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

at Nvidia

📍 Santa Clara, United States

USD 30-94 per hour

INTERN

✅ On-site

Used Tools & Technologies

Machine Learning NLP

Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Python @ 3 Algorithms @ 3 Debugging @ 3 Experimentation @ 6 LLM @ 6 PyTorch @ 3 GPU @ 3 Deep Learning @ 3 AI @ 3 Reinforcement Learning @ 3

Details

We are looking for PhD research interns excited to advance the next generation of large language models through reinforcement learning. Our applied deep learning research team at NVIDIA has helped pioneer projects such as Megatron, MT-NLG, and DLSS. We build state-of-the-art foundation models and develop new methods to improve their reasoning, alignment, reliability, and ability to solve real-world tasks.

This internship will focus on algorithmic research at the intersection of reinforcement learning and large language models. You will design, implement, and evaluate new RL-based methods for improving LLM behavior, with a strong emphasis on hands-on experimentation and rapid prototyping at scale.

Responsibilities

Develop and prototype reinforcement learning algorithms for large language models
Explore methods for improving reasoning, alignment, instruction following, and multi-turn interaction
Design experiments to evaluate model behavior, robustness, hallucination, and task performance
Implement research ideas in Python and PyTorch, and run experiments on large-scale GPU clusters

Requirements

Pursuing a PhD in AI, ML, CS, CE, EE, Math, Physics, or a related field
Strong background in reinforcement learning and natural language processing
Excellent programming skills, especially in Python
Experience with deep learning frameworks such as PyTorch
Comfort with experimental research, debugging models, and working with large-scale training pipelines

Preferred / Ways to stand out

Publications or open-source contributions in RL, LLMs, alignment, reasoning, or post-training
Experience with RLHF, RLAIF, policy optimization, reward modeling, or agentic LLM systems
Strong intuition for both algorithms and large-scale implementation

Compensation and benefits

Internship hourly rate: 30 USD - 94 USD
Eligible for intern benefits (link provided in original posting)

Application information

Applications accepted at least until May 10, 2026
This posting is for an existing vacancy
NVIDIA uses AI tools in its recruiting processes
NVIDIA is an equal opportunity employer and committed to fostering a diverse work environment.