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Parallel Web Systems

APIs for AI-driven web research

Member of Technical Staff - Search Ranking

Applied Machine LearningUpdated on Nov 12
Full-time

About the Job

Requirements

  • Have a bachelor's degree or an equivalent combination of education, training, and professional experience.
  • Demonstrate a field relevant to the role through coursework, training, or professional experience.
  • Bring years of experience appropriate to the internal job level requirements for this position.
  • Have deep intuition for relevance, feature engineering, and trade-offs between quality, latency, and cost.
  • Think rigorously about how ranking, retrieval, and agent behavior inform one another, and how to train models that serve all three.
  • Care that research is applied to products and systems used by millions.

Responsibilities

  • Own the multi-stage ranking pipeline that narrows a web-scale set of candidates to the best passages for a query while minimizing compute.
  • Improve precision and recall across fast candidate retrieval, lightweight first-pass ranking, and heavier neural reranking.
  • Decide how much compute each query should receive.
  • Evaluate ranking using real usage outcomes rather than offline proxies.

About the Company

Parallel Web Systems

APIs for AI-driven web research

Parallel Web Systems builds infrastructure and tools that let artificial intelligence use the web effectively. Its core products are APIs, including a Deep Research API and a Search API, that give AI agents fast and accurate access to web data. The systems re-engineer every layer of data flow—from crawling and indexing to ranking—so machines can consume information efficiently rather than humans. Developers and enterprises embed these APIs into their applications to enable real-time research, workflow automation, coding assistance, and market intelligence. The company differentiates itself by focusing on AI-native web access and machine-to-machine research, creating a programmatic web where AI agents can autonomously query, analyze, and synthesize information. Its goal is to establish a standard way for AI to interact with the web, powering automated research and data-driven workflows at scale.

Company size
51-200
Company stage
Series B
Total funding
$230M
Headquarters
Palo Alto, CA
Founded
2023

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