Job Description
Role Summary:
Builds and fine-tunes OCR models, handwriting models, document segmentation, stamp detection, and image cleanup pipelines.
Key Responsibilities:
• Develop, fine-tune, and optimize OCR and document segmentation models.
• Implement preprocessing: deskew, denoise, watermark/stamp removal, cropping, binarization.
• Train CV models (YOLO/SAM) for stamp detection, handwriting region detection.
• Evaluate multiple OCR engines and build benchmarking frameworks.
• Build orchestration pipelines enabling ensemble predictions.
• Optimize inference for large-scale throughput (millions of docs).
Qualifications:
• 5–10 years in CV/ML.
• Deep knowledge of Py Torch, Tensor Flow, CNNs, Vision Transformers, Open CV.
• Prior OCR/Doc AI experience preferred.
Builds and fine-tunes OCR models, handwriting models, document segmentation, stamp detection, and image cleanup pipelines.
Key Responsibilities:
• Develop, fine-tune, and optimize OCR and document segmentation models.
• Implement preprocessing: deskew, denoise, watermark/stamp removal, cropping, binarization.
• Train CV models (YOLO/SAM) for stamp detection, handwriting region detection.
• Evaluate multiple OCR engines and build benchmarking frameworks.
• Build orchestration pipelines enabling ensemble predictions.
• Optimize inference for large-scale throughput (millions of docs).
Qualifications:
• 5–10 years in CV/ML.
• Deep knowledge of Py Torch, Tensor Flow, CNNs, Vision Transformers, Open CV.
• Prior OCR/Doc AI experience preferred.
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