Clair transforms unstructured documents into actionable, structured data – and our ML pipeline is at the heart of it.

As an ML Engineer focused on NLP and Document AI, you will design and improve the models that extract, classify, and structure information from complex real-world documents.

What you will do

Develop and fine-tune NLP models for document understanding
Build extraction pipelines for tables, entities, and relationships
Improve OCR post-processing and layout analysis
Design evaluation frameworks and quality metrics
Collaborate with engineering to integrate models into production

What you will build

Named entity recognition and relation extraction systems

Table detection and structured data extraction from PDFs

Classification models for document types and content segments

What we are looking for

Strong background in NLP, information extraction, or document AI
Experience with transformer-based models (BERT, LayoutLM, etc.)
Proficiency in Python and ML frameworks (PyTorch, Hugging Face)
Understanding of production ML systems and deployment
Bonus: Experience with OCR systems or financial/ESG documents

Why Clair

Solve hard, meaningful problems with real enterprise data

Shape the ML architecture from the ground up

Work with diverse, real-world document types

Direct impact on how companies handle compliance and ESG data

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