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Job
Member of Technical Staff (ML Engineer, Recommendations & User Modeling)
AI / ML Engineer
• On-site
• Full-time
• 📍 San Francisco
Design, build and optimize the recommendation and personalization systems that power core Perplexity experiences, combining frontier LLMs with real product usage signals.
Responsibilities
- ▹Own the personalization and ranking behind key product surfaces
- ▹Build user modeling capturing intent, preference and propensity
- ▹Design the decision layer balancing competing objectives for the best user experience
- ▹Build the data and evaluation foundations for continuous learning
- ▹Help shape technical direction of ranking, recommendations and personalization
Requirements
- ▹Deep, hands-on experience building production recommendation, ranking or personalization systems at scale
- ▹Strong ML fundamentals: engagement modeling, model calibration, offline/online metrics, online experimentation
- ▹Experience integrating LLMs into ranking, retrieval or personalization pipelines
- ▹Taste and judgment for personalization in an LLM-native product
- ▹For tech-lead roles: prior experience setting technical direction for ranking/recommendation projects
Nice to have
- ▹Experience with large-scale ranking/training infrastructure (multi-stage retrieval and ranking, feature stores, real-time serving)
- ▹Background in user understanding, feed ranking, notifications, growth or lifecycle modeling
Soft skills
Curiosity and first-principles thinkingCross-functional collaborationOwnershipJudgment under ambiguity
About the company
Perplexity is an AI-powered answer engine that combines multiple leading models with real-time web search to deliver fast, trustworthy, citation-backed answers. In 2026 it launched Computer, a general-purpose agentic AI product used by millions to turn knowledge into action.
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