Runze Su
Staff Machine Learning Engineer at Pinterest | LLMs for Rec & Ads Ranking | Scaling Laws | Long-Sequence Transformers
- Role
- Staff Machine Learning Engineer at Pinterest
- Location
- Santa Clara, CA, US
- LinkedIn followers
- 500 followers
About Runze Su
Machine Learning Engineer at Pinterest
Experience
Staff Machine Learning Engineer
Mar 2026 — Present · Palo Alto, CA, US
I lead LLM-driven innovation for recommendation and large-scale ads ranking core conversion modeling, combining post-training of open-source foundation models with scaling-law-guided architecture exploration for long user behavior sequences- LLMs for Rec & Ads ranking (post-training & adaptation): Leading exploration and prototyping of LLM-based approaches for recommendation and large-scale ads ranking, including post-training/adaptation of open-source pretrained LLMs to improve ranking quality with measurable online impact under production constraints (latency, cost, reliability)- Scaling laws × long-sequence architecture × efficient backbones: Driving scaling-law studies and evaluation frameworks to guide model/data/compute tradeoffs, while designing a unified architecture for long user behavior sequences and exploring more efficient Transformer backbones/training strategies to make next-generation ranking models practical at scale.
Education
Michigan State University
Doctor of Philosophy - PhD, Statistics
University of Science and Technology of China
Bachelor's degree, School of the Gifted Young, Statistics
Michigan State University
Doctor of Philosophy - PhD, Computational Science and Engineering
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