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This listing was closed on Jul 18, 2026.
Browse Open JobsMember Of Technical Staff (ML Engineer, Recommendations & User Modeling)
Summary by AIEngineer.careers
Member Of Technical Staff (ML Engineer, Recommendations & User Modeling) is a Machine Learning Engineer role (full-time). with Perplexity. in PALO ALTO, US. Imported listing (source: ziprecruiter.com). Apply on the employer's site (ziprecruiter.com).
Imported listing (source: ziprecruiter.com) · Apply on ziprecruiter.com
PALO ALTO · US
—
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from ziprecruiter.com
Perplexity is seeking experienced ML engineers to design, build, and optimize recommendation systems for its AI-powered platform. The role focuses on personalization and user modeling to deliver deeply tailored experiences using frontier LLMs and real-time data.
Responsibilities
- Own the personalization and ranking behind key product surfaces to improve user and business metrics.
- Build user modeling that captures intent, preference, and propensity for personalized experiences.
- Design decision layers that balance competing objectives for optimal user experiences.
- Build data and evaluation foundations for continuous learning and improvement.
- Help shape the technical direction of ranking, recommendations, and personalization.
Requirements
- Deep hands-on experience building production recommendation, ranking, or personalization systems at scale.
- Strong ML fundamentals covering engagement modeling, calibration, offline/online metrics, and experimentation.
- Experience integrating LLMs into ranking, retrieval, or personalization pipelines.
- Taste and judgment for personalization in an LLM-native product.
Perplexity
San Francisco · US · 1014+ employees
Perplexity is an AI-powered answer engine and search platform founded in 2022. It uses large language models to provide accurate, real-time, and well-sourced responses to user queries, aimed at transforming the search and information retrieval experience.
