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Datalab

AI-driven extraction of structured document data

Senior Software Engineer

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA$225k - $300k /yrIn-person

About the Job

Requirements

  • At least 5 years of full-stack development experience building APIs and/or developer-focused products.
  • Experience building in early-stage startup environments.
  • Experience shipping and maintaining production systems serving high-volume traffic.
  • Experience building with large language models and agentic workflows.

Responsibilities

  • Ship features to the open-source repositories, API, and internal tooling.
  • Design and build frontend features that make document parsing more interactive and understandable.
  • Optimize inference performance and improve framework reliability.
  • Engage with the community on GitHub and Discord by collecting feedback, debugging issues, and identifying opportunities for improvement.
  • Support customer implementations with technical guidance and troubleshooting when needed.
  • Work across backend, frontend, performance, and user-facing surfaces to help developers and enterprises use the models.

Desired Qualifications

  • Experience with Python machine-learning frameworks such as PyTorch or Transformers, or interest in training models.
  • Familiarity with document processing, computer vision, or optical character recognition systems.
  • Experience maintaining or contributing to open-source projects with active communities.
  • Experience writing technical content or demos to showcase work.

About the Company

Datalab

AI-driven extraction of structured document data

Datalab provides a document intelligence platform that converts unstructured documents into structured, machine-readable data via an API toolkit. It uses AI models for OCR, layout detection, and semantic understanding to extract data from PDFs, spreadsheets, and presentations, delivering outputs as JSON, HTML, or Markdown. The platform prioritizes auditability with data-origin tracking through citations and bounding boxes and supports cloud, dedicated, and on-premise deployment across multiple languages. Its goal is to speed enterprise AI adoption by delivering reliable, scalable, and transparent data extraction to power workflows, compliance, and AI pipelines.

Company size
11-50
Company stage
Seed
Total funding
$3.4M
Headquarters
San Francisco, CA
Founded
2024

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