugging Face, Andrés drives cutting-edge research in multimodal and memory-efficient models. He led the development of SmolVLM, the world’s smallest family of vision-language models, and co-created SmolDocling, a powerful document-understanding model in collaboration with IBM. His recent work expands into robotics, building open-source models that enable robots to follow natural language instructions.
He's also a main contributor to several impactful open-source libraries, including NanoVLM and Speech-to-Speech, reflecting his commitment to reproducible, community-driven AI development.
