Member of Technical Staff, Applied Research

About the Role

We are looking for an AI Research Engineer to join our document understanding team.

This role is ideal for someone who sits between applied research and strong engineering. You will work on vision-language models, document processing, data curation, synthetic data generation, benchmarking, training, fine-tuning, and post-training. The goal is simple: make our document AI systems more accurate, faster, and more cost-effective in production.

You should be excited by frontier AI work, but equally motivated by practical product impact. This is not a pure research role where ideas stay in papers. You will be expected to prototype quickly, evaluate rigorously, and help turn promising approaches into production systems used by customers.

What You’ll Do

• Develop and train vision-language models for document processing and document understanding.
• Build data pipelines for data curation, synthetic data generation, labeling, and benchmark creation.
• Evaluate base models and perform post-training or fine-tuning to hit specific performance targets.
• Iterate on the agent layer on top of base models to improve quality and cost-effectiveness.
• Design and maintain benchmarks to measure extraction quality, layout understanding, OCR performance, reasoning accuracy, and end-to-end system reliability.
• Work with messy real-world documents, including PDFs, scanned documents, tables, charts, forms, and multi-page enterprise documents.
• Collaborate with customers (less than 15% of the time) to translate product needs into benchmarks and model capabilities.
• Stay close to the latest research in vision-language models, document AI, post-training, synthetic data, and agentic systems.
• Use modern AI coding workflows and tools to move quickly.