Senior Applied Research Scientist, Multimodal Retrieval

Nvidia • Santa Clara, CA

127d • $224,000 - $356,500 • Remote

About The Position

NVIDIA's Retriever 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 retrieval pipelines for RAG, with a focus on the ingestion of modalities beyond text. At NVIDIA we're building the framework upon which production RAG systems are based. We have contributed to top research models in the text embedding space, topping the MTEB leaderboard, Vidore V1/V2 and have developed commercially viable versions of these models for use in production systems by our customers. Come be a part of our world-class team building the future of Retrieval.

Requirements

• Candidates with a Master's, Ph.D. or equivalent experience in retrieval or multimodal research are preferred.
• A track record of publication in leading conferences like CVPR, ICCV, ECCV, KDD, etc.
• Hands-on experience developing computer vision models and pipelines, with preference for document-focused tasks such as layout analysis, table or figure detection, and OCR.
• 10+ years of experience developing multimodal systems across a range of models and platforms.
• Knowledge of best practices in batching, streaming, and scaling of ingestion pipelines to support real-world applications.
• Excellent Python programming skills and a strong understanding of the Python deep learning ecosystem (PyTorch, Tensorflow, MXNet, etc).
• Strong communication and interpersonal skills are essential, as well as the capability to collaborate within a dynamic, distributed team.

Nice To Haves

• Competitive results in computer vision competitions on Kaggle or similar platforms.
• Information retrieval experience is a big plus.
• An ability to share and communicate your ideas clearly through blog posts, papers, kernels, GitHub, etc.
• A history of mentoring junior engineers and interns is a plus.

Responsibilities

• Working with our team of researchers to develop efficient and performant models and pipelines that extract text content from images, video, audio and other modalities.
• Building vision pipelines for document ingestion, including page layout analysis, object detection, and OCR.
• 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 trainings that help customers understand and take advantage of our research.
• Keeping up to date with the latest developments in Retrieval across academia and industry.

Benefits

• Equity and benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Industry: Computer and Electronic Product Manufacturing
• Education Level: Master's degree