JavaScript Developer for High-Accuracy Multi-Language OCR Tool (Tesseract.js)
Category: Web Developer
Job Description
We are building a browser-based tool for Optical Character Recognition (OCR) using Tesseract.js or a similar OCR solution in JavaScript. The tool should offer:Maximum possible OCR accuracy
Support for handwritten and printed text
OCR support for the following languages:
English, Spanish, Russian, Dutch, Italian, Portuguese, Indonesian, German, French, Korean, Danish, Czech, Swedish, Polish, Romanian, Thai, Vietnamese, Turkish, Japanese, Chinese, Georgian, Finnish, Arabic
Note: The solution must not use heavy machine learning models, and should rely on Tesseract and image preprocessing optimizations.
✅ Responsibilities:
Implement Tesseract.js-based OCR in a React or Next.js frontend
Configure and optimize Tesseract for multi-language and handwriting scenarios
Efficiently load large traineddata language files in-browser
Build a clean, modular OCR interface for integration into our SaaS product
Apply image pre-processing techniques to improve OCR accuracy (grayscale, thresholding, etc.)
Deliver performance optimizations for speed and accuracy
Work collaboratively and communicate technical decisions clearly
Job Skills
? Required Skills:
Strong experience with JavaScript/TypeScript
Proficiency with Next.js or React.js
Hands-on experience with Tesseract.js
Familiarity with Tesseract configuration (psm, oem, etc.)
Good understanding of multi-language handling and character encodings
Knowledge of image processing basics (e.g., sharp.js, canvas)
Performance tuning and efficient frontend architecture
Questions
1. Have you previously worked with Tesseract.js? Please provide code samples or GitHub links.
2. What strategies would you use to optimize OCR accuracy in the browser?
3. How would you support loading multiple traineddata language files efficiently in a browser app?
3. What are Tesseract’s limitations with handwritten text, and how would you mitigate them without ML?
5. Have you ever worked on image preprocessing (e.g., binarization, noise reduction)? If yes, how?
6. What challenges do you foresee in implementing this OCR tool purely in the frontend?
Who Applied Average Bid: Rs.27681.67
