Deep Learning Performance Software Intern - 2027
At a glance
Junior AI Research role at NVIDIA. China, Shanghai · full-time.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and maintain SKILL, Wiki and agent harness materials
- Develop TileGym, the Triton CUDA TileIR backend and CUDA Tile
- Create fast deep learning kernels using tile-based GPU programming
- Tune end-to-end performance through analysis, profiling and optimization
What you bring
- You are pursuing an engineering or computer science degree; master's or doctoral study is preferred
- Strong C/C++ programming ability and sound software design skills
- You understand agent systems, including LLM APIs, tool use, memory, RAG and harness engineering
- You bring performance analysis or GPU programming experience, such as CUDA or OpenCL
Who this fits
This internship suits a student who can work independently and communicate well in a customer-focused, fast-moving team. Python and MLIR experience are useful extras.
From the employer
We are now looking for a Deep Learning Performance Software Engineering Intern!
We are expanding our research and development for deep learning. We seek excellent Software Engineers to join our team. We specialize in developing GPU-accelerated Deep learning software. Researchers around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in numerous areas. Join the team that builds software to enable new solutions. Your ability to work in a fast-paced customer-oriented team is required and excellent communication skills are necessary.
What you’ll be doing:
Creating and maintaining SKILL, Wiki, and agent harness
Develop TileGym, Triton CUDA TileIR backend and CUDA Tile
Develop highly optimized deep learning kernels through tile-based GPU programming model
End-to-end performance optimization through tile-based GPU programming model
Do performance optimization, analysis, and tuning
What we need to see:
Pursuing a degree from a university in an engineering or computer science related field. A masters or doctoral candidate is preferred.
Understands the core components of agentic systems, including LLM APIs, prompting, tool use/function calling, agent loops, planning, reasoning, memory, RAG, skills, MCP, sub-agents, multi-agent architectures, context engineering, and harness engineering.
Excellent C/C++ programming and software design skills
Python experience a plus
MLIR experience a plus
Performance modelling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU
GPU programming experience (CUDA or OpenCL) desired
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people on the planet working for us. If you're creative and autonomous, we want to hear from you!