Applied Deep Learning PhD Research Intern, Reinforcement Learning for LLMs - Fall 2026
$0k - $0k • Remote • US, CA, Santa Clara
Posted 7d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
We are seeking PhD research interns to advance the next generation of large language models using reinforcement learning. Our applied deep learning research team pioneers projects like Megatron, MT-NLG, and DLSS, building state-of-the-art foundation models and developing new methods to enhance 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, involving the design, implementation, and evaluation of new RL-based methods for improving LLM behavior through hands-on experimentation and rapid prototyping at scale.
Responsibilities
- Develop and prototype reinforcement learning algorithms for large language models.
- Explore methods for improving LLM 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
- Currently 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.
Benefits
- Internship hourly rates: 38 USD - 94 USD.
- Eligibility for Intern benefits.