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Principal Engineer, AI Platform

243k – 500kSan Francisco, CAHybrid7+ YOE
Summary

Principal Engineer setting technical vision and building AI/ML infrastructure for Generative AI and Recommender Systems at Pinterest, scaling to hundreds of millions of inferences per second. Requires deep expertise in distributed systems and proven cross-org technical leadership.

About the role

What you’ll do

  • Set the technical vision and roadmap for the Pinterest AI Platform, aligning with business priorities and long-term company strategy.
  • Drive cross-functional strategic initiatives that advance our platform capabilities across:
    • Generative AI: multimodal data management, post-training, evaluation, and batch/online inference.
    • Recommender Systems: feature stores, training infra, and large-scale high performance inference.
    • AI-powered tools that automate the user experience across our platforms, connecting every stage of the AI/ML lifecycle to enhance productivity and accelerate development.
  • Cultivate a collaborative and inclusive culture where every team member feels welcome and empowered, and provide candid, constructive feedback that accelerates individual and team growth.

What we’re looking for

  • Deep expertise in AI/ML infrastructure and distributed systems: Hands-on experience designing, building, and operating highly available, production-grade systems at large scale; strong technical judgment; and proficiency in at least one of C++, Java, or Rust.
  • Proven track record of company-wide impact: Experience leading cross-organizational initiatives, navigating ambiguity, defining technical strategy, influencing architecture decisions, and aligning cross-functional partners and executives around a shared direction.
  • Strong ownership and a high engineering bar: Sets and upholds high standards for engineering quality, integrity, and accountability, and takes end-to-end ownership of outcomes.
  • Bachelor's degree in Computer Science or a related field.
Skills
C++JavaRustAI/ML infrastructureDistributed systemsGenerative AIRecommender SystemsModel trainingModel inferenceFeature stores
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