Senior Optical Character Recognition Evaluation Specialist

Himpunan Profesi Hubungan Industrial (HPHI); United Arab Emirates; Remote; AED 260,000 - 380,000; Full time

Benefits offered by this job

100% remote

Competitive compensation

Professional development

Collaborative, international team

Job summary

Himpunan Profesi Hubungan Industrial (HPHI) is seeking a Senior Optical Character Recognition (OCR) Evaluation Specialist for a fully remote role. You will design evaluation methods and benchmarks to assess OCR accuracy, reliability, and performance across diverse documents and languages.

The ideal candidate has deep experience in OCR evaluation, data science, and document analysis, with strong Python skills and familiarity with major OCR tools.

Qualifications

• Bachelor's or master's degree in Computer Science, AI, Data Science, computational linguistics, IT, or related field.
• Significant experience in OCR evaluation, document processing, computer vision, or ML QA.
• Strong understanding of OCR tech, text recognition, and document image processing.
• Experience evaluating OCR engines and benchmarking recognition performance.
• Knowledge of CER, WER, edit distance, and statistical eval methods.
• Proficiency in Python and image processing/data analysis libraries.
• Familiarity with OCR tools like Tesseract, PaddleOCR, EasyOCR, or Azure AI Document Intelligence.
• Experience with OpenCV and Pillow.
• Understanding of document layout analysis, text segmentation, and table recognition.
• Experience preparing ground-truth datasets and annotation QC.
• Knowledge of multilingual text recognition is advantageous.
• Familiarity with ML model evaluation, regression testing, and performance monitoring.
• Strong analytical reasoning, troubleshooting, and attention to detail.
• Excellent technical documentation and communication skills.
• Ability to work independently and remotely.

Responsibilities

• Design and implement evaluation frameworks for OCR systems and document recognition tech.
• Assess OCR accuracy across formats, languages, fonts, layouts, and image conditions.
• Develop benchmark datasets containing scanned documents, images, and ground-truth text.
• Evaluate CER, WER, precision, recall, and other relevant performance metrics.
• Compare OCR engines, configurations, and models against quality benchmarks.
• Analyze recognition errors including substitutions, omissions, insertions, formatting, and segmentation.
• Evaluate performance on low-resolution, skewed, noisy, handwritten, and complex layouts.
• Assess preprocessing techniques like enhancement, binarization, deskewing, and noise removal.
• Validate text extraction accuracy for tables, forms, multi-column layouts.
• Conduct linguistic and contextual reviews to catch errors automated metrics miss.
• Develop automated testing scripts and QA procedures for OCR evaluation.
• Investigate performance variations across languages, scripts, document categories, and sources.
• Collaborate with ML engineers, document intelligence specialists, data scientists, and software developers.
• Recommend improvements to OCR models, preprocessing pipelines, and post-processing methods.
• Establish quality thresholds, acceptance criteria, and regression testing standards.
• Maintain evaluation datasets, test docs, error taxonomies, and performance reports.
• Monitor OCR model performance after updates and releases.
• Present evaluation findings and recommendations to stakeholders.

Skills

Python

OCR evaluation

OpenCV

Pillow

Education

Bachelor's degree

Master's degree

Tools

Tesseract

PaddleOCR

EasyOCR

Azure Document AI

Job description

Job Title: Senior Optical Character Recognition Evaluation Specialist

Location: United Arab Emirates (Remote)

Employment Type: Full-Time

Work Arrangement: 100% Remote — Work From Home

Level: Senior

About the Role

We are seeking an experienced Senior Optical Character Recognition (OCR) Evaluation Specialist to assess, validate, and improve the accuracy, reliability, and performance of OCR technologies used to convert scanned documents and images into machine-readable text. The successful candidate will develop evaluation methodologies, analyze recognition errors, benchmark OCR engines, and establish quality standards for document processing systems. This fully remote role requires strong expertise in text recognition, image analysis, linguistic validation, and statistical performance evaluation.

Key Responsibilities

• Design and implement comprehensive evaluation frameworks for OCR systems and document recognition technologies.
• Assess OCR accuracy across different document formats, languages, fonts, layouts, and image conditions.
• Develop benchmark datasets containing representative scanned documents, images, and ground-truth text.
• Evaluate character error rate (CER), word error rate (WER), precision, recall, and other relevant performance metrics.
• Compare OCR engines, configurations, and recognition models against established quality benchmarks.
• Analyze recognition errors involving character substitutions, omissions, insertions, formatting, and segmentation.
• Evaluate OCR performance on low-resolution images, skewed scans, noisy backgrounds, handwritten text, and complex layouts.
• Assess preprocessing techniques, including image enhancement, binarization, deskewing, and noise removal.
• Validate text extraction accuracy for tables, forms, multi-column documents, and structured layouts.
• Conduct linguistic and contextual reviews to identify recognition errors that automated metrics may overlook.
• Develop automated testing scripts and quality assurance procedures for OCR evaluation.
• Investigate performance inconsistencies across languages, scripts, document categories, and image sources.
• Collaborate with machine learning engineers, document intelligence specialists, data scientists, and software developers.
• Recommend improvements to OCR models, preprocessing pipelines, and post-processing methods.
• Establish quality thresholds, acceptance criteria, and regression testing standards.
• Maintain evaluation datasets, test documentation, error taxonomies, and performance reports.
• Monitor OCR model performance following updates, configuration changes, and system releases.
• Present evaluation findings and technical recommendations to relevant stakeholders.

Qualifications and Experience

• Bachelor's or master's degree in Computer Science, Artificial Intelligence, Data Science, Computational Linguistics, Information Technology, or a related discipline.
• Significant professional experience in OCR evaluation, document processing, computer vision, or machine learning quality assurance.
• Strong understanding of OCR technologies, text recognition algorithms, and document image processing.
• Practical experience evaluating OCR engines and benchmarking recognition performance.
• Knowledge of character error rate, word error rate, edit distance, and statistical evaluation methods.
• Proficiency in Python and relevant image processing or data analysis libraries.
• Familiarity with OCR tools and platforms such as Tesseract, PaddleOCR, EasyOCR, Azure AI Document Intelligence, or equivalent technologies.
• Experience with image processing libraries such as OpenCV and Pillow.
• Understanding of document layout analysis, text segmentation, and table recognition.
• Experience preparing ground-truth datasets and performing manual or automated annotation quality checks.
• Knowledge of multilingual text recognition and different writing systems is advantageous.
• Familiarity with machine learning model evaluation, regression testing, and performance monitoring.
• Strong analytical reasoning, troubleshooting, and attention to detail.
• Excellent technical documentation and communication skills.
• Ability to work independently and collaborate effectively in a fully remote environment.

What We Offer

• 100% remote working arrangement within the stated employment framework.
• Competitive compensation based on qualifications and professional experience.
• Opportunities to work on advanced OCR and intelligent document processing technologies.
• Professional development and continuous learning opportunities.
• Collaborative environment with international and multidisciplinary teams.