Applied Research PhD Intern, Retriever - 2025
Germany, Munich
NVIDIA
NVIDIA erfindet den Grafikprozessor und fördert Fortschritte in den Bereichen KI, HPC, Gaming, kreatives Design, autonome Fahrzeuge und Robotik.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.
What you’ll be doing:
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
What we need to see:
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.
Ways to stand out from the crowd:
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
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Tags: Computer Science Computer Vision Deep Learning GitHub GPU LLMs Machine Learning Microservices OCR PhD Pipelines Python PyTorch RAG Research
Perks/benefits: Conferences
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