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AI Hallucination Rate Benchmarking Engineer

Sofia Garcia

Full-time · Job · Los_Angeles

About the role

Hallucination rate, langchain retrieval quality, and statistical significance testing are the core of what we build here. Every model vendor reports their own hallucination numbers using their own methodology, which makes cross-model comparison nearly meaningless for teams trying to pick a model in good faith. You'll design a benchmarking suite that measures hallucination rate consistently across model families and retrieval setups, then publish the methodology so other teams can reproduce it. This is a senior, largely self-directed role reporting to our head of evaluation research.

Responsibilities

  • Design a consistent hallucination benchmarking methodology across models
  • Build the evaluation suite and validate it against human judgments
  • Publish methodology documentation for external reproducibility

Requirements

  • 5+ years in ml evaluation, nlp research, or benchmark design
  • Strong statistical background in significance testing
  • Comfortable publishing methodology for external scrutiny

Benefits

  • Fully remote position
  • Competitive salary and equity
  • Research time for methodology publications
  • Health, dental, and vision insurance

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Categories

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face statistics rag

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face statistics rag

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