Join Perplexity AI as a Search Quality Analyst to enhance core search technologies through data analysis and engineering.
Posted by employer 1 week ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
Skills & Technologies
Role intensity
70% hands-on coding
AI in the day-to-day
Building labeling pipelines using LLM-as-a-judge.
Requirements
Not disclosed in this posting: compensation, visa sponsorship.
Joblaze summary
In this role, the analyst focuses on enhancing search technologies by diagnosing quality issues and designing metrics to measure performance. Key skills include strong coding abilities in Python and SQL, along with experience in building data pipelines and training machine learning models. This position is ideal for someone with over four years of experience in data analysis or a related field, particularly those with a background in search-related products. The team is dedicated to refining search quality, making it a pivotal role in the company's growth.
Joblaze insights
Quick facts
From the original posting
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