PhD Research Intern: Efficient DL for Diffusion & Edge AI

NVIDIA Corporation; California; On-site; USD 52,000 - 129,000; Full time

Benefits offered by this job

Intern benefits

Job summary

NVIDIA seeks an outstanding PhD intern to advance efficient deep learning within the Deep Learning Efficiency Research (DLER) team in California. You will research diffusion LLMs, multimodal models, and efficient agentic AI, with opportunities to publish and transfer technology to product groups.

You will collaborate with researchers across cloud and edge environments, participating in a fast-paced, award-winning research culture and contributing to cutting-edge architecture and optimization

Qualifications

• Pursuing a Ph.D. in Computer Science/Engineering, Electrical Engineering, etc.
• Excellent knowledge of theory and practice of machine learning and deep learning.
• Experience with large language models, diffusion language models, multimodal / vision-language models, or agentic systems is required.
• Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) is required.
• Outstanding research track record with at least one top-tier conference (ICML, ICLR, NeurIPS, CVPR, ICCV, etc.).
• Excellent communication skills.

Responsibilities

• Research, design, and implement novel methods for efficient deep learning in the focus areas.
• Publish original research.
• Collaborate with other team members and teams.
• Work with product groups to transfer technology.
• Collaborate with external researchers.

Skills

Deep learning theory

Large language models

Model training at scale

Research publication

Communication skills

Education

PhD in CS/Engineering

Tools

CUDA

Job description

NVIDIA seeks an outstanding PhD intern to advance efficient deep learning within the Deep Learning Efficiency Research (DLER) team in California. You will research diffusion LLMs, multimodal models, and efficient agentic AI, with opportunities to publish and transfer technology to product groups.

You will collaborate with researchers across cloud and edge environments, participating in a fast-paced, award-winning research culture and contributing to cutting-edge architecture and optimization