Stateside Spec Engineering jobs in the United States

NVIDIA

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

Santa Clara, CA · On-site · Intern

Discipline
Software
Industry
Semiconductor

Spec sheet

Automatically summarized from the employer’s posting. Check the original description below for full requirements.

Applied Deep Learning Research

NVIDIA internship for PhD students in RL for LLMs; Python/PyTorch, large-scale GPU training, RL methods; hourly pay 38–94 USD; US Santa Clara, CA.

$38–$94 / hour · 0+ years · PhD ongoing in AI/ML/CS/CE/EE/Math/Physics

Required

  • Pursuing a PhD in AI, ML, CS, CE, EE, Math, Physics, or related field
  • Strong background in reinforcement learning
  • Experience with Python
  • Experience with PyTorch
  • Experience with large-scale training pipelines

Preferred

  • Publications or open-source contributions in RL, LLMs, alignment, reasoning
  • Experience with RLHF, RLAIF, policy optimization, reward modeling
  • Experience with large-scale GPU clusters
  • Hands-on experimentation and rapid prototyping

Benefits

  • medical
  • benefits
  • Intern benefits

Get new Software roles in California by email.

Free. We email only when something new matches, and only after you confirm. More options.

Employer description

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.

What you will be doing:

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

What we need to see:

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

Ways to stand out from the crowd:

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

If you are excited about using reinforcement learning to make language models more capable, reliable, and useful, this team could be a great fit.

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.

You will also be eligible for Intern benefits. ​

Applications for this job will be accepted at least until October 16, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Stateside Spec lists roles for engineering teams in the United States. Work-authorization notes come from the employer. We do not guarantee visa policy. Apply off-site. Report an issue with this listing View employer source