Nvidia Senior Applied Research Scientist Multimodal Retrieval 

United States, Texas 

75210467

What you’ll be doing:

• 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.

• 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 (NIMs) and 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.

What we need to see:

• Candidates with a Master's, Ph.D. or equivalent experience in retrieval or multimodal research are preferred, along with a track record of publication in leading conferences like SIGIR, KDD, UMAP, RecSys, etc.

• An understanding of the state of the art in retrieval research, with a focus on multimodal content retrieval.

• 3+ 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, etc).

• An ability to share and communicate your ideas clearly through blog posts, papers, kernels, GitHub, etc.

• Excellent communication and interpersonal skills are required, along with the ability to work in a dynamic, product-oriented, distributed team. A history of mentoring junior engineers and interns is a plus.