The internet is vast, containing trillions of URLs. Perplexity’s crawling and storage system is complex and has multiple stages (URL discovery, crawling, parsing, indexing). Each stage offers many opportunities for improvement and room for intricate bugs. You’ll work at the intersection of data analysis and engineering — designing metrics, building data pipelines, and improving the quality of our search and answer systems.

Responsibilities

Find and diagnose quality issues in our crawling pipeline

Train small models that optimize particular aspects of the pipeline (e.g. parsing quality)

Build datasets for model training, including LLM-as-a-judge labeling pipelines

Improve page selection algorithms for indexing

Design and analyze experiments to validate improvements

Qualifications

4+ years of experience as a data analyst, ML engineer, or in a related role

Strong coding skills: you should be able to write production-grade code at the level of a mid-level backend engineer

Experience designing metrics from scratch

Experience training ML models that shipped to production with measurable metric improvements

Nice to have

Direct experience working on web crawling or indexing pipelines