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NVIDIA

Applied Deep Learning PhD Research Intern, Reinforcement Learning for LLMs - Fall 2026

NVIDIA

Published 07 May 2026
Santa Clara, CA, USA
Full Time

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Role Highlights

Languages used

Python

Key skills

Deep Learning
NLP
Reinforcement Learning
Interaction Design
foundation model
LLMs
PhD
Research
Reliability
ProtoTyping
AI
Machine Learning
Mathematics
Physics
Debugging
post-training
RLHF
Optimization
Modelling
Infrastructure

Tools, Libraries and Frameworks

GPUs
PyTorch

Description

The role involves developing and deploying machine learning models. It requires building and maintaining data pipelines for model training and inference. The position also entails collaborating with cross-functional teams to integrate AI solutions into existing products. The individual will be responsible for optimizing model performance and ensuring scalability.

Required Qualifications and Skills

The role requires proficiency in Python and SQL for data manipulation and model development. Experience with cloud platforms such as AWS is necessary. Familiarity with containerization technologies like Docker and Kubernetes is also essential. The candidate should have a strong understanding of machine learning frameworks including TensorFlow, PyTorch, and Scikit-learn. Experience in MLOps and data engineering practices is required.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

NVIDIA

Size

27685

Founded

HQ

Santa Clara, US

Public/Private

Public Company

Description

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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