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AI Query Understanding Engineer

Henry Eriksson

Full-time · Job · New_York

About the role

When someone types "best pizza near me that's open late" into our search platform, 14 things need to happen before we return results: intent classification, entity extraction, location resolution, temporal parsing, preference ranking, and more. We call this the query understanding layer, and it processes 12 million queries daily for our restaurant discovery clients. The current pipeline handles straightforward queries well but falls apart on compound intents, implicit preferences, and conversational follow-ups. "That same place but with outdoor seating" — what does "that" refer to? Your job is to make the query understanding layer handle these cases as naturally as a human concierge would. You'll join a search team of four engineers in our NYC office (3 days on-site, 2 remote). The senior search architect owns the retrieval and ranking stack; you'll own everything upstream — from raw query string to structured search intent. Every improvement gets measured by search success rate: the percentage of queries where the user clicks a result in the top 3.

Responsibilities

  • Build and improve query understanding models for intent, entities, and context
  • Handle compound intents and conversational query resolution
  • Design evaluation benchmarks for query understanding accuracy
  • Integrate with the retrieval pipeline via structured intent outputs
  • Analyze query logs to identify failure patterns and prioritize fixes
  • Run online experiments to measure search success rate improvements

Requirements

  • 3+ years in NLP with experience in search, dialogue, or information extraction
  • Hands-on work with transformer models for classification and extraction
  • Strong Python and PyTorch skills
  • Experience with evaluation methodologies for NLP systems
  • Interest in search ranking and user intent modeling

Benefits

  • Hybrid — 3 days NYC office, 2 days remote
  • Health, dental, and vision coverage
  • Commuter benefits
  • $3,000 annual conference budget
  • Catered lunches on office days

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Categories

NLP & Prompt Engineering AI & Machine Learning Engineers

Skills

python pytorch hugging face sql docker

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

NLP & Prompt Engineering AI & Machine Learning Engineers

Skills

python pytorch hugging face sql docker fastapi

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