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Staff Software Engineer, Growth AI

208k – 365kSan Francisco, CAPalo Alto, CASeattle, WALos Angeles, CAHybrid8+ YOE
Summary

Staff Software Engineer anchoring AI-powered growth products across SEO and exploratory teams. Architect production ML systems, partner with ML orgs, and set technical direction as a senior IC.

About the role

What you'll do

  • Architect and build the production systems that AI/ML capabilities ship through across two Growth teams: APIs, data pipelines, content systems, evaluation and monitoring infrastructure.
  • Partner with Pinterest's centralized ML org and applied research teams to productize AI/ML capabilities at scale — defining service interfaces, building eval pipelines, and managing latency, cost, and quality tradeoffs.
  • Design and build the cross-team technical foundations that serve both teams: AI evaluation systems, content quality pipelines, agent skill platform, knowledge brain.
  • Set the technical bar across two teams operating an AI-native engineering model: AI in every part of the SDLC, eval-driven shipping, prototype-first culture.
  • Mentor engineers across both teams as a peer Staff IC, deepening their technical work without managing them.

What we're looking for

  • 8+ years of product / systems engineering experience, with a strong track record shipping production systems at scale that touch real users.
  • Cross-team technical leadership: you've been the architectural anchor on multi-team initiatives, set direction others build on, and mentored through code.
  • Working knowledge of common ML/AI techniques (supervised learning, embeddings, ranking, LLMs, evaluation methodology) — enough to scope ML projects, reason about ML system design, and collaborate effectively with MLEs.
  • Strong track record partnering with ML/research teams to ship AI-powered features in production.
  • Demonstrated AI-augmented engineering practice — fluent use of Cursor / Claude Code / agentic tools, with a clear approach to validating AI-generated work.
  • Bachelor’s/Master’s degree in a relevant field such as Computer Science, or equivalent experience.

Nice to have

  • Direct hands-on experience shipping applied ML, LLM/VLM, or agentic systems in production
  • Domain experience in search, discovery, recommendations, ranking, growth, or SEO
  • Experience as the product-engineering counterpart on an AI-first product launch from prototype to scale
Skills
PythonJavaScalaMachine LearningLLMsEmbeddingsRanking SystemsAPIsData PipelinesEvaluation Systems
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