Felipe Frujeri is an AI researcher and former software engineer with 11 years of experience building foundation models, embodied agents, and production ML systems across NVIDIA, Microsoft, and Vatic Labs. His recent research focuses on decision-making agents, RL fine-tuning of LLMs, AI alignment, and cognitive architectures that augment LLMs with prefrontal-cortex–like control and external memory for multimodal skill learning. He has bridged research and engineering on “self-driving datacenter” scenarios and production ML inference platforms, and earlier work applied deep RL to database configuration and resource management at Azure. Felipe combines a strong systems pedigree—from high-performance computing and cloud efficiency to agentic workflows for quantitative finance—with graduate training in computer vision and machine learning from École Polytechnique. Colleagues value his rare mix of hands-on system design and theoretical curiosity about embodiment and reasoning in agents.
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