Research and deploy ML models that identify content by combining multimodal LLM understanding, uncertainty estimation, and causal modeling to maximize exploration ROI at scale. Drive projects from problem formulation and experimentation design through model training, real-time serving architecture, and production launches, collaborating closely with Feed Ranking, Content, and Infra teams. Partner to align semantic applicant retrieval, ranking incentives, and warm-start handoffs so promising new content seamlessly activates the organic recommendation flywheel.
Lead zero-history discovery for Discover’s top formats—making dynamically generated AI content (AIGC) a citizen across the stack and surfacing breaking news within minutes of publication. Evolve StarSearch into the intelligent gatekeeper for Discover’s content ecosystem—safely bootstrapping fresh, niche, and creator supply to expand personalization headroom while rapidly pruning unengaged content to keep the serving corpus fresh and efficient.
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