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Parallel Web Systems

APIs for AI-driven web research

Early Career Research Engineer

AI ResearchUpdated on Nov 12
Full-time

About the Job

Requirements

  • A Bachelor's degree or an equivalent combination of education, training, and professional experience.
  • A relevant field demonstrated through coursework, training, or professional experience.
  • Experience with information retrieval systems, embedding models, or neural ranking at scale, or strong curiosity about fundamental problems in training models to understand and serve billions of web documents.
  • Comfort operating between theory and production, including reading research papers and debugging distributed training pipelines.

Responsibilities

  • Design and train the models that power the company's APIs and help AI agents find relevant information from the open web.
  • Train embedding models to capture semantic intent across diverse query types.
  • Balance model expressiveness with sub-second retrieval latency.
  • Maintain index freshness as the web updates without rebuilding from scratch.
  • Build information retrieval capabilities for AI agents issuing complex, multi-hop queries and expecting structured, programmatic responses.
  • Combine classical information retrieval techniques with modern deep learning and deliver solutions efficiently on real infrastructure.

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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