• Design and develop models to extract entities, detect intents, and understand document structure • Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs • Evaluate model performance where ground truth is partial, uncertain, or evolving • Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions • Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines • Understand product use-cases and define key performance metrics for models according to business requirements • Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.)