[Hiring] Senior Applied Research Scientist @NVIDIA

Role Description

NVIDIA’s Curator team is seeking a Senior Applied Research Scientist with experience researching, developing, and deploying deep learning models at scale across a range of modalities. You’ll join a team of Applied Research Scientists, Machine Learning and MLOps Engineers working on the next generation of data curation and document extraction pipelines for foundation-model training.

• Working with our team of researchers to develop efficient and performant models and data pipelines that extract and curate multi-modal data (documents, image, audio and videos) used in the training of foundation models.
• Building pipelines for petabyte-scale extraction and content deduplication, including document and html parsing, fuzzy and near-duplicate deduplication, semantic deduplication, and substring deduplication.
• Contributing to the expansion and optimization of curation methodologies targeting petabyte-scale multimodal data run across hundred-node GPU clusters to improve the quality of foundation model training sets.
• Exploring and crafting datasets, metrics, experiments, and validation scripts to develop standard methodologies for research.
• Helping ML Engineers scale pipelines to production capability through the development of NVIDIA Inference Microservices (NIMs) and blueprints which demonstrate how to deploy NIMs in a pipeline effectively.
• Writing papers, blog posts, documentation and training materials that help customers understand and take advantage of our research.
• Keeping up to date with the latest developments in data curation across academia and industry.

Qualifications

• Master's, Ph.D. or equivalent experience in data curation, document AI, information retrieval or multimodal research.
• Track record of publication in leading conferences like CVPR, ICCV, ECCV, KDD, etc.
• Hands-on experience developing computer vision and document-extraction models and pipelines, including layout analysis, OCR, and table, figure, or formula extraction.
• Kaggle Grandmaster status or a strong record of top-tier results in machine learning competitions is a strong plus.
• Understanding of the state of the art in data curation research, with a focus on multimodal content extraction and deduplication.
• 10+ years of experience developing multimodal systems across a range of models and platforms.
• Proven expertise managing distributed data frameworks like Ray, Spark, or Dask.
• History of deploying massive, multi-node machine learning or data processing tasks within production environments.
• Knowledge of best practices in batching, streaming, and scaling of ingestion pipelines to support real-world applications.
• Excellent Python programming skills and strong hands-on experience with PyTorch or comparable modern deep learning frameworks.
• Ability to share and communicate ideas clearly through blog posts, papers, kernels, GitHub, etc.
• Excellent communication and interpersonal skills.
• Ability to work in a dynamic, user-focused, distributed team.
• History of mentoring junior engineers and interns is a plus.

Requirements

• Location is flexible and the team is remotely situated, focusing on NA/EU time zones.
• Remote work is accepted in any country where NVIDIA has an office.

Benefits

• Highly competitive salaries.
• Comprehensive benefits package.
• Base salary range is 224,000 USD - 356,500 USD, determined based on location, experience, and pay of employees in similar positions.
• Eligibility for equity and benefits.