Senior Engineer Analyst

Intellias; Madrid; A distancia; EUR 60.000 - 80.000; Jornada completa

Descripción de la vacante

A leading tech company is seeking a Senior ML Engineer / Researcher to focus on OCR and document intelligence. This remote position offers an opportunity to work with open-source models for high-precision document conversion. The ideal candidate will have expertise in Python, PyTorch, and Hugging Face, along with a strong understanding of OCR pipelines and layout recognition.

Formación

• Strong hands-on expertise with Python, PyTorch, and Hugging Face Transformers (training, fine-tuning, inference).
• Practical experience deploying LLM/VLM models on vLLM or equivalent high-performance inference frameworks.
• Solid understanding of OCR pipelines, layout parsing, and document structure recognition.

Responsabilidades

• Research, evaluate, and fine-tune open-source OCR and document intelligence models for text and layout extraction from PDFs.
• Develop end-to-end solutions for PDF-to-Markdown / PDF-to-HTML conversion.
• Build tools for data preprocessing, annotation, and quality evaluation of OCR outputs.

Conocimientos

Python

vLLM

Hugging Face (inference)

Computer Vision

PyTorch

Document intelligence

OCR pipelines

Educación

B2 level of English

Descripción del empleo

Senior ML Engineer / Researcher

Location : Remote from Spain (Spanish employment contract)

We are actively experimenting with OCR and metadata extraction from the PDF documents. OCR is one of the very hot topics these days with open models actively competing for the leading places - DeepSeek OCR, LightOn OCR, etc.

We are looking for someone with the experience of running OSS models on vLLM with focus on document intelligence - computer vision that results in PDF - Markdown or PDF - HTML conversion with high precision for complex documents

Requirements

• Python
• vLLM
• Hugging Face (inference)
• Computer Vision
• PyTorch
• Strong hands‑on expertise with Python, PyTorch, and Hugging Face Transformers (training, fine‑tuning, inference).
• Practical experience deploying LLM / VLM models on vLLM or equivalent high‑performance inference frameworks.
• Solid understanding of OCR pipelines, layout parsing, and document structure recognition (PDFs, scanned docs, tables, mixed content).
• Understanding of cloud infrastructure and GPU‑based inference pipelines.
• Research mindset with the ability to experiment, analyze, and iterate quickly.
• Strong communication and documentation skills; ability to clearly present findings and proposed improvements.
• At least B2 level of English.

Responsibilities

Research, evaluate, and fine‑tune open‑source OCR and document intelligence models for text and layout extraction from complex PDFs.

Develop end‑to‑end solutions for PDF‑to‑Markdown / PDF‑to‑HTML conversion with high accuracy in text structure, formatting, and layout retention.

Build tools for data preprocessing, annotation, and quality evaluation of OCR outputs.

Implement techniques for post‑processing, text alignment, and metadata extraction to enhance model precision.

Collaborate with research and engineering teams to integrate OCR pipelines into production‑grade systems.

Stay up to date with the latest developments in document AI, multimodal learning, and OCR research.