Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world.

The NVIDIA Retriever Team is seeking an Applied Research Intern who will work on the next generation of retrieval pipelines for RAG, with a focus on modalities beyond text. You'll join a team of experienced Research Scientists, ML and Software Engineers developing NVIDIA's components for enterprise RAG applications, including but not limited to embedding, ranking, object/text detection, OCR, and llm-as-a judge models or highly optimized containers. 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 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.

• Working with our team of researchers to fine-tune information retrieval models and develop pipelines for text, image, video, audio, and other modalities content.
• Exploring and crafting datasets, designing metrics, running experiments, and evaluating models in order to develop standard methodologies. These methodologies will offer customers clear guidance on which models and pipelines to apply in specific contexts.
• Helping ML Engineers bring new Retrieval models to production as NVIDIA Inference Microservices (NIMs) or blueprints
• Writing blog posts, documentation, training materials and potentially papers, that help customers understand and take advantage of our research
• Keeping up to date with the latest developments in Retrieval across academia and industry

• Pursuing a PhD in Computer Science or other relevant technical fields
• Excellent Python programming skills and a strong understanding of the Python deep learning ecosystem (in particular PyTorch)
• Excellent knowledge of the current state of Deep Learning, including experience fine-tuning state of the art Large Language Models and Computer Vision models
• Excellent communication skills and the ability to share and communicate your ideas clearly through blog posts, papers, kernels, GitHub, etc.

• Strong research track record and publication record at top-tier conferences
• Prior experience in multi-GPU and multi-node training
• Background experience and/or academic publication in Retrieval research
• Prior work experience and/or academic publication in (multimodal) Large Language Models