Why this role stands out
This role at Perplexity offers a unique opportunity to shape the core of a cutting-edge search engine, blending data analysis with engineering to drive significant improvements in search quality. You'll thrive here if you have a passion for solving complex problems at scale, enjoy building robust data pipelines, and are eager to contribute to a fast-paced, innovative environment with hybrid flexibility. Apply now to make a tangible impact on how people access information!
Quick overview
Job description
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
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