ML/AI Engineer (OCR, VL Models)

Що очікуємо

• Have broad experience working with unstructured data and have used both classical OCR systems (Tesseract, PaddleOCR, EasyOCR) and modern models (PaddleOCR-VL, DeepSeek-OCR, dots.ocr, Qwen3-VL). Understand the strengths and weaknesses of different architectures and the scenarios in which each is most effective.
• Have hands-on experience training and fine-tuning OCR and Vision-Language models.
• Understand algorithmic approaches to image enhancement, preprocessing, and filtering in order to improve downstream recognition quality.
• Have worked with Docling (including advanced backend tuning for parsing complex PDFs and tables), markitdown, Apache Tika, PyMuPDF, and other tools for document conversion and structuring. Be comfortable with processing layered and non-trivial PDF files.
• Have experience working with self-hosted models, including deploying and optimizing models in vLLM environments on H100-class GPUs and above, and understand the principles of GPU architecture and KV cache.