Member of Technical Staff (Search Quality Analyst)
Perplexity·Belgrade, Serbia | London, England, United Kingdom | Berlin, Berlin, Germany·posted 31d ago · last seen 23m agoTrack this application
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Get Started FreeAbout interviewing at Perplexity
One of the few AI startups with a fully published interview guide (perplexity.ai/hub/careers/interview-guide): online application (response within two weeks) → recruiter phone screen → a technical screen that for engineers is 'usually a standard technical programming interview' → a quickly-scheduled onsite of 4–5 interviews including a hiring-manager deep dive on past work and experience anecdotes → a final interview with a Perplexity founder or leader → decision within a week of the onsite. Coding leans Python and mixes LeetCode medium–hard with practical search-flavored tasks (ranking/filtering, concurrency, data handling); system design is AI-native (RAG pipelines, retrieval at scale, LLM serving cost/latency). Applicants are judged 'solely on merit and potential impact' and must show 'frontier knowledge and excellence in at least one area'; roles are broad by default with team matching happening during the onsite, every role — managers included — is hands-on, and building AI products isn't expected but fluency in using AI tools is required. In-person 4 days/week near an office; remote is case-by-case.
Read the full Perplexity interview process →Description
Perplexity is looking for an experienced analyst to help us build and improve our core search technologies. 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.
This role is hybrid in Belgrade, London or Berlin.
Responsibilities
Find and diagnose quality issues in our search pipeline
Design metrics from scratch to track and measure search quality
Build datasets for model training, including LLM-as-a-judge labeling pipelines
Improve search snippet quality and page selection algorithms for indexing
Design and analyze A/B experiments to validate improvements
Qualifications
4+ years of experience as a data analyst or in a related role
Strong coding skills — expected to write production-grade code at a mid-level backend engineer level
Proficiency with SQL and Python
Demonstrated hands-on experience with at least one of the following:
Designing metrics from scratch (not just analyzing existing A/B experiments)
Building labeling pipelines using LLM-as-a-judge
Training ML models that shipped to production with measurable metric improvements
Designing evals with known ground truth (e.g. SimpleQA, BrowseComp) or driving meaningful improvements on such evals
Preferred Qualifications
Experience working on search-related products
Knowledge of statistics and A/B experiment design
Experience with Apache Spark or Databricks
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