Senior Applied Research Scientist developing efficient models for multimodal retrieval. Joining NVIDIA's Retriever team to advance the state of retrieval systems across various modalities.
Responsibilities
Develop efficient and performant models and pipelines that extract text content from images, video, audio, and other modalities
Explore and craft datasets, metrics, experiments, and validation scripts to develop standard methodologies for research
Help ML Engineers scale pipelines to production capability through the development of NVIDIA Inference Microservices (NIMs)
Write papers, blog posts, documentation, and trainings that help customers understand and take advantage of our research
Keep 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 preferred
Track record of publication in leading conferences like SIGIR, KDD, UMAP, RecSys
Understanding of the state of the art in retrieval research with a focus on multimodal content retrieval
5+ years of experience developing multimodal systems across a range of models and platforms
Information retrieval experience is a big plus
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)
Ability to communicate ideas clearly through blog posts, papers, kernels, GitHub
Excellent communication and interpersonal skills
Ability to work in a dynamic, product-oriented, distributed team
History of mentoring junior engineers and interns is a plus.
Benefits
Competitive salary package
Benefits
Job title
Senior Applied Research Scientist, Multimodal Retrieval
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