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Parallel Web Systems

APIs for AI-driven web research

Member of Technical Staff - Model Training

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Have a bachelor's degree or an equivalent combination of education, training, and professional experience.
  • Have a field relevant to the role, demonstrated through coursework, training, or professional experience.
  • Have deep intuition on modern models and training, including transformer fine-tuning, data curation, and label quality.
  • Think rigorously about how ranking, retrieval, and agent behavior inform one another, and how to train models that serve all three.

Responsibilities

  • Own the training pipeline behind models powering Parallel’s search stack and agents, including rankers, classifiers, and query models for search and models that help agents plan, reason, and execute tasks over web data.
  • Build the path from real product usage to high-quality training data.
  • Fine-tune and rigorously evaluate models.
  • Safely ship models to traffic used by millions.

Desired Qualifications

  • Care about research being applied to products and systems used by millions.

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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