Member of Technical Staff (ML Engineer, Recommendations & User Modeling)

The role

You will design, build, and optimize recommendation systems that power core experiences on Perplexity. You will own personalization and ranking, build user modeling, and design decision layers to improve user experience.

What you will do

• Own the personalization and ranking behind key product surfaces
• Build user modeling that captures intent, preference, and propensity
• Design the decision layer that balances competing objectives
• Build the data and evaluation foundations for system learning
• Help shape the technical direction of ranking, recommendations, and personalization

Required qualifications

• Deep, hands-on experience building production recommendation, ranking, or personalization systems at scale
• Strong ML fundamentals, covering areas such as engagement modeling, model calibration, offline and online metrics, and online experimentation
• Experience integrating LLMs into ranking, retrieval, or personalization pipelines
• Taste and judgment for how personalization should work in an LLM-native product
• Curiosity about reimagining it from first principles
• For tech leadership roles, prior experience setting technical direction for recommendation/ranking projects

Nice to have

• Experience with large-scale ranking and training infrastructure (multi-stage retrieval and ranking, feature stores, real-time serving)
• Background in user understanding, feed ranking, notifications, growth, or lifecycle modeling

About the company

Perplexity builds AI for those who expect more. Their products are designed to help people find answers, make consequential decisions, and complete ambitious work.