AI Engineer - Document Intelligence & Applied GenAI

PandaDoc is seeking an AI Engineer specializing in document intelligence and applied generative AI. The role focuses on building and deploying ML models for document understanding, combining traditional computer vision approaches with cutting-edge LLM-based solutions.

• Model Development & Evaluation: Build evaluation frameworks for document models, LLMs, OCR, and structured extraction; define metrics and benchmarks for real-world document workloads
• Dataset & Pipeline Creation: Design high-quality datasets for training and fine-tuning; create scalable preprocessing pipelines for PDFs, scans, images, forms, and semi-structured documents
• Model Training & Fine-Tuning: Train and fine-tune transformer-based OCR, VLMs, layout models, and open-source LLMs; optimize for reliability, accuracy, and cost efficiency
• Inference & Deployment: Deploy models using modern inference runtimes (vLLM, TGI, TensorRT, ONNX Runtime); build guardrails and monitoring systems
• RAG & Document Reasoning: Develop retrieval and chunking strategies for document structures; optimize RAG pipelines for semantic search and workflow automation
• Cross-Functional Collaboration: Partner with product managers, engineers, and designers to define AI opportunities

• 5+ years of Python experience
• Experience training, fine-tuning, and deploying computer vision models for document intelligence (layout detection, table extraction, OCR, information extraction)
• Hands-on experience with:
  • Traditional document AI models (LayoutLM, Donut, DocFormer)
  • Vision-language models with OCR capabilities (DeepSeek-OCR, LightOnOCR-1B, etc.)
  • Model deployment using vLLM, TGI, TensorRT, or ONNX Runtime
  • LLMs applied to document intelligence workflows
  • Coordinate systems and spatial reasoning for form/document field detection
• Nice to have: PDF parsing libraries, open-source model fine-tuning, evaluation metrics knowledge (F1, exact match)

• Distributed team with flexible remote work options globally
• 6 self-care days
• Competitive salary
• Open culture emphasizing feedback and professional development