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AI Semantic Search Relevance Tuning Engineer

Henry Eriksson

Full-time · Job · London

About the role

Have you ever wanted to build search that actually understands intent instead of just matching keywords? We publish internally and encourage conference submissions, and this role sits at the center of that research. Retrieval-augmented generation and embedding models are what we build. You'll own relevance tuning for our semantic search stack, running offline evaluations and online experiments to close the gap between what users ask and what they actually find useful.

Responsibilities

  • Own relevance tuning for the semantic search stack
  • Design offline evaluation sets for retrieval quality
  • Run online experiments to validate ranking changes
  • Publish internal findings on retrieval methodology

Requirements

  • 4+ years with rag or embedding-based search systems
  • Experience with langchain and hugging face models
  • Comfortable reading and implementing recent research papers

Benefits

  • Fully remote position
  • Conference and publication support
  • Health and dental insurance
  • Competitive salary

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Categories

NLP & Prompt Engineering AI & Machine Learning Engineers

Skills

python rag langchain hugging face openai api

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

NLP & Prompt Engineering AI & Machine Learning Engineers

Skills

python rag langchain hugging face openai api

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