Quintin Fettes is an AI research scientist in Menlo Park with nine years of experience advancing post-training and alignment for frontier LLMs and multimodal models across Meta’s Reality Labs and Superintelligence Labs. He drives end-to-end solutions—from synthetic data flywheels and novel SFT/RLHF/reward-modeling techniques to production-grade evaluations for long-form factuality, tool-use, and video understanding. Quintin has led cross-team technical direction on token-level tool protocols and built auto-judges and preference-aware reward architectures that bridge research prototypes to regular model releases. His PhD work applied reinforcement learning to computer architecture, a thread that surfaces in his unusual combination of low-level RL expertise and large-scale generative model alignment. Notably, he shipped an ads Variance Reduction System in production that protected billions in revenue, demonstrating rare product-impact at scale alongside deep research contributions. He publishes and maintains an academic footprint (Google Scholar) while translating cutting-edge evaluation and post-training methods into deployable systems.
9 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Electrical Engineering and Computer Science, Doctor of Philosophy - PhD, Electrical Engineering and Computer Science at Ohio University
Contributions:144 commits, 125 pushes, 2 branches in 3 years
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Quintin Fettes - Senior Research Scientist (Generative AI)