Summary
Antonio Guillen-perez is a Senior Machine Learning Engineer in the San Francisco Bay Area with a Ph.D. and a decade of experience applying RL, generative models, and scalable ML systems to autonomous systems and robotics. At Uber AV Labs he focuses on mining long-tail, high-value edge cases from petabyte-scale driving logs using foundation models, flow matching, and vision-language approaches to improve AV safety. Previously at HPE AI Labs he co-designed open-source simulation environments for MARL and built distributed RL infrastructure that scaled to hundreds of workers, earning a NeurIPS workshop award and contributing a patent. His academic work blends telecommunications, multi-agent RL, and 5G-enabled vehicle coordination, and he has applied deep learning to biomedical signal detection with published results. Known for bridging rigorous research with production-grade systems, he’s particularly adept at turning complex simulations and rare-event data into robust, deployable models.
10 years of coding experience
Bachelor's Degree in Telecommunications Systems Engineering, Electronics and communication systems, 2.12, Bachelor's Degree in Telecommunications Systems Engineering, Electronics and communication systems, 2.12 at Polytechnic University of Cartagena
Bachelor, Science and Technologies, 8.53, Bachelor, Science and Technologies, 8.53 at IES Dr. Pedro Guillén (Archena -Murcia)
English, Spanish