Senior Applied Research Scientist, Data Curation

What you'll do

• Develop efficient models and data pipelines to extract and curate multi-modal data for foundation model training.
• Build petabyte-scale pipelines for content deduplication, including document parsing and semantic deduplication.
• Optimize curation methodologies for large-scale multimodal data processed across hundred-node GPU clusters.
• Create datasets, metrics, experiments, and validation scripts to establish standard research methodologies.
• Collaborate with ML Engineers to scale pipelines into production via NVIDIA Inference Microservices (NIMs).
• Author papers, blog posts, and documentation to communicate research findings and training materials to customers.
• Monitor and integrate the latest industry and academic developments in data curation research.

What we're looking for

• Master's or Ph.D. degree in data curation, document AI, information retrieval, or multimodal research.
• Track record of publication in leading conferences such as CVPR, ICCV, ECCV, and KDD.
• 10+ years of experience developing multimodal systems across a range of models and platforms.
• Hands-on experience developing computer vision and document-extraction models including layout analysis, OCR, and table/figure extraction.
• Proven expertise managing distributed data frameworks like Ray, Spark, or Dask for multi-node production tasks.
• Excellent Python programming skills and hands-on experience with PyTorch or comparable deep learning frameworks.
• Strong understanding of state-of-the-art research in multimodal content extraction and deduplication.
• Ability to communicate complex ideas clearly through papers, blog posts, documentation, and other public platforms.