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4 дня назад

Research Engineer (AI)

180 000 - 350 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Research Engineer (AI): Building learned signals and decision systems for web-scale search with an accent on page quality, credibility, parsing, and semantic deduplication. Focus on defining ground truth for ambiguous problems, training classifiers and rankers, and improving crawling, indexing, and retrieval decisions.

Location: San Francisco, California; on-site

Salary: $180K–$350K

Company

hirify.global is an applied AI lab building a large-scale search engine that crawls the web, trains embedding models, and uses high-performance vector databases for retrieval.

What you will do

  • Own the signals and decisions that determine which pages to index, refresh, follow, deduplicate, or exclude.
  • Improve parsing on pages that are currently unsupported and measure the resulting search improvements.
  • Train models to assess page quality and establish workable definitions of quality for supervision.
  • Model credibility, misinformation, source reliability, and whether content is intended for readers or crawlers.
  • Determine whether documents are semantically equivalent or meaningfully different for web deduplication.
  • Collaborate with crawling, indexing, and retrieval teams to ensure signals produce measurable search improvements.

Requirements

  • Hands-on machine learning experience with classifiers, rankers, and calibration.
  • Strong data intuition and experience working at web scale.
  • Ability to own ambiguous problems without established ground truth and define what the correct answer means.
  • End-to-end product and systems thinking, connecting signals to decisions and search quality.
  • Interest in finding and evaluating high-quality knowledge.

Culture & Benefits

  • Cross-functional work spanning crawling, indexing, retrieval, and machine learning.
  • Opportunity to build infrastructure and ML systems operating at massive web scale.
  • Equal opportunity employment practices.

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