4d ago
New

LLM Reinforcement Learning Framework Intern - 2027

ChinaChina·Shanghaientry
Other
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Quick Summary

Key Responsibilities

Help NVIDIA Nemo RL to be efficiently working under large scale post train workload. Adopt SOTA RL algorithms to Nemo RL. Improve RL rollout performance.

Requirements Summary

Having experience with VeRL, Miles, Slime, or Nemo RL is highly beneficial. Strong proficiency in programming languages such as Python, C++, or CUDA.

Technical Tools
Other

We are now looking for exceptionally dedicated individuals to join our team as LLM Reinforcement Learning Framework Intern!


At NVIDIA, we are renowned for our continual progress in the fields of graphics and parallel computing. By joining our Architecture group, you will be part of a dynamic team that is spearheading the AI revolution. This remarkable opportunity will allow you to work on innovative projects that extend the frontiers of GPU technology and AI.


Responsibilities

~1 min read
  • →Help NVIDIA Nemo RL to be efficiently working under large scale post train workload.
  • →Adopt SOTA RL algorithms to Nemo RL.
  • →Improve RL rollout performance.

Requirements

~1 min read
  • Having experience with VeRL, Miles, Slime, or Nemo RL is highly beneficial.
  • Strong proficiency in programming languages such as Python, C++, or CUDA.
  • Ambitious approach with a proven track record of taking initiative and delivering results.
  • Experience with PyTorch, RLHF (Reinforcement Learning with Human Feedback), and LLM training frameworks like FSDP/Megatron LLM is a plus.
  • Familiarity with agentic RL and inference engine development is preferred.
  • Pursuing A degree in Computer Science, Engineering, or a related field

Location & Eligibility

Where is the job
Shanghai, China
On-site at the office
Who can apply
CN

About this job

Who can apply
China
Posted
4 days ago
Employer
has 3,391 open jobs on Jobera in 29 countries.

Listing Details

Posted
November 3, 2026
First seen
November 3, 2026
Last seen
November 6, 2026

Posting Health

Days active
2
Repost count
0
Trust Level
49%
Scored at
November 6, 2026

Signal breakdown

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LLM Reinforcement Learning Framework Intern - 2027