NVIDIA

Senior Applied Research Scientist, Multimodal Retrieval

NVIDIA

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $224,000 - $356,500 per year

Job Level

Senior

Tech Stack

MicroservicesPythonPyTorchTensorflow

About the role

  • Work 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
  • These methodologies will offer customers clear guidance on which models and pipelines to apply in specific contexts
  • 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

Requirements

  • Master's, Ph.D. or equivalent experience in retrieval or multimodal research; track record of publication in CVPR, ICCV, ECCV, KDD, etc.
  • Hands-on experience developing computer vision models and pipelines; preference for document-focused tasks such as layout analysis, table or figure detection, and OCR
  • Competitive results in computer vision competitions on Kaggle or similar platforms
  • Understanding of the state of the art in retrieval research, with a focus on multimodal content retrieval
  • 10+ years of experience developing multimodal systems across a range of models and platforms
  • Information retrieval experience is a big plus
  • Knowledge of batching, streaming, and scaling of ingestion pipelines
  • Excellent Python programming skills and a strong understanding of the Python deep learning ecosystem (PyTorch, Tensorflow, MXNet, etc)
  • An ability to share and communicate your ideas clearly through blog posts, papers, kernels, GitHub, etc.
  • Strong communication and interpersonal skills are essential, as well as the capability to collaborate within a dynamic, distributed team
  • A history of mentoring junior engineers and interns is a plus
  • Location is flexible and the team is remotely situated, focusing on NA/EU time zones