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AI Search Relevance Feedback Loop Engineer

Isaac Singh

Full-time · Job · Paris

About the role

Enterprise search results quietly get worse over time as user behavior shifts, and right now we have no systematic way to catch that decline before customers complain. Our clients rely on our knowledge graph platform to power search across millions of documents, and we need a senior engineer to close the loop between what users click and how relevance scoring adapts. You'll own the pipeline that turns click and dwell-time signals into relevance feedback, working with defined sprints and clear ownership, partnering closely with the search team on what 'better' actually means for each client vertical.

Responsibilities

  • Build pipelines turning click and dwell-time data into relevance signals
  • Own experimentation for search relevance feedback loops
  • Partner with the search team to define per-vertical relevance goals
  • Report relevance improvements and regressions to engineering leadership

Requirements

  • 5+ years in data engineering with strong SQL and Spark skills
  • Experience with search relevance, ranking, or recommendation systems
  • Background working with knowledge graphs is a plus

Benefits

  • Fully remote across European time zones
  • Health coverage and annual wellness stipend
  • Conference attendance budget for data engineering events

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Categories

data science & analytics

Skills

python sql spark airflow

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

data science & analytics

Skills

python sql spark airflow

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