James Fox is a Machine Learning Engineer with 11 years of experience building large-scale recommender and search systems, currently applying those skills to messaging at Meta. He holds a Ph.D. in Computational Science and Engineering from Georgia Tech and a CS degree from UC Berkeley, combining deep academic research in computer vision, graph methods, and model robustness with production ML at scale. His research internships at Sandia and national labs produced publications on rotation-robust 3D point-cloud embeddings, sample-efficient models for materials discovery, and GNN robustness—work that underpins his practical focus on reliable, efficient models. Comfortable across the full ML lifecycle, he has engineered high-performance scientific workflows on supercomputers and optimized backend systems for latency and resiliency. Based in Atlanta, he blends rigorous experimental methodology with hands-on deployment experience to drive measurable improvements in search and recommendation quality.
11 years of coding experience
6 years of employment as a software developer
Bachelor's Degree, Computer Science, Bachelor's Degree, Computer Science at University of California, Berkeley
Doctor of Philosophy (Ph.D.), Computational Science and Engineering, Doctor of Philosophy (Ph.D.), Computational Science and Engineering at Georgia Institute of Technology
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