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DocAI Engineer

  • Full-time
  • 2+ years
  • Ahmedabad, on-site
  • Posted 12 Oct 2026

Turn messy scanned documents into clean structured data with OCR and LLM pipelines.

01 / 06

About the role

Pharma batch records, invoices, forms and engineering drawings still arrive as scans and PDFs. You’ll build the systems that read them, pull out the right fields and tables, and hand back clean structured data that client software can trust. This role sits between OCR, layout models and LLMs, and the work is about getting the last few percent of accuracy right.

02 / 06

What you’ll do

  • Build extraction pipelines for scanned and digital documents, covering text, tables, checkboxes, stamps and signatures
  • Combine OCR, layout-aware models and LLMs to extract fields with high accuracy
  • Design validation rules and confidence scores so low-quality extractions get flagged for human review
  • Build test sets from real client documents and track accuracy per field
  • Work with our pharma domain experts on GMP documents, where accuracy and audit trails are mandatory
03 / 06

What you need

  • 2+ years building document processing or OCR systems in production
  • Strong Python skills
  • Hands-on experience with OCR engines such as Tesseract, PaddleOCR, docTR, or cloud OCR like AWS Textract and Azure Document Intelligence
  • Experience with layout-aware models such as LayoutLMv3, Donut or similar
  • Experience using LLMs for structured extraction, including JSON schemas and output validation
04 / 06

Nice to have

  • Experience with table extraction from complex PDFs
  • Exposure to pharma, healthcare or finance documents
  • Knowledge of 21 CFR Part 11 or other compliance requirements for electronic records
  • Experience with vision-language models for document understanding
05 / 06

Tools you’ll use

06 / 06

What you get

  • Work on live client systems in manufacturing, construction, healthcare, pharma, sports and warehousing, with clients in the US, UK and India
  • Ownership of your piece from first requirement to deployment, so you see your models run in the real world
  • Direct access to Mitesh Patel, NVIDIA Certified AI Architect, and the senior engineers for design reviews
  • Access to GPU hardware and NVIDIA Jetson devices for experiments and client work
  • A small team of 20 engineers where your work is visible and your opinion counts in technical decisions

How hiring works

Interns follow the same four steps with a lighter task.

  1. Application review

    We read every application and reply within 5 working days.

  2. Technical task

    You get a short, practical task tied to the role, sized for 3 to 4 hours of work.

  3. Technical interview

    You walk our engineers through your task and one past project you’re proud of.

  4. Founder conversation

    A final chat with Mitesh Patel about the work, the team and your goals.

Apply for DocAI Engineer

Fill in the form and we’ll get back to you within 5 working days.

Applying for
DocAI Engineer
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humans@brainyneurals.com


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