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AI Faceted Search Filter Recommendation Engineer

Kyle Park

Full-time · Job · Chicago

About the role

The models you'll help ship decide which filters show up first the moment a user starts searching, before they've clicked anything at all. Our semantic search and query intent tools already understand what a user is looking for, but the filter panel next to those results still shows the same static list of categories to everyone. This role helps build a system that recommends the most relevant filters dynamically based on query intent and what similar searches have found useful.

Responsibilities

  • Help build models recommending dynamic search filters from query intent
  • Analyze filter usage patterns across similar historical searches
  • Support senior engineers in running filter recommendation experiments
  • Summarize findings clearly for the product and search quality teams

Requirements

  • Some experience with SQL and search or recommendation data
  • Basic understanding of query intent or ranking concepts
  • Comfortable with Hugging Face model pipelines
  • Willingness to learn production search infrastructure

Benefits

  • Fully remote entry-level role
  • Structured mentorship program
  • Health insurance included
  • Clear growth path to mid-level engineer

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Categories

AI & Machine Learning Engineers AI Product & Strategy

Skills

python sql statistics hugging face

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

AI & Machine Learning Engineers AI Product & Strategy

Skills

python sql statistics hugging face

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