Summary
Emily Mcmilin is a research scientist based in Menlo Park with eight years of experience bridging applied hardware engineering and machine learning research. She moved from designing antennas for Apple products to advancing generative AI for developer productivity as a senior researcher on Meta's PyTorch team. Her independent research on offline RL, causal inference, and selection biases in large language models has been presented at NeurIPS, ICML workshops, and UAI venues, reflecting a strong track record in causality and NLP. Emily also serves as a technical editor and frequent invited speaker, combining rigorous academic training (PhD in Electrical Engineering, BS in Symbolic Systems) with production-focused engineering. Colleagues describe her as a curious generalist who surfaces subtle dataset and selection issues that can silently undermine generative model behavior.
8 years of coding experience
13 years of employment as a software developer
Master of Applied Science, Electrical and Computer Engineering, Master of Applied Science, Electrical and Computer Engineering at University of Victoria
Bachelor of Science, Symbolic Systems, Bachelor of Science, Symbolic Systems at Stanford University