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K

AI Search Relevance Engineer

Kyle Park

Full-time · Job · New_York

About the role

Hugging Face models, retrieval-augmented ranking, and a search index handling millions of queries a day are the core of what this team builds. If tuning relevance until the top result is actually the right one sounds satisfying to you, keep reading. You'll join the semantic search team to improve ranking quality using RAG techniques layered on top of our existing embedding-based retrieval, measuring impact with SQL-driven relevance metrics rather than guesswork. Everything ships in Docker containers through our standard deployment pipeline. You'll work alongside engineers already focused on query understanding and autocomplete, sharing infrastructure and evaluation datasets.

Responsibilities

  • Improve search ranking quality using RAG-based reranking techniques
  • Measure relevance impact with SQL-driven metrics and offline evaluation
  • Package and deploy improvements through Docker-based pipelines
  • Collaborate with the query understanding and autocomplete teams

Requirements

  • 3+ years working on search relevance or ranking systems
  • Hands-on experience with Hugging Face models and RAG techniques
  • Strong SQL skills for relevance analysis
  • Comfortable with Docker-based deployment workflows

Benefits

  • Fully remote position
  • Health and dental insurance
  • 401k matching
  • Learning stipend

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Categories

NLP & Prompt Engineering AI & Machine Learning Engineers

Skills

python hugging face rag 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 hugging face rag sql docker

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