Director, Machine Learning Engineering, Ads Quality
Pinterest, Palo Alto, CA +2
What you will do
- Set the technical vision and multi-year strategy for Ads Quality machine learning, connecting model innovation to Pinner value, advertiser performance, revenue, and marketplace health.
- Lead and develop a group of engineering managers, senior technical leaders, and machine-learning engineers across multiple modeling domains.
- Establish a coherent modeling roadmap across engagement, conversion, ROAS, relevance, ranking, and foundation-model initiatives.
- Drive improvements in model quality, calibration, generalization, cold-start performance, attribution, and robustness across Pinterest surfaces.
- Guide the evolution of Ads models toward larger, more generalizable architectures, including foundation models, distillation, long-context sequence modeling, multimodal representations, and cross-domain learning.
- Ensure that modeling investments translate into reliable production outcomes through strong offline evaluation, online experimentation, launch discipline, and post-launch monitoring.