Ph.D. Research Large Language Models Intern

Nvidia

Confirmed live yesterday High trust

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Work type: On-site
Location: Santa Clara, CA
Posted: 23 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Similar $225k

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About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

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TL;DR · Ph.D. Research Large Language Models Intern

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NVIDIA 2027 Internships: Ph.D. Research Large Language Models is a research internship focused on advancing the capabilities of large language and multimodal models within an industry-leading team. You will research and develop novel methods, collaborate with internal teams and external researchers, and deliver results such as prototypes, patents, products, or original research publications to enable new product types. The role requires candidates currently pursuing a Ph.D. in Computer Science, Electrical Engineering, or related fields. Key technical requirements include proficiency in Python, C++, CUDA, and deep learning frameworks like PyTorch, TensorFlow, or JAX. Candidates should possess a strong research background with publications at top conferences. Relevant domain expertise includes transformer architectures, model efficiency, quantization, reinforcement learning, retrieval-augmented generation, and synthetic data generation to solve complex challenges in large-scale model training and inference optimization.

Skills

Large Language Models Multimodal Models Python C++ CUDA PyTorch TensorFlow JAX Deep Learning Transformer Architectures Model Compression Quantization Reinforcement Learning Retrieval-Augmented Generation (RAG) Neural Architecture Search Instruction Tuning Knowledge Distillation Data Synthesis

What you'll do

Research and develop novel methods to advance large language and multimodal model capabilities.
Translate research findings into practical applications for product groups to enable new products.
Produce tangible deliverables including prototypes, patents, and published original research.
Implement advanced techniques such as knowledge distillation, data synthesis, or long-context methods.
Optimize model efficiency through compression, pruning, quantization, and inference acceleration.
Perform training and alignment tasks including instruction tuning and reinforcement learning.
Develop and refine retrieval-augmented generation (RAG) and multimodal vision language models.
Conduct research in advanced reasoning, test-time inference, and synthetic data generation.

What we're looking for

Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field.
Must provide an anticipated graduation date on the resume or CV for consideration.
Proficiency in Python, C++, CUDA, and Deep Learning Frameworks (PyTorch, TensorFlow, JAX, etc.) is required depending on the internship.
A strong background in research with publications at top conferences is required.
Excellent communication and collaboration skills are required.
Experience with large-scale model training is a plus.
Research experience in specific areas like LLMs, Transformer architectures, or Model Efficiency may be required based on the internship.
Research experience in advanced topics such as RAG, Multimodal models, or Reinforcement Learning may be required based on the internship.

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