Staff Machine Learning Engineer, Homefeed
Pinterest · San Francisco, CA, US; Remote, US
About this role
**About Pinterest** Millions of people use Pinterest to find creative ideas, dream about new possibilities, and plan memories that last a lifetime. At Pinterest, AI is a powerful partner that augments creativity and amplifies impact. **Team & Role** Pinterest’s Retrieval team builds shared machine learning capabilities that help connect people with relevant ideas. As a **Staff Machine Learning Engineer (Homefeed)**, you’ll advance how those capabilities are developed through **agentic AI**. Your primary focus will be **Reflex**—automating and accelerating recommendation research and development. You’ll own a major technical area, building agents that investigate opportunities, implement changes, run experiments, and learn from results. You’ll also contribute to **generative retrieval**, with a focus on **Semantic IDs** (learning structured representations of content that recommendation models can generate and use to retrieve relevant items). --- **What you’ll do** - Own and advance a major technical area in automated recommendation research within Reflex, collaborating with technical leads and partner teams. - Build **LLM agents** that connect hypothesis generation, implementation, experiment execution, evaluation, and learning. - Develop rigorous evaluations for agent behavior and research outputs to improve quality, reliability, and efficiency. - Contribute to generative retrieval models, especially **Semantic ID learning**, evaluation, and production integration. - Move ideas from research/prototypes to impact via offline evaluation, online experimentation, and production launches. - Build reliable integrations with ML development infrastructure; make tradeoffs across model quality, iteration speed, compute cost, and operational complexity. - Raise technical quality through hands-on implementation, design/code reviews, documentation, and mentorship. - Partner with research, recommendation, and ML infrastructure teams to shape approaches, resolve dependencies, and support adoption. - Identify and apply relevant research advances; contribute new methods when existing approaches fall short. --- **What we’re looking for** - BS in Computer Science, Machine Learning, or related field (or equivalent practical experience). - **8+ years** building and shipping ML/AI systems, including substantial hands-on engineering and technical leadership. - Demonstrated experience building **LLM agents / agentic AI** for complex tasks, including clear evaluation and improvement approaches. - Strong ML fundamentals and depth in areas such as applied LLMs, representation learning, recommendation systems, retrieval, or ML systems. - Experience taking research ideas into reliable production systems and evaluating impact through meaningful experiments. - Strong software engineering skills (design maintainable systems, implement difficult components, conduct thorough technical reviews). - Experience leading a substantial technical area, making decisions under ambiguity, and collaborating across teams. - Track record mentoring engineers and raising team technical quality. - Clear written and verbal communication, including explaining technical tradeoffs to different audiences. - Disciplined approach to using AI in your own work (verification of generated code, analysis, and conclusions). --- **Additional details** - Individual contributor role (prior people management not required). - **Relocation:** Not eligible for relocation assistance. - **In-office
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