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Apiphany

AI-driven extraction from unstructured documents

Data Domain Expert

Data ManagementConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

  • Three to six years of experience in mechanical engineering, electrical engineering, or electronics engineering roles within original equipment manufacturers or manufacturing organizations.
  • Strong understanding of mechanical and manufacturing concepts.
  • Ability to interpret technical data and explain it clearly to non-domain teams.
  • Experience reviewing, validating, or tagging data.

Responsibilities

  • Understand and review mechanical and manufacturing-related client data.
  • Guide data-processing teams on data relevance and usage.
  • Help define tagging and classification guidelines.
  • Review processed outputs and provide feedback for corrections.
  • Support quality checks and validation activities.
  • Assist during client discussions when domain input is required.

Desired Qualifications

  • Experience working with engineering design documents, bills of materials, product lifecycle management software, and computer-aided design models.
  • Experience working with data, analytics, or artificial intelligence teams.
  • Exposure to quality, process, or documentation-heavy projects.
  • Familiarity with tools used for tagging or reviewing data.

About the Company

Apiphany

AI-driven extraction from unstructured documents

Apiphany provides an AI-powered platform that extracts key information from unstructured documents such as invoices, contracts, and reports. It uses artificial intelligence, machine learning, and natural language processing to understand document context and pull relevant data into structured formats, automating data entry and reducing errors. The system integrates with existing business workflows and continuously learns from new data to improve accuracy, while prioritizing security and regulatory compliance across industries. Its goal is to help businesses save time and cut costs by turning unstructured data into actionable, decision-support information.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
2023

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