# PhD Intern - Efficient Deep Learning

**Company**: NVIDIA
**Job type**: internship
**Salary**: 38 USD - 94 USD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Research-Intern--Efficient-Deep-Learning---2027_JR2025478?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_071f618d-64f

## Description

NVIDIA is searching for an outstanding PhD intern working on efficient deep learning to join the Deep Learning Efficiency Research (DLER) team.

We are passionate about research that pushes boundaries but also has impact in the real world. The team has two core focuses: (1) efficient diffusion language models and multimodal generative models, and (2) efficient agentic AI with hybrid inference orchestration across cloud and edge.

You will work within an amazing and collaborative research team that consistently publishes at the top venues in computer vision and machine learning. Your contributions have the chance to create real impact on our products.

**Responsibilities**

- Research, design, and implement novel methods for efficient deep learning in one or both of the team’s focus areas:

+ Diffusion LLMs and multimodal models , sampling efficiency, adaptive unmasking, self-speculation / parallel decoding, training and distillation pipelines, and multimodal generation.   + Efficient agentic AI , hybrid inference orchestration across cloud and edge, routing and scheduling policies, on-device vs. cloud expert delegation, and resource-aware agent loops.

- Publish original research.

- Collaborate with other team members and teams.

- Work with product groups to transfer technology.

- Collaborate with external researchers.

**Requirements**

- 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.

**Nice to Have**

- Parallel programming (e.g., CUDA).

- Interest or experience in hybrid cloud–edge inference, orchestration, or adaptive routing.

- Background in pruning, quantization, NAS, or efficient backbones.

NVIDIA is widely considered to be one of the technology world’s most desirable employers with competitive salaries and a generous benefits package. Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD - 94 USD.

## Skills

### Required
- machine learning
- deep learning
- large language models
- diffusion language models
- multimodal models
- agentic systems
- model parallelization

### Nice to have
- parallel programming
- CUDA
- hybrid cloud–edge inference
- orchestration
- adaptive routing
- pruning
- quantization
- NAS
- efficient backbones

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Research-Intern--Efficient-Deep-Learning---2027_JR2025478?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)