Stacey Svetlichnaya is an Alignment Data Scientist and seasoned AI ecosystem engineer with 14 years of experience building production ML systems, developer tools, and research workflows that bridge deep learning, interpretability, and collective decision-making. She helped found and ship core features at Weights & Biases, led early AI-augmented image search and aesthetic modeling at Flickr, and has stewarded open-source AI research and tools as CTO of the AI Objectives Institute. Currently focused on AI alignment and sustainability, Stacey combines rigorous experiment pipelines and visualization-driven interpretability with practical productization across academia and industry. She’s comfortable moving between research labs and production code, and brings a rare blend of systems engineering, user-facing tooling, and long-term safety thinking informed by Symbolic Systems training from Stanford.
14 years of coding experience
12 years of employment as a software developer
M.S Symbolic Systems, M.S Symbolic Systems at Stanford University
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